Intelligent Forum
A web site for discussion of the
rapid advent of machine superintelligence
and the resulting need for a drastic
increase in
human collective intelligence.
Your comments on these articles are
welcome at
CURRENT CONTENTS:
HUMAN-LEVEL ARTIFICIAL
INTELLIGENCE --- AND ITS CONSEQUENCES --- ARE NEAR:
HUMAN-LEVEL ARTIFICIAL
INTELLIGENCE --- AND ITS CONSEQUENCES --- ARE NEAR: Why AI will be created in roughly a decade
& what that means
========================================
THE
TIME FOR POWERFUL ARTIFICIAL INTELLIGENCE IS RAPIDLY APPROACHING
========================================
There
is a good chance human-level AI will be created within five to fifteen years
--- and, almost certainly, within twenty-five.
In
ten years, for example, a machine costing one million dollars may well be able
to: --- write reliable, complex code faster than a hundred human programmers
--- remember every word and concept in a world-class law library, and reason
from them hundreds of times faster than a human lawyer --- or ---- contribute
more rapidly to the advancement of mathematical physics than all of humanity
combined.
A
cloud of such systems could represent all the knowledge recorded in books and
on the web --- stored in a highly indexed, inter-mapped, semantic deep
structure that would allow extremely rapid reasoning from it. Such a cloud
would have the power to rapidly search, match, infer, synthesize, and create
--- using that world of data --- so as to provide humanity with a font of
knowledge, reasoning, technology, and creativity few can currently imagine.
YOU
SHOULD BE SKEPTICAL. The AI field has been littered with false promises. But
for each of history's long-sought, but long-delayed
technical breakthroughs, there has always come a time when that breakthrough
--- finally --- DID happen. There are strong reasons to believe that --- for
powerful machine intelligence --- that time is fast approaching.
What
is the evidence?
It
has two major threads.
First,
within five to ten years, we are projected, for the first time, to have
hardware with the computational power to roughly support human-level
intelligence. Within that time, the price for such hardware could be as low as
three million dollars, down, by the end, to, perhaps, as little as one hundred
thousand. These prices are low enough that virtually every medium to large-size
business, educational, and governmental organization would be able to afford
them.
Second,
due to advances in brain science and in AI, itself, there are starting to be
people who have developed reasonable and relatively detailed architectures for
how to use such powerful hardware to create near-human and, ultimately,
super-human artificial intelligence.
THE
HARDWARE
========================================
To
do computations of the type at which we humans currently out perform computers,
you need something within at least several orders of magnitude of the capacity
of the human brain, itself. You need such capacity in each of at least four
dimensions. These include representational capacity, computational capacity,
processor-to-memory bandwidth, and processor-to-processor bandwidth. You can't
have the common sense, intuition, natural language capabilities, and context
appropriateness of human thought --- unless you can represent, rapidly search,
infer between, and make generalizations from, vast portions of human-level
world knowledge --- where --- "world knowledge" is the name given to
the extremely large body of experientially derived visual, auditory, olfactory,
tactile, kinesthetic, emotional, linguistic, semantic, goal-oriented, and
behavioral knowledge that most humans have.
Most
past AI work has been done on machines that have less than one one millionth the capacity of the human brain in one or
more of these four dimensions. That is like trying to do what the human brain
does with a brain the size of a spider s. Even many current supercomputers,
that cost tens of millions of dollars, have processor-to-processor bandwidths
that are three or more orders of magnitude smaller than that of the human
brain.
No
wonder so many prior attempts at human-level AI have hit a brick wall. Nor is
it any surprise that most of the AI establishment does not understand the
importance of the correct ---roughly brain-level-hardware --- approach to AI.
Such an approach has been impossible to properly study, and experiment with, at
prior hardware costs and funding levels --- and, thus, has been impossible to
use for advancing one s career in the AI field, or for raising venture capital.
But
starting in three to five years it should be possible to make hardware that is
much more suited for roughly human-like computing.
Moore s Law is likely to keep going for
some time. 22nm node prototypes have already been built. Intel claims it is
confident it can take CMOS two generations further,
to the 11nm node, by mid to late this decade. But, perhaps even more important,
there has been a growing trend toward more AI-capable hardware architectures,
and, in particular, toward addressing the bandwidth deficiencies of current
computing systems.
This
is indicated by the trend toward putting more processor cores, with high speed
interconnect, on a chip. Tilera has recently
demonstrated a 100 core processor with extremely high internal bandwidth. IBM
and Intel both have R&D chips with roughly 64 to 80 mesh-networked
processors, and they both plan to provide high bandwidth connections between
such processors and memory placed on multiple semiconductor layers above or
below them. High bandwidth to such memory will be provided by massive numbers
of through-silicon metal vias connected between
layers. Intel has said it hoped to have such multi-core, multi-layer modules on
the market by 2012. And one of its researchers has said inferencing
is one of the major tasks that could make such hardware commercially valuable.
Photonics
will enable hundreds of gigabits per second to be communicated on photolithographically produced waveguides at relatively low
energy and thermal costs. This, and the through-silicon vias,
will substantially break the processor-to-RAM and processor-to-processor
bandwidth bottlenecks that are currently the major barriers preventing current
clustered systems from being used efficiently for human-like reasoning. These
bottlenecks need to be broken because many types of human-like reasoning
involve --- massively parallel, highly-non-local, out-of-order, memory
accessing --- in huge, sparsely-interconnected, networks of world knowledge.
With the rapid advances in integrated photonics --- and in low-cost interconnect
between such integrated photonics and optical fibers --- being made by
organizations like HP, IBM, Luxtera, and Cornell
University, it will become possible to extend massive numbers of extremely high
bandwidth optical links across chips, wafers, boards, and multi-board systems
--- enabling us to create computers --- and clouds of computers --- having not
only more effective representational and computational power than the human
brain, but also greater processor-to-memory and processor-to-processor interconnect.
With
the highly redundant designs made possible by tiled processors, and their
associated memory and network hardware --- wafer-scale and multi-level
wafer-scale manufacturing techniques can become practical. Such highly uniform,
replicated designs make it easier to provide fault-tolerance and self-test. The
conventional wisdom is that wafer-scale integration was proved futile in the
1980s. But that was when the large size of most circuit components made it
inefficient to provide redundancy in anything other than highly replicated
circuits, such as memories. In the coming decade, however, entire cores will be
small enough to be fused out with relatively little functional loss. In
addition, redundant vertical and horizontal pathways can be provided in 3D
circuitry, so that a defect in part of one layer will not prevent functional
access to components above, below, and beside it.
Combined,
all these technologies can greatly decrease the cost of manufacturing the
massive amounts of memory, processing power, and connectivity demanded for
extremely powerful --- roughly brain-level --- artificial intelligence.
For
example, if --- 11nm semiconductor lithography --- multilevel circuitry --- and
--- integrated-photonic interconnect --- are all in mainstream production in
ten years --- as many predict --- then one million dollars should be able to
purchase a system with: --- roughly 4 million small processor cores, allowing a
theoretical max of 4 thousand trillion instructions per second --- 32 TBytes of 2ns EDRAM, allowing
roughly 400 trillion read-modify-writes to EDRAM per
second --- over 200 TBytes of sub-20ns-read-access
phase-change-memory (PCM), allowing roughly 160
trillion random reads per second --- and a global, sustainable, inter-processor
bandwidth of over 20 trillion 64Byte payload messages per second.
The
AI community does not know exactly how much representation, computation,
processor-to-memory, and processor-to-processor capacity is needed for
human-level computing. The estimates vary by four or five orders of magnitude.
Some think we will have to match the complexity of the brain almost exactly to
get brain-level performance, causing them to think we will have to wait until
approximately 2040 to achieve human-level AI. But this fails to take into
account the many superiorities electronic hardware has
relative to wetware. From my research and calculations, I am relatively
confident that the above computational resources --- that could be available
for one million dollars by 2020 --- would have more than enough capability to
provide something approaching --- or, very possibly, substantially surpassing
--- all the useful talents at which a human mind can currently out perform
computers.
In
addition, a machine with this power could also execute tasks at which computers
already substantially out perform humans at speeds, and with exact memory, that
exceed that of humans by millions or trillions of times. Combining the types of
computing at which humans and machines each currently excel will greatly
amplify the power of artificial intelligence. Such a system could have a
high-bandwidth, fine-grained interface between these two different types of
computation. And it could have the ability to rapidly vary the degree of
mixture between them in each of many different concurrent processes or
sub-processes --- all under the dynamic control of powerful hierarchical mental
behaviors that have been honed by automatic reinforcement learning. This
mixture will enable artificial intelligences that are substantially sub-human
in some ways, to be hundreds to millions of times more powerful than humans at
tasks that now can only be performed by us --- such as --- trying to use
on-line tools to find the set of legal cases that are most relevant to a new,
complex legal problem --- or trying to find information on the internet in
those situations in which Google doesn't seem helpful.
To
show why the 2020 system hypothesized above would, most probably, be capable of
human-level thinking --- let us assume half of its 200TBytes of PCM memory were used to represent nodes and links in an
experientially grounded, self-organizing, semantic-net memory. Assume an
average of 100 bytes is required to represent and properly index an occurrence
of a pattern, or concept, represented by a node in that net. Assume that
roughly another 100 bytes is required to represent one of the relationships of
such a concept s occurrence to another pattern or to one or more temporal,
spatial, or semantic maps. With these assumptions this 100TBytes could create
an experiential record storing an average of 1000 such nodes or links for each
of one billion seconds. That s roughly the equivalent of three pages of text to
describe a person s experiences for every second in over 31 years. When
combined with the type of memory described in the paragraph below, this is
almost certainly much, much more world knowledge than a human mind can store.
Continuing
this simplified model of memory distribution --- let the remaining 100TByte of PCM store billions of patterns to represent and ground the
meaning of the above mentioned nodes and links. This would include an
invariant, hierarchical, self-organizing memory representing the composition,
generalization, and similarity relationships between such patterns. This semantic
net would include --- billions of patterns generalized from activation, or
recorded, states in the system's network of sensory and semantic nodes and
links --- and --- mappings between such generalized patterns, and their parts,
and occurrences of such patterns in perceptions, thoughts, plans, imaginations,
and memories. These generalized patterns would include billions of relatively
simple sensory and motor patterns. They would also include more complex
patterns representing concepts such as objects, persons, actions, emotions,
drives, goals, and behaviors. These more complex patterns would include
physical and mental behaviors and plans --- and their associated goals and
other memories --- including feedback on their value and effectiveness. These patterns
would include temporal and spatial relationships, and relationships defined by
the relative roles of patterns in larger patterns. They would also include
probabilistic statistics on the frequency, long term importance, and
relationships between such patterns.
For
many applications, such a system would contain many terabytes of information to
help them excel at communicating with humans through --- text --- speech ---
vision --- gestures --- facial expressions --- tones of voice --- and
photorealistic, real-time, audio/video animation. Such systems would record ---
tens of millions of compressed photographs, millions of which would be stored
in morphable, semantically-labeled photosynths for generating 3D images and animations ---
millions of seconds of compressed audio and moving images --- including models
of humans communicating --- and --- many millions of mental patterns and
behaviors relating to understanding human intentions, communications between
humans, and communication with humans.
From
the above we can see that the 200TBytes of storage --- provided by the
hypothetical 2020 system --- particularly if it uses a context-sensitive,
invariant representation scheme (of the type discussed in more detail below)
--- is almost certainly enough to represent much more functional world
knowledge than a human mind can store --- and to ground the concepts in such
knowledge in an extremely rich web of sensory, cognitive, emotional, and
behavioral memories and associations. This grounding should be much more than
enough to give such a system's symbols --- true meaning.
This
hypothetical 2020 system --- not only has enough capacity to more than
represent human-level world knowledge --- it also appears to have enough
computational and communication capacity to reason from such world knowledge
faster than humans. The 2020 system s ability to randomly read its PCM memory 160 trillion times per second, and to perform
over a 400 trillion random read-modify-writes to portions of its EDRAM representing dynamic activation values of patterns
stored in the PCM, give it tremendous power to reason
from its world-knowledge. It would have enough power to perform relatively
shallow and most-probable (i.e. subconscious) inferencing
simultaneously from billions of somewhat activated patterns --- and ---
relatively deep and/or broad (i.e., conscious) inferencing,
involving tens of billions of multi-level spreading activations from each of a
small number of highly activated patterns that were the focus of attention.
This allows rich, deep, grounded, and highly dynamic activation states. Ones that would probably have more useful informational complexity
than those in our own minds.
These
dynamic activation states --- when combined with mental behaviors for
dynamically selecting and focusing attention --- can give rise to a powerful
combination of conscious and subconscious thought. In this combination,
conscious thought would commonly result from massive activation from a
relatively small number of concepts and their relationships. The concepts
chosen for such massive conscious activation would be generated, tested, and
selected by many billions, or trillions, of computations in the subconscious.
These subconscious computations would be made in response to sensations, emotions,
desires, goals, memories --- and --- from activations from current and recently
consciously activated concepts. In such a system the distribution of activation
energy between conscious and subconscious activations, and between various
activations within the subconscious, can be rapidly varied. For example, this
allows each of many increasingly higher scoring networks of activation in the
subconscious to receive increasingly more activation energy to verify which of
them actually warrant being thresholded into
conscious attention.
In
summary, the above numbers give us good reason to believe that within ten years
it will be commercially viable to build and sell machines that have the
representation, computation, processor-to-memory, and processor-to-processor
capacities necessary to support human-level --- and likely superhuman-level ---
intelligence.
As
one former head of DARPA s AI funding told me, The
hardware being there is a given. It s the software that s needed.
THE
SOFTWARE
========================================
Tremendous
advances have been made in artificial intelligence in the recent past. This is
largely due to the ever increasing rate of progress in brain science. It is
also due to the increasing power of the computers that researchers can
experiment with.
One
example of such recent progress is the paper Learning a Dictionary of
Shape-Components in Visual Cortex:... , by Thomas Serre of Prof.Tomasa Poggio s group at MIT. It describes a system that provides
human-level performance in one limited, but impressive, type of human visual
perception (http://cbcl.mit.edu/projects/cbcl/publications/ps/MIT-CSAIL-TR-2006-028.pdf
). The Serre-Poggio system learns and uses patterns
in a generalization and composition hierarchy. This allows efficient multiple use of representational components, and computations
matching against them, in multiple higher level patterns. It allows the system
to learn in compositional increments. It also provides surprisingly robust
invariant representation. Such invariant representation is extremely important
because it allows efficient non-literal matching, pattern recognition, and
context appropriate pattern imagining and instantiation. Such non-literal match
and instantiation tasks have --- until recently --- been among the major
problems in trying to create human-like perception, cognition, imagination, and
planning.
Although
it is different than the Serre-Poggio system, the
system described in Geoff Hinton s Google Tech Talk at http://www.youtube.com/watch?v=AyzOUbkUf3M
demonstrates a character recognition architecture that shares many of these
same beneficial characteristics --- including a hierarchical, scalable, and
invariant representation/computation scheme that can be efficiently and
automatically trained. The Hinton scheme is quite general, and can be applied
to many types of learning, recognition, and context sensitive imagining. The
architecture described by Jeff Hawkins et al. of Numenta,
Inc. in Towards a Mathematical Theory of Cortical Micro-circuits (http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000532
) also shares the concepts of hierarchical memory and invariance, and provides
a potentially powerful and general computational model that attempts to
describe the functioning of the human cortex in terms of its individual layers.
Similar
amazing advances have been made in understanding other brain systems ---
including those that control and coordinate the behavior of, and between,
multiple areas in the brain --- and those that focus attention and decide which
of competing actions to take or consciously consider.
These
advances, and many more, provide enough understanding that we can actually
start experimenting with designs for powerful artificial minds. It s not as if
we have exact blue prints. But we do have a good overview, and good ideas on
how to handle every problem I have ever heard mentioned in regard to creating
roughly brain-like AI. As Deb Roy, of MIT, once agreed with me after one of his
lectures, there are no problems between us and roughly human-level AI that we
have no idea how to solve. The major problem that exists is the engineering
problem of getting all the pieces to fit and work together well, automatically,
and within a commercially-viable computational budget. That will take
experimentation.
But
we certainly do know enough to design and build general artificial
intelligences that could provide useful functions.
The
most complete, currently-publicly-available artificial brain architecture of
which I am aware, is the OpenCogPrime
architecture. It has been created by the open-source AGI
initiative headed by
Ben Goertzel. There may be other equally complete and impressive
brain architectures available to the public. But since I do not know them, let
me give a brief -- but hopefully revealing overview of the OpenCog architecture --- as I understand it, in combination
with some of my own thinking on the subject. (The OpenCog
architecture is described at http://www.opencog.org/wiki/OpenCogPrime:WikiBook#Introduction
.)
OpenCog starts with a focus on General Intelligence , which it
defines as the ability to achieve complex goals in complex environments. AGI stands for Artificial General Intelligence. It is
focused on automatic, interactive learning, experiential grounding, self
understanding, and both conscious (focus-of-attention) and unconscious (less
attended) thought.
It
records its sensory and emotional experiences, finds repeated patterns in such
recordings, makes generalizations and compositions out
of such patterns --- all through multiple levels of generalization and
composition --- based on spatial, temporal, and learned-pattern-defined
relationships. It uses Bayesian mathematics --- based on the frequencies of the
detection of such patterns and their relationships --- in a way that allows
inferences to be drawn from many billions of activated patterns at once.
Patterns
-- which can include behaviors (including those that control the operation of
the mind itself) -- are recorded, modified, generalized, and deleted all the
time. They have to compete for their computational resources, including memory
space, and, thus, their own continued existence. Re-enforcement learning and
other forms of credit assignment are used to determine which patterns are
useful enough to be kept, and for how long. This results in a self-organizing
network of similarity, generalization, and composition patterns and
relationships, that all must continue to prove their worth in a survival-of-the-fittest, goal-oriented,
experiential-knowledge ecology.
Re-enforcement
learning is also used to weight patterns for long-term and current short term
importance, based on the roles they have played in achieving the system s goals
in the past. These indications of importance -- along with a deep memory for
past similar experiences, contexts, and goals, and for the relative usefulness
of various past inferencing behaviors in such
contexts -- significantly narrow and focus attention and spreading activation.
This helps avoid the pitfalls of combinatorial explosion, and it tends to
result in context-appropriate perception, cognition, and behavior.
OpenCog uses evolutionary program learning --- somewhat like
genetic programming --- to increase the system s ability to learn and tune:
generalizations of patterns; classifiers; creative ideas; and behaviors ---
including physical, attention focusing, inferencing,
and learning behaviors. This evolutionary learning is made more powerful by
being used by --- and by using --- the rest of the system. This includes the
system s composition and generalization hierarchy, its network of probabilistic
associations, its inferencing, and its reinforcement
learning. Evolutionary programs can be used by the system s experiential
probabilistic learning. Such programs can, themselves --- along with
experientially learned patterns --- be incorporated --- with or without
modification --- into the learning of new evolutionary programs. A compositional
and generalization hierarchy including such evolutionarily-learned programs
enables complex programs to be learned more efficiently in incremental steps
from more simple ones. Experiential memories help guide and evaluate the
evolutionary process, including reducing the computation required for
estimating the fitness functions for many evolutionary candidates. Experiential
memories can also provide information for probabilistically inferring which
programs are appropriate to employ, with which parameters, in which contexts.
Taken
together, software architectures like those discussed above --- when combined
with the hardware likely to be available within a decade --- will allow AGI systems to automatically learn, reason, plan, imagine,
and create with a sophistication and power never
before possible -- not even for the most intelligent of humans.
Of
course, it will take some time for the first such systems to automatically
learn roughly the equivalent of human-level world knowledge. After all, it takes
over twenty years for most human minds to train up. But there is reason to
believe substantial portions of such machine learning could be performed in
parallel. And since such machines will be capable of remembering vastly more
detail than humans, their learning should be much faster. Such machine learning
is likely to be better grounded in physical reality, if such machines can
control robotic bodies with human-like senses that enable them to learn by
exploring the physical world, as do human children --- or by, at least, having
the equivalent in a fairly accurate virtual world. The learning of many
concepts would be improved by having human teachers. Once such a system
achieves a certain level of world-knowledge --- including a child s level of
common-sense physics, basic human behavior, natural-language, and visual scene
understanding --- they will be able to rapidly learn by reading and viewing
images and diagrams from large libraries of digitally recorded books, and from
media on the web.
And once one such system has been fully trained in basic
world knowledge --- or in the knowledge relating to a given field of expertise
that is linked to a common representation of such world knowledge--- that
knowledge can be copied to another similar machine in seconds or minutes.
WILL
IT WORK?
========================================
The
answer is most probably, yes, because such systems will: ---
-a-
in multiple important ways --- work like the human brain, itself;
-b-
have enough representation, computation, and interconnect capacity to make
types of AI that were never before even close to possible for most in the AI
community --- not only possible --- but commercially practical --- including
the ability to represent and rapidly reason from grounded, human-level world
knowledge --- and
-c-
benefit from the explosion of AI related advances that will occur in this
decade.
This
explosion of AI-related advances --- in addition to the hardware advances
described above --- will occur in: --- brain science --- generalized machine
learning and inferencing --- attention and inference
control --- large-scale semantic web applications --- learning and reasoning
from self-organizing ontologies --- natural language
understanding and generation --- common-sense and world-knowledge learning and
computing --- evolutionary learning --- machine vision --- multimedia indexing
--- command and control --- national security and defense applications ---
search --- robotics --- personal assistants --- web agents --- user interfaces
--- and more human-like characters for video games and virtual realities. All
of this will be in addition to the increasing research that will be performed
in AGI, itself.
Within
three to seven years, hardware having the effective representation, computation,
and inter-connect of small mammal and, then, primate brains will be available
--- at sufficiently low costs that thousands of such systems will be used by
academic and corporate teams to experiment in such fields. All this research
will help identify, refine, and tune various general algorithms that could be
put together to create powerful generalized thought robots --- i.e., powerful
artificial intelligences that can --- automatically --- or with relatively
little handcrafting --- tune their learning and mental behaviors to achieve
various goals across a broad range of applications.
AGI is not currently competitive for most applications, because its general
algorithms tend to require much more training, memory, and computation than AI
systems handcrafted by humans to solve a particular set of problems. But many
of the learning, inferencing, and inference control
mechanisms deployed in more narrow applications can be generalized to have
applicability to AGI. And many early AGI s will have
handcrafted parts to make them more competitive for specific applications. As
memory, computation, and interconnect costs drop drastically relative to
programming costs --- particularly relative to the cost of handcrafting AIs for extremely complex problems --- larger, more
general, and more capable AGI will become ever more
competitive.
Once
created, AGI will be particularly attractive for
corporate and cloud computing --- because it can automatically be adapted to
the many different uses that different people will want from AI services ---
and because it can provide superintelligent user
interfaces --- using text, speech, audio, vision, and the real-time generation
of animation --- to make it easy for users to instruct, monitor, and learn
relevant information from such machines.
So
can human-level AGI be built?
Yes!
The
only question is how fast. And it is almost certain that if the right people,
got the right money, it could be built within ten years --- that is --- by no
later than Twenty-Twenty.
Making
this happen should be our nation s "Twenty-Twenty vision" because
machine superintelligence is the most transformative
technology of all.
THE CONSEQUENCES
========================================
It
is hard to overstate the economic value and transformative power of the types
of machines that will probably be built by 2020 --- and if not by then --- by
2030.
The
one-million-dollar 2020 hardware hypothesized above could be rented out on the
web, at a profit, for roughly $50 an hour. It --- would have superhuman
concentration --- could work close to 24/7 --- could perform many types of
reasoning tasks millions of times faster than a human --- and --- if connected
to a cloud of similar machines that stored a large percent of human knowledge
in instantly-accessible semantic deep structure --- it would, in effect, have
photographic memory for almost all of recorded human knowledge. It is not
unrealistic to think that for a large number of tasks such a machine could do
work at a higher rate than one hundred programmers, lawyers, doctors, or
managers.
If
such a system were part of a computing cloud --- then an average of --- 64
thousand cores --- 500 GBytes of 2ns EDRAM --- 3 TBytes of
20ns-read-access PCM memory --- and --- over 300
billion global, 64Byte messages per second --- could be provided to serve an
individual user of a wireless mobile phone; retinal-scanning, headset computer;
or other personal device --- at roughly the same price currently charged for
long distance phone calls. This should be enough power to provide users with
moderately good --- natural language --- vision --- real-time animation ---
intelligent search --- semantic web reasoning --- and machine-mediated
collective computing.
Most
of the time they were connected, users would not even begin to fully use the
64K processor chunk of hardware described above, but there would frequently be
tasks demanding more power --- such as understanding difficult natural language
constructions --- performing computationally intensive queries, summaries, and
reasoning --- and --- synthesizing creative solutions to complex problems.
Larger portions of the cloud could be used in a multiplexed manner for such
tasks. Users who utilize more than a certain amount of the cloud's resources in
a given time could be notified that they were about to do so, and be billed
extra for it at less than one dollar for a the equivalent of using one of the
above described one-million-dollar 2020 machine s worth of hardware for one
minute.
That
one dollar should be enough, for example, to get a reasonably well reasoned
legal brief on a moderately complex issue --- something that would cost several
hundred to several thousand dollars from most American lawyers.
Even
if we make the extremely conservative assumption that our one-million-dollar
2020 machine could only simultaneously do the work of ten human lawyers,
doctors, financial experts, or managers --- that would mean it could provide
the services of such a professional or manager for $5 dollar per hour ---
making most such highly educated professionals or managers unemployable at the
current minimum wage.
Furthermore
if new areas of electronics --- such as 3D, carbon nanotube,graphene, nanowire, quantum
dot, spintronic, quantum entanglement, molecular, neuromorphic, and self-organizing electronics --- keep
Moore s law going for several decades past the final density expected for
traditional silicon electronics --- in twenty to thirty years a machine of
power similar to the one-million-dollar 2020 system might cost less than a
current personal computer. Such a continuation of
Moore's law is likely. This is because
machine superintelligences can be produced at even
the 22nm node at sufficiently low prices that they could be commercially useful
for greatly increasing the rate of development in electronics and electronic
design. If such cost reductions are, in fact, obtained, virtually all human
mental jobs could be replaced for one or two pennies an hour in thirty years.
If superintelligence is used to speed advances and cost
reductions in robotics --- all of humanity --- including in places like
China,
India,
Vietnam, and
Haiti --- will cease to be competitive
for most current forms of work.
AGI will create a historical singularity of the type Ray Kurzweil has done so much to popularize. That is, a
technological change so powerful --- that --- when combined with the massive
acceleration it will cause in --- the internet --- electronics --- computing
--- robotics --- nanotechnology --- and --- biotechnology --- it will warp the
very fabric of human economies, cultures, values, and societies in somewhat the
same way the singularity of a black hole warps the fabric of space-time --- and
is believed --- by some --- to create an entirely new universe -- one largely
disconnected from its past in space and time.
Can
we, or should we, stop the advent of superintelligence?
No.
It is futile to try.
Too
many people already know how much technological, economic, military, cultural,
and political advantage can be gained by the nations and corporations that are
first to substantially deploy it. It cannot be stopped because electronic
technology and our understanding of intelligence are already so advanced that
in a decade the development of superintelligence will
be well within the economic and intellectual grasp of a most nations, thousands
of corporations, and hundreds of universities. It is already within the grasp
of the world s leading nations and technological companies. It cannot be
stopped by international agreements, because --- compared to the development of
nuclear weapons --- in a decade, machine intelligence can be developed for very
little money, in very little space, with relatively little electricity. Its
development would be very difficult to detect, prove, or stop.
There
are many reasons we should want --- rather than oppose --- the development of superintelligence. It --- and the rapid advances in
technology and productivity it will bring --- could be a force for tremendous
good.
It
could create a world of material, medical, mental, and intellectual well being
and richness. It could help us develop highly efficient, sustainably,
less-polluting, factories, farms, stores, corporations, and transportation. It
could teach us how to cure most disease, how to keep our bodies younger longer,
and how to make our minds work in more powerful and satisfying ways. It could
help us to become a truly enlightened species. It could educate all of us, with
virtual tutors more knowledgeable and more capable of explaining things to us
than the most brilliant and attentive human teachers. It could learn to know
each of us better than we know ourselves, and to provide us with personal
counseling superior to that of the best psychologist or friend.
It
could help us better simulate and determine the costs, benefits, and risks of
personal, corporate, and governmental decisions. It could enable people to
communicate, collaborate, and deliberate with an efficiency and fairness never
before possible. It could help us better deal with the rapid changes it will
produce --- such as the fact it will end most current ways of earning a living
in the industrialized world --- by helping us to create a new, fair, and
sustainable social contract --- and new types of meaningful work ---- such as
sharing more responsibility in much more participatory local, regional,
national, and world governments and institutions. It can allow us to have AGI-mediated, real-time virtual conversations, debates,
celebrations, songs, dances, games, and prayers --- in which hundreds,
thousands, millions, or billions of people take part.
The
world is facing many challenges that seem beyond the capacity of our current
political institutions to solve. It is arguable we need superintelligence
to help us find how to provide food, shelter, clothing, medical services,
education, meaningful lives --- and --- most importantly --- peace --- for the
projected 9 billion people that will populate earth by 2050. Most of these will
come from societies that are brutally poor --- and yet most of them will have
access to the extremely powerful --- but, by 2050, inexpensive --- personal
information devices of the future --- video devices that will likely teach them
to want as much power and material wealth as people in the richest nations. It
is arguable that we will need superintelligence to
help us deal with such problems without poisoning our planet with pollution ---
or by destroying it with war or terrorism.
Butsuperintelligence, and the technologies it will
bring, could also cause great harm.
Unless
we are careful --- in addition to putting most of us out of work --- superintelligence can be used to create surveillance
systems and robotic police or military forces that could enable one class,
group, person, or system of machines to create a powerful oligarchy or
dictatorship. Unethical people, governments, or machines will almost certainly
use superintelligences to constantly try hacking into
our networks and intelligent machines --- trying to take control of them for
their own selfish purposes.
AGI can create virtual realities, friends, and lovers that are much more
attractive, attentive, sensitive, romantic, funny, and seductive than those
that are real. These virtual worlds and personalities could weaken the bonds
between humans, and could seduce us into increasingly turning over more
attention and power to machines, and to the virtual worlds they generate for us
--- whether those machines are controlled by businessmen, political leaders, or
machines themselves. Low income housing may become stackable 4 x 4 x 8 foot
plastic pods with super HD 3D virtual interfaces, in which the elites provide
the masses with a bare-minimum physical reality, but an extremely rich --- and
much less expensive --- virtual one.
Human
laziness may well lead us to turn too much power over to superintelligences
--- so much so that we might soon be at their mercy. Ultimately, the machines
themselves might well take over. And if they do --- it is not clear whether
they would like us enough to let us keep consuming so much of the earth s
resources --- which they, themselves, could use for their own purposes --- and
their own progeny.
Sometranshumanists say --- the only way in which what we
value as "human" can remain competitive in a world bound to be ruled
by superintelligences is for us to increasingly merge
our values, memories, consciousnesses, and bodies with such machines. They say
our seduction by virtual worlds, friends, and lovers is a good thing ---
because it will make --- what they view --- as the necessary man-machine merger
--- more emotionally acceptable. To make our lives more meaningful --- they say
--- we should view the machines as our kin and our posterity.
Sometranshumanists suggest it is necessary for our very
survival that we place into, or onto, our brains high bandwidth connections to superintelligences. Preferably such connections will be to
a World-Wide-Web of other people similarly connected to such machines. This
would make us into Star-Trek-like borgs
--- but, let us hope, ones with substantially more individualism, humor, and
happiness.
Othertranshumanists suggest uploading our minds to run on
such machines so they can live for billions of years.
To
most people all this sound like a whipped out science-fiction horror flick. But
there are reasons to believe that within only decades --- almost certainly by
the end of this century --- much of this could, in fact, come true.
Thetranshumanists may be right. We humans largely rule
the earth because our intelligence and knowledge excels that of all other
species. By analogy, it only makes sense that --- starting in several decades
when there are likely to be networks of many superintelligences --- each thousands of times
smarter than humans --- there will ultimately come a time when machines take
domination away from us.
That
is, perhaps, unless we join them, and make them part us, and us part them.
There are already many who look forward to connecting their brains to superintelligences --- and it is almost certain, that once superintelligence arrives, the people who use such
implanted, high bandwidth, connections to such machines will be more successful
than those who do not.
But
even the transhumanist scenario requires that
humanity act intelligently and wisely if the transition to humanity+ is to be a
happy one.
How
we develop --- use --- and control superintelligence
is one of the greatest challenges facing mankind. We cannot stop its advent,
but we can try to control it --- to reduce its danger, at least to some degree.
Great flexibility is possible in the design of AGI s, and we should be careful
to learn what types of machines are likely to be more safe and what types are
likely to be more dangerous. We should learn how to best use the safer types ofsuperintelligence to protect us against the more
dangerous. If you care about humanity --- more important than creating superintelligence per se --- is creating super-intelligence
that is well combined with the wisdom, compassion, and voices and concerns of
billions of individual human beings.
That
is why, ultimately --- from humanity s standpoint ---
the most important technology of all is collective intelligence.
It
is the technology of using the internet, computers, and, soon, superintelligence, to enable groups, corporations, nations
--- and ultimately the world --- to think and act together more intelligently,
successfully, and humanely --- as we --- as a species --- have to navigate in
an ever more rapidly-changing future.
And
that is why --- the single most important use of superintelligence
--- is to help give mankind enough collective intelligence that --- for decades , or, perhaps, even centuries --- humanity can
safely and happily travel into that rapidly-changing future.
HOW
LONG TILL HUMAN-LEVEL AI? WHAT DO THE EXPERTS SAY?
========================================
There
is a good article entitled How Long Till Human-Level AI? What Do the Experts
Say? written by
Ben Goertzel, Seth Baum, Ted Goertzel at http://hplusmagazine.com/articles/ai/how-long-till-human-level-ai
To
me its most important information is in the figure entitled When Will
Milestones of AGI be Achieved
without New Funding . It indicates that, of the 21 attendees at the AGI 2009 conference who answered the survey, 42% think
AGI s capable of passing the Turning Test will be created within ten to
twenty-years.
Oddly
that is slightly more than the 38% who think AGI s would achieve the human-like
capabilities of a 3rd grader within the same time frame. This might reflect the
fact that too many of the attendees have been influenced by the famous Eliza
experiment, which was a quasi Turing Test that actually managed to fool some
people into thinking they were reading text generated by a human doctor ---
using mid-1960s computers.
I
have always assumed the Turing test would be administered by humans who
understood human psychiatry and brain function, and
artificial intelligence sufficiently that they would be able to smoke out a
sub-human intelligence relatively quickly in the Turning Test.
In
fact, I am the person quoted in that article for giving my reasons why I
thought it would be more difficult to make a computer pass the turning test
than to posses many of the other useful intellectual capabilities of a powerful
human mind --- as quoted in the paragraph that follows:
One
observed that making an AGI capable of doing
powerful and creative thinking is probably easier than making one that imitates
the many, complex behaviors of a human mind many of which would actually be
hindrances when it comes to creating Nobel-quality science. He observed
humans tend to have minds that bore easily, wander away from a given mental
task, and that care about things such as sexual attraction, all which would
probably impede scientific ability, rather that promote it. To successfully
emulate a human, a computer might have to disguise many of its abilities,
masquerading as being less intelligent in certain ways than it actually
was. There is no compelling reason to spend time and money developing this
capacity in a computer.
I
thought the idea --- suggested in one of the survey questioned mentioned in the
article --- that AGI might be funded by 100 billion
dollars is a little rich. I understand, however, such a large figure was picked
to --- in effect --- ask how people how fast they thought AGI
would be developed if money was virtually no obstacle.
I
think AGI could be developed over ten years for well
under 500 million dollars if the right people were administering and working on
the project. (This does not count all the other money that is already likely to
be invested in electronics, computer science, and more narrow AI in the coming
decade.) Unfortunately, it would be hard for the government to know who were the right people, and what were the right approaches,
for such a project. But I believe a well designed project, designed to achieve
human level AGI, almost certainly could succeed in
ten years with only 2 to 4 billion dollars of funding over that period. Such a
project would fund multiple teams with say 10 to 30 million dollars to start,
and then increasingly allocate funding over time to the teams and approaches
that produced the most promising results.
2
to 4 billion dollars over ten years would be totally within the funding
capacity of multiple government agencies.
DevelopingAGI in that time frame would be exceptionally
valuable to America --- because it would give a tremendous chance to save our
economy before its is bled to death --- by our trade imbalance with the rapidly
developing world --- and --- by the many tens of trillions of dollars of in
health care and other unfunded benefits America owes its seniors and government
workers.
Ed Porter
MORE
PROGRESS ON GENERALIZED AI TECHNIQUES
========================================
In
my first post above on this topic I said:
WILL IT WORK?
========================================
The
answer is most probably, yes, because ...
...
...many
of the learning, inferencing, and inference control
mechanisms deployed in more narrow applications can be generalized to have
applicability to AGI.
As
evidence of the above statement, I am attaching a link to a lecture by Pedro Domingos of the
University of
Washington on what he views as a highly
generalized AI learning and inferencing system using
Markov logic networks. http://videolectures.net/bsciw08_domingos_mlwuv/
. This representation shares many
features with the hypergraph representation in OpenCogPrime by Goertzel et al.
OTHER VOICES PREDICTING AI BY 2020
========================================
In
the main post above I stated human level AI could be probably built within
roughly a decade, by 2020.
That
is much sooner than the conventional wisdom in the AI community. But there are
some very knowledgeable people who share my guess of approximately 2020. And
some of them have considerable resources to throw at the problem.
In
a Google Tech Talk, recorded in May 2006, Doug Lenat, mentioned in passing
that Sergey Brin, one of the two founders of Google,
had said AI could be built by 2020. Doug Lenat is
head of Cycorp, the corporate continuation of one of
the largest and longest big-AI projects. Lenat s talk
is at http://video.google.com/videoplay?docid=-7704388615049492068
. It provides a good overview of Cycorp s Cyc system, and has an amusing
introduction of Doug by Peter Norvig, co-author of
one of the leading textbooks on AI and Google s director of research.
In
response to Lenat s statement about Brin s projection, I did a brief web search to see if I
could find exactly what Brin had said about achieving
AI by 2020. I was unable to find any other reference to the quote. But I did
find the following information relevant to Google s pursuit of AI and to the
2020 estimate.
As
was cited on multiple web sites --- including http://www.naturalsearchblog.com/archives/2007/02/20/google-developing-artificial-intelligence-ai-brave-new-world
--- Google s Larry Page said at the 2007 conference for the American
Association for the Advancement of the Sciences, that
researchers at Google were working upon developing Artificial Intelligence. He
said human brain algorithms actually weren t all that complicated and could
likely be approximated with sufficient computational power. He said, We have
some people at Google (who) are really trying to build artificial intelligence
and to do it on a large scale. It s not as far off as people think.
According
to http://www.alexandriaarchive.org/blog/index.php?s=brin
: Sergey Brin is reported to have said that the
perfect search engine would look like the mind of God . Similar ideas, but
less extravagantly worded, have come from Marissa Mayer, Google s VP of Search
Products and User Experience when she talked about how Google s massive data
stores and sophisticated algorithms are acting more and more like
intelligence .
In
2008 Nicholas Carr --- who served as executive editor of the Harvard Business
Review, and who has written extensively on information technology --- wrote a
book entitled The Big Switch: Rewiring the World, From Edison to Google. A
review of it, at http://computersight.com/computers/the-big-switch-rewiring-the-world-from-edison-to-google-by-nicholas-carr/
, says:
the book discussed the future of computing. The main
discussion was with Google founders, Larry Page and Sergey Brin,
about their dream of what their search engine will do in the coming years.
According to Page and Brin, artificial intelligence
is the main goal of those behind the future of Google. Google wants to link the
human brain with the computer to share its search engine. The author also spoke
about advancements Microsoft and other Computer Scientists want for the future
of computing. According to Carr, in 2020, Google s dream may come true.
[AG]Looking further ahead at
Google's intentions, you write in The Big Switch that Google's ultimate plan is
to create artificial intelligence. How does this follow from what the company's
doing today?
[NC]
It's pretty clear from what [Google co-founders] Larry Page and Sergey Brin have said in interviews that Google sees search as
essentially a basic form of artificial intelligence. A year ago, Google
executives said the company had achieved just 5% of its complete vision of
search. That means, in order to provide the best possible results, Google's
search engine will eventually have to know what people are thinking, how to
interpret language, even the way users' brains operate.
Google
has lots of experts in artificial intelligence working on these problems,
largely from an academic perspective. But from a business perspective,
artificial intelligence's effects on search results or advertising would mean
huge amounts of money.
[AG] You've also suggested that
Google wants to physically integrate search with the human brain.
[NC]This
may sound like science fiction, but if you take Google's founders at their
word, this is one of their ultimate goals. The idea is that you no longer have
to sit down at a keyboard to locate information. It becomes automatic, a sort
of machine-mind meld. Larry Page has discussed a scenario where you merely
think of a question, and Google whispers the answer into your ear through your cellphone.
[AG] What would an ultra-intelligent
Google of the future look like?
[NC]I
think it's pretty clear that Google believes that there will eventually be an intelligence greater than what we think of today as human
intelligence. Whether that comes out of all the
world's computers networked together, or whether it comes from computers
integrated with our brains, I don't know, and I'm not sure that Google knows.
But the top executives at Google say that the company's goal is to pioneer that
new form of intelligence. And the more closely that they can replicate or even
expand how peoples' mind works, the more money they make.
[AG] You don't seem very optimistic
about a future where Google is smarter than humans.
[NC]I
think if Google's users were aware of that intention, they might be less
enthusiastic about the prospect than the mathematicians and computer scientists
at Google seem to be. A lot of people are worried that a superior intelligence
would mean for human beings.
I'm
not talking about Google robots walking around and pushing humans into lines.
But Google seems intent on creating a machine that's able to do a lot of our
thinking for us. When we begin to rely on a machine for memory and decision
making, you have to wonder what happens to our free will.
By
2012, he wants Google to be able to tell all of us what we want. This
technology, what Google co-founder Larry Page calls the "perfect search
engine," might not only replace our shrinks but also all those marketing
professionals whose livelihoods are based on predicting or guessing
consumer desires.
The
article also says
iGoogle is growing into a tightly-knit suite of services
personalized homepage, search engine, blog, e-mail
system, mini-program gadgets, Web-browsing history, etc. that together will
create the world's most intimate information database. On iGoogle,
we all get to aggregate our lives, consciously or not, so artificially
intelligent software can sort out our desires. It will piece together our
recent blog posts, where we've been online, our
e-commerce history and cultural interests. It will amass so much information
about each of us that eventually it will be able to logically determine what we
want to do tomorrow and what job we want.
We
will probably make conscious machines sometime between 2015 and 2020, I think.
But it probably won't be like you and I. It will be conscious and aware of
itself and it will be conscious in pretty much the same way as you and I, but
it will work in a very different way. It will be an alien. It will be a
different way of thinking from us, but nonetheless still thinking
In
response to the interviewer pointing out that
as
soon as machines become intelligent, according to
Moore's Law they will soon surpass
humans. By the way, BT's 2006 technology timeline predicts that AI entities
will be awarded with Nobel prizes by 2020, and soon after robots will become
mentally superior to humans. What comes after that: the super intelligence or
God 2.0?
Peterson
responds
I
think that I would certainly still go along with those time frames for
superhuman intelligence, but I won't comment on God 2.0. I think that we still
should expect a conscious computer smarter than people by 2020. I still see no
reason why that it is not going to happen in that time frame. But I don't think
we will understand it. The reason is because we don't even understand how some
of the principal functions of consciousness should work.
Of
course, Microsoft Research is also putting a lot of effort into artificial
intelligence research. A March 2, 2009 New York Times article at http://www.nytimes.com/2009/03/02/technology/business-computing/02compute.html
, reports on some of Microsoft s efforts in the field. Among other interesting
things it says:
CraigMundie, the chief research and strategy officer at
Microsoft, expects to see computing systems that are about 50 to 100 times more
powerful than today s systems by 2013.
Most
important, the new chips will consume about the same power as current chips,
making possible things like a virtual assistant with voice- and
facial-recognition skills that are embedded into an office door.
We
think that in five years time, people will be able to use computers to do
things that today are just not accessible to them, Mr. Mundie
said during a speech last week. You might find essentially a medical doctor in
a box, so to speak, in the form of your computer that could help you with
basic, nonacute care, medical problems that today you
can get no medical support for.
With
such technology in hand, Microsoft predicts a future filled with a vast array
of devices much better equipped to deal with speech, artificial intelligence
and the processing of huge databases.
So,
in sum, there is good reason to believe there will be an explosion in AI in the
next ten years.
DARPA'S DEEP
LEARNING PROGRAM COULD ADVANCE AGI.
========================================
Below
is a link to a DARPA request for a proposal for a
program to perform deep learning. It wants a system that can automatically
learn patterns of many different types from visual, auditory, and text with
little human guidance, using automatically learned hierarchical invariant
representations, of the general type described in the first few paragraphs of
"THE SOFTWARE" section of the above
post.
This
is the type of project, which if the right people got the funding could really
help advance AGI. It seems like Numenta,Poggio's group, or Hinton, could all submit
compelling responses to this proposal. The request says it is interested in
sponsoring multiple teams, and in disseminating much of what is learned to the
public to advance the computing arts.
DARPA S MIND S EYE
PROJECT LIKELY TO ADVANCE AI
========================================
TheDARPA Mind s Eye program is another example of an
ambitious AI program that is likely to get us closer to human-level AI. This
program will be run out of DARPA's TCTO or Transformational Convergence Technology Officee.
The
Mind s Eye program --- to reach its goals --- has to be able to:
-have
a fairly large invariant ontology of objects, motions, humans, weapons,
military behaviors, scenes, and scenarios it recognizes in many different instantiations,
forms, views, scale, and lighting;
-do
visual scene recognition and understanding;
-understand
behaviors of entities it is seeing;
-map
such understandings into a larger higher level representation and understanding
of what is taking place around it;
-presumably
have to combine audio and visual recognition, since sound is an important
source of information in a battlefield;
-have
to have complex goal pursuit and attention focusing, to decide what to look at,
and track, and spend its optical and computational resources on; and
-have
natural language communication capabilities, or some other method of creating
concise reports for human consumption and for receiving commands from humans
In
sum, this project would require quite an advanced set of AI capabilities to
function well.
The
Mind s Eye program seeks to develop in machines a capability that currently
exists only in animals: visual intelligence. Humans in particular perform a
wide range of visual tasks with ease, which no current artificial intelligence
can do in a robust way. Humans have inherently strong spatial judgment and are
able to learn new spatiotemporal concepts directly from the visual experience.
Humans can visualize scenes and objects, as well as the actions involving those
objects. Humans possess a powerful ability to manipulate those imagined scenes
mentally to solve problems. A machine‐based implementation of such
abilities would be broadly applicable to a wide range of applications.
This
program pursues the capability to learn generally applicable and generative
representations of action between objects in a scene directly from visual
inputs, and then reason over those learned representations. A key distinction
between this research and the state of the art in machine vision is that the
latter has made continual progress in recognizing a wide range of objects and
their properties what might be thought of as the nouns in the description of a
scene. The focus of Mind s Eye is to add the perceptual and cognitive
underpinnings for recognizing and reasoning about the verbs in those scenes,
enabling a more complete narrative of action in the visual experience.
One
of the desired military capabilities resulting from this new form of visual
intelligence is a smart camera, with sufficient visual intelligence that it can
report on activity in an area of observation. A camera with this kind of visual
intelligence could be employed as a payload on a broad range of persistent
stare surveillance platforms, from fixed surveillance systems, which would
conceivably benefit from abundant computing power, to camera‐equipped
perch‐and‐stare micro air vehicles, which would impose extreme
limitations on payload size and available computing power. For the purpose of
this research, employment of this capability on man‐portable unmanned
ground vehicles (UGVs) is assumed. This provides a
reasonable yet challenging set of development constraints, along with the
potential to transition the technology to an objective ground force capability.
Mind s
Eye strongly emphasizes fundamental research. It is expected that technology
development teams will draw equally from the state of the art in cognitive
systems, machine vision, and related fields to develop this new visual
intelligence. To guide this transformative research toward operational
benefits, the program will also feature flexible and opportunistic systems
integration. This integration will leverage proven visual intelligence software
to develop prototype smart cameras. Integrators will contribute an economical
level of effort during the technology development phase, supporting
participation in phase I program events (PI meetings, demonstrations, and
evaluations) as well as development of detailed systems integration concepts
that will be considered by DARPA at appropriate times
for increased effort in phase II systems integration.
DARPA IPTO PROJECTS LIKELY TO ADVANCE AGI
========================================
Here
is a summary of projects of DARPA s IPTO (Information Processing Technique Office) taken from
its web site. It shows this office within DARPA is
funding a lot of projects that are likely to speed the advance of AI. I have
capitalized the portions of text that seem most relevant to the development of
AI. (Apologies to those who view all caps as screaming.
In the limited word processor offered in this forum, it seems the most
efficient way to let one scan highlighted text.). Particularly if it is
combined with the type of deep learning DARPA is
proposing, described in one of my posts above, or if it combined with DARPA s neuromorphic computing
project
========================================
COGNITIVE
COMPUTING IS THE DEVELOPMENT OF COMPUTER TECHNIQUES TO EMULATE HUMAN
PERCEPTION, INTELLIGENCE AND PROBLEM SOLVING. Cognitive systems offer some
important advantages over conventional computing approaches. For example,
COGNITIVE SYSTEMS CAN LEARN FROM EVENTS THAT OCCUR IN THE REAL WORLD and so are
better suited to applications that require EXTRACTING AND ORGANIZING
INFORMATION IN COMPLEX UNSTRUCTURED SCENARIOS than conventional computing
systems, which must have the right models built in a priori in order to be
effective. Because many of challenges faced by military commanders involve vast
amounts of data from sensors, databases, the Web and human sources, IPTO is creating cognitive systems that CAN LEARN AND
REASON TO STRUCTURE MASSIVE AMOUNTS OF RAW DATA INTO USEFUL, ORGANIZED
KNOWLEDGE WITH A MINIMUM OF HUMAN ASSISTANCE. IPTO is
implementing cognitive technology in systems that support warfighters
in the decision-making, management, and understanding of complexity in
traditional and emergent military missions. These cognitive
systems WILL UNDERSTAND WHAT THE USER IS REALLY TRYING TO DO AND PROVIDE
PROACTIVE INTELLIGENCE, ASSISTANCE AND ADVICE. Finally, the increasing
complexity, rigidity, fragility and vulnerability of modern information
technology has led to ever-growing manpower requirements for IT support. The incorporation of COGNITIVE CAPABILITIES IN INFORMATION SYSTEMS
WILL ENABLE THEM TO SELF-MONITOR, SELF-CORRECT, AND SELF-DEFEND AS THEY
EXPERIENCE SOFTWARE CODING ERRORS, HARDWARE FAULTS AND CYBER-ATTACK.
Programs
Advanced
Soldier Sensor Information System and Technology (ASSIST)
----------------------------------------------------------------------
The
main goal of the program is to enhance battlefield awareness via exploitation
of soldier-collected information. The program will demonstrate advanced
technologies and an integrated system for processing, digitizing and
disseminating key data and knowledge captured by and for small squad leaders.
Bootstrapped
Learning (BL)
----------------------------------------------------------------------
THE
BOOTSTRAPPED LEARNING PROGRAM SEEKS TO MAKE INSTRUCTABLE
COMPUTING A REALITY. THE "ELECTRONIC STUDENT" WILL LEARN FROM A HUMAN
TEACHER WHO USES SPOKEN LANGUAGE, GESTURES, DEMONSTRATION, AND MANY OTHER
METHODS ONE WOULD FIND IN A HUMAN MENTORED RELATIONSHIP. FURTHERMORE, IT WILL
BUILD UPON LEARNED CONCEPTS AND APPLY THAT KNOWLEDGE ACROSS DIFFERENT FIELDS OF
STUDY.
EMBEDDING
BL TECHNOLOGY IN COMPUTING SYSTEMS WILL ELIMINATE THE NEED FOR TRAINED
PROGRAMMERS IN MANY PRACTICAL SETTINGS, significantly accelerating
human-machine instruction, and making possible on-the-fly upgrades by domain
experts rather than computer experts. Target applications include a variety of
field-trainable military systems, such as human-instructable
unmanned aerial vehicles. However, BL technology is being developed and tested
against a portfolio of training tasks across very diverse domains, thus it can
be applied to any programmable, automated system. As such systems have become
ubiquitous, and their operation inaccessible to the layperson, there is also
the strong prospect of societal adoption and benefit.
Brood
of Spectrum Supremacy (BOSS)
----------------------------------------------------------------------
The
goal of the Brood of Spectrum Supremacy (BOSS) program is to provide a radio
frequency (RF) spectrum analogue to night vision
capabilities for the tactical warfighter, with a
particular focus on RF-rich urban operations. The
program is intended to apply collaborative processing capabilities for
software-defined radios to specific military applications.
Cyber
Trust (CT)
----------------------------------------------------------------------
The
Cyber Trust program will create the technology and techniques to enable
trustworthy information systems by:
1.
Developing hardware, firmware, and microkernel architectures as necessary to
provide foundational security for operating systems and applications.
2.
Developing tools to find vulnerabilities in complex open source software.
3.
Developing scalable formal methods to formally verify complex hardware/software.
Integrated
Learning (IL)
----------------------------------------------------------------------
The
Integrated Learning program SEEKS TO ACHIEVE REVOLUTIONARY ADVANCES IN MACHINE
LEARNING BY CREATING SYSTEMS THAT OPPORTUNISTICALLY ASSEMBLE KNOWLEDGE FROM
MANY DIFFERENT SOURCES IN ORDER TO LEARN. THE GOAL IS TO MOVE BEYOND THE
CURRENT STATISTICALLY-ORIENTED PARADIGMS VIA THE INTEGRATION OF EXISTING
LEARNING, REASONING, AND KNOWLEDGE REPRESENTATION TECHNOLOGIES INTO A COHERENT
ARTIFACT THAT WILL BE ABLE TO LEARN MUCH MORE QUICKLY AND ROBUSTLY IN A WIDER
RANGE OF APPLICATIONS. The program is FOCUSED UPON LEARNING MODELS OF ACTION
FROM VERY SPARSE DATA, which will provide the ability to develop more effective
military decision/planning support systems at lower costs. Target applications
include military airspace management and medical logistics.
LANdroids
----------------------------------------------------------------------
Communications
are essential to warfighters - they enable warfighters to share situational awareness and to stay
coordinated with each other and command. Communications are important for voice
and data and the importance for data traffic will only increase in the future.
The problem is that urban settings hinder communications. Buildings, walls,
vehicles, etc., create obstacles that impact the manner in which radio signals
propagate. The net result is unreliable communications in these settings, which
can leave warfighters, sensors, etc., without the
benefit of reach back to command or each other.
This
program will help to solve the urban communications problem by CREATING
INTELLIGENT AUTONOMOUS ROBOTIC RADIO RELAY NODES, CALLED LANDROIDS
(LOCAL AREA NETWORK DROIDS), WHICH WORK TO ESTABLISH AND MAINTAIN MESH NETWORKS
THAT SUPPORT VOICE AND DATA TRAFFIC. Through autonomous movement and
intelligent control algorithms, LANdroids can
mitigate many of the communications problems present in urban settings, e.g.,
relaying signals into shadows and making small adjustments to reduce multi-path
effects.
LANdroids will be pocket-sized and inexpensive. The concept of
operations is that warfighters will carry several LANdroids, which they drop as needed during deployment. TheLANdroids then form the mesh network and work to
maintain it - establishing a communications infrastructure that supports the warfighters in that region.
Machine
Reading (MR)
----------------------------------------------------------------------
The
Machine Reading Program WILL BUILD A UNIVERSAL TEXT ENGINE THAT CAPTURES
KNOWLEDGE FROM NATURALLY OCCURRING TEXT AND TRANSFORMS IT INTO THE FORMAL
REPRESENTATIONS USED BY ARTIFICIAL INTELLIGENCE (AI) REASONING SYSTEMS. The
Machine Reading Program will create an automated reading system that SERVES AS
A BRIDGE BETWEEN KNOWLEDGE CONTAINED IN NATURAL TEXTS AND THE FORMAL REASONING
SYSTEMS THAT NEED SUCH KNOWLEDGE.
Personalized
Assistant that Learns (PAL)
----------------------------------------------------------------------
The
mission of the PAL program is TO RADICALLY IMPROVE THE WAY COMPUTERS SUPPORT
HUMANS BY ENABLING SYSTEMS THAT ARE COGNITIVE, I.E., COMPUTER SYSTEMS THAT CAN
REASON, LEARN FROM EXPERIENCE, BE TOLD WHAT TO DO, EXPLAIN WHAT THEY ARE DOING,
REFLECT ON THEIR EXPERIENCE, AND RESPOND ROBUSTLY TO SURPRISE. MORE SPECIFICALLY,
PAL WILL DEVELOP A SERIES OF PROTOTYPE COGNITIVE SYSTEMS THAT CAN ACT AS AN
ASSISTANT FOR COMMANDERS AND STAFF. Successful completion of this program will
usher in a new era of computational support for a broad range of human
activity.
Current
software systems - in the military and elsewhere - are plagued by brittleness
and the inability to deal with changing and novel situations - and must
therefore be painstakingly programmed for every contingency. If PAL succeeds it
could result in software systems that could learn on their own - that could
adapt to changing situations without the need for constant reprogramming. PAL
technology could drastically reduce the money spend by DoD on information systems of all kinds.
This
is the FIRST BROAD-BASED RESEARCH PROGRAM IN COGNITIVE SYSTEMS SINCE THE
STRATEGIC COMPUTING INITIATIVE FUNDED BY DARPA IN THE
1980S. Since then, there have been significant developments in the technologies
needed to enable cognitive systems, such as machine learning, reasoning, perception,
and, multi-modal interaction. Improvements in processors, memory, sensors and
networking have also dramatically changed the context of cognitive systems
research. It is now time to encourage the various areas to come together again
by focusing on by a common application problem: a Personalized Assistant that
Learns.
Developing
cognitive systems that learn to adapt to their user could dramatically improve
a wide range of military operations. The development and application of
intelligent systems to support military decision-making may provide dramatic
advances for traditional military roles and missions. The technologies
developed under the PAL program are intended to make military decision-making
more efficient and more effective at all levels.
For
example, today's command centers require hundreds of staff members to support a
relatively small number of key decision-makers. If PAL succeeds, and develops a
new capability for "cognitive assistants," those assistants could
eliminate the need for large command staffs - enabling smaller, more mobile,
less vulnerable command centers.
Self-Regenerative
Systems (SRS)
----------------------------------------------------------------------
The
goal of the SRS program is to develop technology for building military
computing systems that provide critical functionality at all times, in spite of
damage caused by unintentional errors or attacks. All current systems suffer
eventual failure due to the accumulated effects of errors or attacks. The SRS
program aims to develop technologies enabling military systems to learn,
regenerate themselves, and automatically improve their ability to deliver
critical services. If successful, self-regenerative systems will show a
positive trend in reliability, actually exceeding initial operating capability
and approaching a theoretical optimal performance level over long time
intervals.
Situation
Aware Protocols in Edge Network Technologies (SAPIENT)
----------------------------------------------------------------------
The
mission of the Situation Aware Protocols in Edge Network Technologies (SAPIENT)
program is to create a new generation of adaptive communication systems that
achieve new levels of functionality through situation-awareness.
Transfer
Learning (TL)
----------------------------------------------------------------------
The
TRANSFER LEARNING PROGRAM SEEKS TO SOLVE THE PROBLEM OF REUSING KNOWLEDGE
DERIVED IN ONE DOMAIN TO HELP EFFECT SOLUTIONS IN ANOTHER DOMAIN. Adaptive
systems, systems that respond to changes in their environment, stand to benefit
significantly from the application of TL technology. Today's adaptive systems
need to be trained for every new situation they encounter. This requires
building new training data, which is the most expensive and most limiting
aspect of deploying such systems. The TL PROGRAM ADDRESSES THIS SHORTCOMING BY
IMBUING ADAPTIVE SYSTEMS WITH THE ABILITY TO ENCAPSULATE WHAT THEY HAVE LEARNED
AND APPLY THIS KNOWLEDGE TO NEW SITUATIONS. Thus, rather than having to be
retrained for each new context, TL enables systems to leverage what they have
already learned in order to be effective much sooner and with less effort spent
on training. Early applications of TL technology include adaptive ISR systems, robotic vision and manipulation, and automated
population of databases from unstructured text.
========================================
Command
and control is the exercise of authority and direction by a properly designated
commander over assigned and attached forces in the accomplishment of a mission.
Without question the missions faced by our warfighters
today (such as counter-insurgency) and the operational environments (such as
cities) are more complex and dangerous than ever before. While following their
rules of engagement, warfighters must make rapid
decisions based on limited observables interpreted in the context of the
evolving situation. Command and control systems must augment the observables
within constrained timelines and present actionable results to the warfighter. IPTO ENABLES WARFIGTER SUCCESS BY CREATING TECHNOLOGIES AND SYSTEMS THAT
PROVIDE TAILORED, CONSISTENT, PREDICTIVE SITUATION AWARENESS ACROSS ALL COMMAND
ELEMENTS, AND CONTINUOUS SYNCHRONIZATION OF SENSING, STRIKE, COMMUNICATIONS,
AND LOGISTICS TO MAXIMIZE THE EFFECTIVENESS OF MILITARY OPERATIONS WHILE
MINIMIZING UNDESIRABLE SIDE EFFECTS. In counter-insurgency operations, targets
of interest are often not known until a significant event (e.g. detonation of IED) occurs. In those instances, reliably and quickly
determining the origin of the devices/vehicles becomes the key to preventing
subsequent attacks. IPTO is creating systems that
collect wide area observables in the absence of any strong a priori cues,
analyze the prior time history of events and track insurgent activities to
their point of origin.
Programs
Conflict
Modeling, Planning, and Outcomes Experimentation (COMPOEX)
----------------------------------------------------------------------
DARPA's Conflict Modeling, Planning, and Outcomes Experimentation (COMPOEX) program is developing a suite of tools that will
help military commanders and their civilian counterparts to plan, analyze and
conduct complex campaigns. "Complex" here refers to those operations
- often of long duration and large scale - that require careful consideration
of not only traditional military, but also political, social, economic actions
and ramifications.
Deep
Green (DG)
----------------------------------------------------------------------
The
Deep Green concept is an innovative approach to using simulation to support
ongoing military operations while they are being conducted. The basic approach
is to MAINTAIN A STATE-SPACE GRAPH OF POSSIBLE FUTURE
STATES. SOFTWARE AGENTS USE INFORMATION ON THE TRAJECTORY OF THE ONGOING
OPERATION, VICE A PRIORI STAFF ESTIMATES AS TO HOW THE
BATTLE MIGHT UNFOLD, AS WELL AS SIMULATION
TECHNOLOGIES, TO ASSESS THE LIKELIHOOD OF REACHING SOME SET OF POSSIBLE FUTURE
STATES. THE LIKELIHOOD, UTILITY, AND FLEXIBILITY OF POSSIBLE FUTURE NODES IN
THE STATE SPACE GRAPH ARE COMPUTED AND EVALUATED TO FOCUS THE PLANNING EFFORTS.
This notion is called anticipatory planning and involves the generation of
options (either manual or semi-automated) ahead of "real time,"
before the options are needed. In addition, the Deep Green concept provides
mechanisms for adaptive execution, which can be described as "late binding,"
or choosing a branch in the state space graph at the last moment to maintain
flexibility. By using information acquired from the ongoing operation, rather
than assumptions made during the planning phase, commanders and staffs can make
more informed choices and focus on building options for futures that are
becoming more likely.
Heterogeneous
Airborne Reconnaissance Team (HART)
----------------------------------------------------------------------
The
complexity of counter-insurgency operations especially in the urban combat
environment demands multiple sensing modes for agility and for persistent,
ubiquitous coverage. The HART system implements collaborative control of
reconnaissance, surveillance and target acquisition (RSTA)
assets, so that the information can be made available to warfighters
at every echelon.
Persistent
Operational Surface Surveillance and Engagement (POSSE)
----------------------------------------------------------------------
The
POSSE program is building a REAL-TIME, ALL-SOURCE EXPLOITATION SYSTEM TO
PROVIDE INDICATIONS AND WARNINGS OF INSURGENT ACTIVITY DERIVED FROM AIRBORNE
AND GROUND-BASED SENSORS. Envisioning a day when our sensors can be integrated
into a cohesive "ISR Force", it's building
AN INTEGRATED SUITE OF SIGNAL PROCESSING, PATTERN ANALYSIS, AND
COLLECTION MANAGEMENT SOFTWARE that will increase reliability, reduce manpower,
and speed up responses.
Predictive
Analysis for Naval Deployment Activities (PANDA)
----------------------------------------------------------------------
The
current CONOPS for achieving situation awareness in
the maritime domain calls for close monitoring of those entities that we
already have reason to be concerned about (i.e., we already suspect are threats
or which carry cargos that could be dangerous in the hands of the wrong
people). PANDA will ADVANCE TECHNOLOGIES AND DEVELOP AN ARCHITECTURE THAT WILL
ALERT WATCHSTANDERS TO ANOMALOUS SHIP behavior AS IT
OCCURS, allowing them to detect potentially dangerous behavior before it causes
harm. These technologies and systems will be transitioned to various partners
and customers throughout the development process, ensuring that the end product
meets the needs of the services and watchstanders.
Participants will work closely with the transition partners to aid in this process.
Urban
Leader Tactical Response, Awareness & Visualization (ULTRA-Vis)
----------------------------------------------------------------------
Current
military operations are focusing efforts on urban and asymmetric warfare, as
well as distributed operations, but small unit leaders lack the capability to
issue commands and share mission-relevant information in an urban environment
non-line-of-sight. Various factors that can impact mission effectiveness and
tempo of operations are:
1.
Leaders communicate by shouting and hand signals;
2.
Teams operate within earshot and line-of-sight;
3.
Intra-squad radios are hard to hear; and
4.
Leaders must stop to use handheld displays.
Military
operations in the urban terrain (extensive areas with hostile forces,
non-combatant populations, and complex infrastructure) require special
capabilities and agility to conduct close-combat operations under highly
dynamic, adverse conditions. In short, tactical leaders need the ability to
adapt on the move, coordinate small unit actions and execute commands across a
wider area of engagement. SIGNIFICANT TACTICAL ADVANTAGES COULD BE REALIZED
THROUGH THE SMALL UNIT LEADER'S ABILITY TO INTUITIVELY GENERATE/ROUTE COMMANDS
AND TIMELY ACTIONABLE COMBAT INFORMATION TO THE APPROPRIATE TEAM OR INDIVIDUAL WARFIGHTER IN A READILY UNDERSTOOD FORMAT THAT AVOIDS
INFORMATION OVERLOAD.
========================================
IPTO is DEVELOPING THE HIGH-PRODUCTIVITY, HIGH-PERFORMANCE COMPUTER HARDWARE
AND THE ASSOCIATED SOFTWARE TECHNOLOGY BASE REQUIRED TO SUPPORT FUTURE CRITICAL
NATIONAL SECURITY NEEDS FOR COMPUTATIONALLY-INTENSIVE AND DATA-INTENSIVE
APPLICATIONS. THESE TECHNOLOGIES WILL LEAD TO NEW MULTI-GENERATION PRODUCT
LINES OF COMMERCIALLY VIABLE, SUSTAINABLE COMPUTING SYSTEMS FOR A BROAD
SPECTRUM OF SCIENTIFIC AND ENGINEERING APPLICATIONS, including both
supercomputer and embedded computing. The goal is to ensure accessibility and
usability of high end computing to a wide range of application developers, not
just computational science experts. This is ESSENTIAL FOR MAINTAINING THE
NATION'S STRENGTH IN SUPERCOMPUTING BOTH FOR ULTRA LARGE-SCALE ENGINEERING
APPLICATIONS AND FOR SURVEILLANCE AND RECONNAISSANCE DATA ASSIMILATION AND
EXPLOITATION. ONE OF THE MAJOR CHALLENGES CURRENTLY FACING THE DOD IS THE
PROHIBITIVELY HIGH COST, TIME, AND EXPERTISE REQUIRED TO
BUILD LARGE COMPLEX SOFTWARE SYSTEMS. POWERFUL NEW APPROACHES AND TOOLS
ARE NEEDED TO ENABLE THE RAPID AND EFFICIENT PRODUCTION OF NEW SOFTWARE,
INCLUDING SOFTWARE THAT CAN BE EASILY CHANGED TO ADDRESS NEW REQUIREMENTS AND
TO PLATFORM AND ENVIRONMENTAL PERTURBATIONS. Computing capabilities must
progress dramatically if
U.S. forces are to exploit an
ever-increasing diversity, quantity, and complexity of sensor and other types
of data. Doing so both in command centers and on the
battlefield will require significantly increasing performance and significantly
decreasing power and size requirements.
Programs
[there was currently no available description for these programs]
Architecture-Aware
Compiler Environment (AACE)
----------------------------------------------------------------------
Disruptive
Manufacturing Technology, Software Producibility (DMT-SWP)
----------------------------------------------------------------------
.
High
Productivity Computing Systems (HPCS)
----------------------------------------------------------------------
========================================
At
present, the exploitation of foreign language speech and text is slow and labor
intensive and as a result, the availability, quantity and timeliness of
information from foreign-language sources is limited. IPTO is creating NEW TECHNOLOGIES AND SYSTEMS FOR
AUTOMATING THE TRANSCRIPTION AND TRANSLATION OF FOREIGN LANGUAGES. These
language processing capabilities will enable our military to exploit large
volumes of speech and text in multiple languages, thereby increasing
situational awareness at all levels of command. In particular, IPTO is AUTOMATING THE CAPABILITY TO MONITOR FOREIGN
LANGUAGE MEDIA AND TO EXPLOIT FOREIGN LANGUAGE NEWS BROADCASTS with one-way
(foreign-language-to-English) translation technologies. IPTO
is also DEVELOPING HAND-HELD, TWO-WAY (FOREIGN-LANGUAGE-TO-ENGLISH AND
ENGLISH-TO-FOREIGN-LANGUAGE) SPEECH-TO-SPEECH TRANSLATION SYSTEMS that enable
the warfighter on the ground to communicate directly
with local populations in their native language. Finally, IPTO
is creating TECHNOLOGIES TO EXPLOIT THE INFORMATION CONTAINED IN HARD-COPY
DOCUMENTS AND DOCUMENT IMAGES RESIDENT ON MAGNETIC AND OPTICAL MEDIA CAPTURED
IN THE FIELd. Making full use of all of the
information extracted from foreign-language sources REQUIRES THE CAPABILITY TO
AUTOMATICALLY COLLATE, FILTER, SYNTHESIZE, SUMMARIZE, AND PRESENT RELEVANT
INFORMATION IN TIMELY AND RELEVANT FORMS. IPTO is
DEVELOPING NATURAL LANGUAGE PROCESSING SYSTEMS TO ENHANCE LOCAL, REGIONAL AND
GLOBAL SITUATIONAL AWARENESS AND ELIMINATE THE NEED FOR TRANSLATORS AND SUBJECT
MATTER EXPERTS AT EVERY MILITARY SITE WHERE FOREIGN-LANGUAGE INFORMATION IS
OBTAINED.
Programs
Global
Autonomous Language Exploitation (GALE)
----------------------------------------------------------------------
The
goal of the GALE (Global Autonomous Language Exploitation) program is to DEVELOP
AND APPLY COMPUTER SOFTWARE TECHNOLOGIES TO ABSORB, TRANSLATE, ANALYZE, AND
INTERPRET HUGE VOLUMES OF SPEECH AND TEXT IN MULTIPLE LANGUAGES, eliminating
the need for linguists and analysts, and automatically providing relevant,
concise, actionable information to military command and personnel in a timely
fashion. Automatic processing "engines" will convert and distill the
data, delivering pertinent, consolidated information in easy-to-understand
forms to military personnel and monolingual English-speaking analysts in
response to direct or implicit requests.
Multilingual
Automatic Document Classification Analysis and Translation (MADCAT)
----------------------------------------------------------------------
The
United States has a compelling need for reliable
information affecting military command, soldiers in the field, and national
security. Currently, our warfighters encounter
foreign language images in many forms, including, but not limited to graffiti,
road signs, printed media, and captured records in the form of paper and
computer files. Given the quantity of foreign language material, it is
difficult to interpret the salient pieces of information, much of which is
either ignored or analyzed too late to be of any use. The mission of the
Multilingual Automatic Document Classification Analysis and Translation (MADCAT) Program is to AUTOMATICALLY CONVERT FOREIGN
LANGUAGE TEXT IMAGES INTO ENGLISH TRANSCRIPTS, thus eliminating the need for
linguists and analysts while automatically providing relevant, distilled
actionable information to military command and personnel in a timely fashion.
Spoken
Language Communication and Translation System for Tactical Use (TRANSTAC)
----------------------------------------------------------------------
Today,
phrase-based translation devices are being tactically deployed. These one-way
devices translate English input into pre-recorded phrases in target languages.
While such systems are useful in many operational settings, the inability to
translate foreign speech into English is a significant limitation. The mission
of the Spoken Language Communication and Translation System for Tactical Use (TRANSTAC) program is to demonstrate capabilities to rapidly
develop and field TWO-WAY TRANSLATION SYSTEMS THAT ENABLE SPEAKERS OF DIFFERENT
LANGUAGES TO SPONTANEOUSLY COMMUNICATE WITH ONE ANOTHER IN REAL-WORLD TACTICAL
SITUATIONS.
========================================
U.S. forces and sensors are increasingly
networked across service, location, domain (land, sea and air), echelon, and
platform. This trend increases responsiveness, flexibility and combat
effectiveness, but also increases the inherent complexity of sensor and
information management. IPTO is CREATING SYSTEMS THAT
CAN DERIVE HIGH-LEVEL INFORMATION FROM SENSOR DATA STREAMS (FROM BOTH MANNED
AND UNMANNED SYSTEMS), PRODUCE MEANINGFUL SUMMARIES OF COMPLEX DYNAMIC
SITUATIONS, AND SCALE TO THOUSANDS OF SOURCES. Future battlefields will
continue to be populated with targets that use mobility and concealment as key
survival tactics, and high-value targets will range from quiet submarines, to
mobile missile/artillery, to specific individual insurgents. IPTO develops and demonstrates system CONCEPTS THAT COMBINE
NOVEL APPROACHES TO SENSING, SENSOR PROCESSING, SENSOR FUSION, AND INFORMATION
MANAGEMENT TO ENABLE PERVASIVE AND PERSISTENT SURVEILLANCE OF THE BATTLESPACE AND DETECTION, IDENTIFICATION, TRACKING,
ENGAGEMENT AND BATTLE DAMAGE ASSESSMENT FOR HIGH-VALUE TARGETS IN ALL WEATHER
CONDITIONS AND IN ALL POSSIBLE COMBAT ENVIRONMENTS. Finally, warfighters in the field must concentrate on observing
their immediate environment but at the same time must maintain awareness of the
larger battlespace picture, and as a result they are
susceptible to being swamped by too much detail. IPTO
is creating system approaches that can exploit context and advanced information
display/presentation techniques to overcome these challenges.
Programs
Autonomous
Real-time Ground Ubiquitous Surveillance - Imaging System (ARGUS-IS)
----------------------------------------------------------------------
The
mission of the Autonomous Real-time Ground Ubiquitous Surveillance - Imaging
System (ARGUS-IS) program is to provide military users a flexible and
responsive capability to find, track and monitor events and activities of
interest on a continuous basis in areas of interest.
The
overall objective is to increase situational awareness and understanding
enabling an ability to find and fix critical events in a large area in enough
time to influence events. ARGUS - IS provides military users an
"eyes-on" persistent wide area surveillance capability to support
tactical users in a dynamic battlespace or urban
environment.
FOPEN Reconnaissance, Surveillance, Tracking and Engagement Radar (FORESTER)
----------------------------------------------------------------------
The
Foliage Penetration Reconnaissance, Surveillance, Tracking and Engagement Radar
(FORESTER) is a joint DARPA/Army program to develop
and demonstrate an advanced airborne UHF radar capable of detecting people and
vehicles moving under foliage. FORESTER will provide robust, wide-area,
all-weather, persistent stand-off coverage of moving vehicles and dismounted
troops under foliage, filling the surveillance gap that currently exists.
Multispectral Adaptive Networked Tactical Imaging System (MANTIS)
----------------------------------------------------------------------
The
MANTIS program will develop, integrate and demonstrate A SOLDIER-WORN
VISUALIZATION SYSTEM, CONSISTING OF A HEAD-MOUNTED MULTISPECTRAL
SENSOR SUITE WITH A HIGH RESOLUTION DISPLAY AND A HIGH
PERFORMANCE VISION PROCESSOR (ASIC), CONNECTED TO A
SOLDIER-WORN POWER SUPPLY AND RADIO. The helmet-mounted MANTIS Vision Processor
will provide the soldier with digitally fused, multispectral
video imagery in real time from the Visible/Near Infrared (VNIR),
the Short Wave Infrared (SWIR) and the Long Wave
Infrared (LWIR) helmet-mounted sensors via the high
resolution visor display. The processor adaptively fuses the digital imagery
from the multispectral sensors providing the highest
context, best nighttime imagery in real-time under varying battlefield conditions.
The system also ALLOWS THE VIDEO IMAGERY TO BE RECORDED AND PLAYED BACK ON
DEMAND AND ALLOWS THE OVERLAY OF BATTLEFIELD INFORMATION. MANTIS will exploit
the existing soldier radio network and PROVIDE SOLDIER-TO-SOLDIER SHARING OF
VIDEO CLIPS VIEWED AS PICTURE-IN-PICTURE ON THEIR HELMET MOUNTED DISPLAYS. MANTIS WILL "regain the nighttime advantage" and
"EXPLOIT THE NET" TO PROVIDE THE INDIVIDUAL SOLDIER WITH
UNPRECEDENTED SITUATIONAL AWARENESS.
NetTrack (NT)
----------------------------------------------------------------------
PERSISTENT RECONNAISSANCE, SURVEILLANCE, TRACKING AND
TARGETING OF EVASIVE VEHICLES IN CLUTTERED ENVIRONMENTS.
Quint Networking Technology (QNT)
----------------------------------------------------------------------
In
a network centric battle space, U.S. Forces must exploit distributed sensor
platforms to rapidly and precisely find, fix, track, and engage static and
moving targets in real time. There are several relevant thrusts to time
critical targeting and strike areas within the Services. One aspect of these
thrusts is to use data links to fully integrate tactical UAVs,
dismounted ground forces and weapon control into the future network centric
warfare environment.
TheQuint Networking Technology (QNT)
is a modular network data link program focused on providing a multi-band
modular capability to close the seams between five nodes - Aircraft, UCAV, Weapons, tactical UAV and
dismounted ground forces. The specific intended QNT
hardware users are weapons, air control forces on the ground (dismounted) and
tactical UAV's. These three are the focal points of
the QNT effort with the other two elements using
hardware and waveforms from established programs. The assumption is these other
two types of platforms provide a starting point for building capability for the
other three elements.
Standoff
Precision ID in 3-D (SPI-3D)
----------------------------------------------------------------------
The
SPI-3D program will develop and demonstrate the ability to provide precision geolocation of ground targets combined with high-resolution
3D imagery at useful standoff ranges. These dual capabilities will be provided
using a sensor package composed of commercially available components. It will
be capable of providing "optical quality precision at radar standoff
ranges" and have the ability to overcome limited weapons effects
obscuration, and penetrate moderate foliage. The figure below shows the
operational concept of the SPI-3D system.
Urban
Reasoning and Geospatial Exploitation Technology (URGENT)
----------------------------------------------------------------------
The
recognition of targets in urban environments poses unique operational
challenges for the warfighter. Historically, target
recognition has focused on conventional military objects, with particular
emphasis on military vehicles such as tanks and armored personnel carriers. In
many cases, these threats exhibit unique signatures and are relatively
geographically isolated from densely populated areas. The same cannot be said of
today's asymmetric threats, which are embedded in urban areas, thereby forcing
U.S. Forces to engage enemy combatants in cities with large civilian
populations. Under these conditions, even the most common urban objects can
have tactical significance: trash cans can contain improvised explosive
devices, doors can conceal snipers, jersey barriers can block troop ingress, roof tops can become landing zones, and so on. Today's urban
missions involve analyzing a multitude of urban objects in the area of regard.
As military operations in urban regions have grown, the need to identify urban
objects has become an important requirement for the military. URGENT WILL
ENABLE UNDERSTANDING THE LOCATIONS, SHAPES, AND CLASSIFICATIONS OF OBJECTS FOR
A BROAD RANGE OF PRESSING URBAN MISSION PLANNING ANALYTICAL QUERIES (E.G.,
FINDING ALL ROOF TOP LANDING ZONES ON THREE STORY BUILDINGS CLEAR OF VERTICAL
OBSTRUCTIONS AND VERIFYING INGRESS ROUTES WITH MAXIMUM COVER FOR GROUND
TROOPS). IN ADDITION, URGENT WILL ENABLE AUTOMATED TIME-SENSITIVE SITUATION
ANALYSIS (E.G., ALERTING FOR VEHICLES FOUND ON A ROAD SHOULDER AFTER DARK AND
ESTIMATING DAMAGE TO A BUILDING EXTERIOR AFTER AN EXPLOSION) THAT WILL MAKE A
SIGNIFICANT POSITIVE IMPACT ON URBAN OPERATIONS.
Vehicle
and Dismount Exploitation Radar (VADER)
----------------------------------------------------------------------
VADER
is a RADAR SYSTEM DESIGNED TO ENABLE THE SURVEILLANCE AND TRACKING OF GROUND
VEHICLES AND DISMOUNTS from a Warrior (or similar) unmanned aerial vehicle (UAV) platform. VADER will PROVIDE REAL-TIME DATA PRODUCTS
TO A COMMAND ECHELONS AT WHICH THE REAL-TIME INFORMATION WILL BE IMMEDIATELY
ACTIONABLE. For example, a warfighter could use the
Warrior UAV with VADER installed to monitor a road,
track a vehicle to a stop, OBSERVE DISMOUNT MOTION NEAR THE VEHICLE,
CHARACTERIZE CERTAIN MOTIONS (LIKE SOMEONE CARRYING A HEAVY LOAD), AND MEASURE
A GROUND DISTURBANCE AFTER THE VEHICLE DEPARTS.
Video
and Image Retrieval and Analysis Tool (VIRAT)
----------------------------------------------------------------------
The
overall goal of the Video and Image Retrieval and Analysis Tool (VIRAT) program is to produce A SCALABLE AND EXTENSIBLE
END-TO-END SYSTEM THAT ENABLES MILITARY ANALYSTS TO OBTAIN GREATER VALUE FROM
AERIAL VIDEO COLLECTED IN COMBAT ENVIRONMENTS.
========================================
IPTO is EXPLORING SEVERAL EMERGING INFORMATION PROCESSING TECHNOLOGIES
INCLUDING NOVEL USES OF MODELING AND SIMULATION TO CREATE NEW BATTLE COMMAND
PARADIGMS; REVOLUTIONARY APPROACHES TO POWER, SIZE AND PROGRAMMABILITY AS
ENABLERS FOR COMPUTING AT THE EXASCALE; COMPUTATIONAL
SOCIAL SCIENCE AS THE FOUNDATION FOR BETTER UNDERSTANDING OF THE WORLD FACED BY
THE WARFIGHTER; ADVANCED SENSING ARCHITECTURES
INCLUDING NEW SENSING MODALITIES TO COUNTER DIFFICULT THREATS; AUTOMATED
STORAGE, INDEXING, ANALYSIS, CORRELATION, SEARCH, AND RETRIEVAL OF MULTIMEDIA
DATA; AND TECHNIQUES TO ENABLE INFORMATION SHARING ACROSS ORGANIZATIONAL
BOUNDARIES AND ADMINISTRATIVE/SECURITY DOMAINS.
Programs
Advanced
Speech Encoding (ASE)
----------------------------------------------------------------------
Speech
is the most natural form of human-to-human communications. However, THE
MILITARY IS OFTEN FORCED TO OPERATE IN ENVIRONMENTS WHERE SPEECH IS DIFFICULT.
For example, the quality and intelligibility of the acoustic signal can be
severely degraded by HARSH ACOUSTIC NOISE BACKGROUNDS that are common in
military environments. In addition, many situations also require war fighters
to operate in silence and in a stealth mode so that their presence and intent
are not compromised. THE ADVANCED SPEECH ENCODING (ASE) PROGRAM WILL DEVELOP
TECHNOLOGY THAT WILL ENABLE COMMUNICATION IN THESE CHALLENGING MILITARY
ENVIRONMENTS.
Information
Theory for
Mobile Ad-Hoc Networks (ITMANET)
----------------------------------------------------------------------
The
mission of the Information Theory for Mobile Ad-Hoc Networks (ITMANET) program is TO DEVELOP AND EXPLOIT MORE POWERFUL
INFORMATION THEORY CONCERNING MOBILE WIRELESS NETWORKS. The hypothesis of this
program is that a specific challenge problem --- better understanding of MANET capacity limits --- will lead to actionable
implications for network design and deployment. The anticipated byproducts of a
more evolved theory include new separation theorems to inform wireless network
"layering" as well as new protocol ideas.
Integrated
Crisis Early Warning System (ICEWS)
----------------------------------------------------------------------
The
Integrated Crisis Early Warning System (ICEWS)
program seeks to DEVELOP A COMPREHENSIVE, INTEGRATED, AUTOMATED, GENERALIZABLE, AND VALIDATED SYSTEM TO MONITOR, ASSESS, AND
FORECAST NATIONAL, SUB-NATIONAL, AND INTERNATIONAL CRISES IN A WAY THAT
SUPPORTS DECISIONS ON HOW TO ALLOCATE RESOURCES TO MITIGATE THEM. ICEWS will provide Combatant Commanders (COCOMs) with a powerful, systematic capability to
anticipate and respond to stability challenges in the Area of Responsibility (AOR); allocate resources efficiently in accordance to the
risks they are designed to mitigate; and track and measure the effectiveness of
resource allocations toward end-state stability objectives, in near-real time.
RealWorld
----------------------------------------------------------------------
TheRealWorld program exploits technology innovation to
PROVIDE EVERY WARFIGHTER WITH THE ABILITY TO OPEN A LAPTOP COMPUTER AND RAPIDLY CREATE A MISSION-SPECIFIC SIMULATION
IN A RELEVANT GEO-SPECIFIC 3-D WORLD. currently,
major simulation programs are time consuming, expensive, and require
graduate-level expertise in computer programming. realworld will remove these barriers and, for the
first time, PUT THE TACTICAL ADVANTAGE OF REAL-TIME SIMULATION DIRECTLY INTO
THE HANDS OF THE WARFIGHTER.
DARPA S 2 LITER, 1KW, 10^14 SYNAPSE AGI
BRAIN
========================================
DARPA s Defense Sciences Office (DSO) is supporting the Systems of Neuromorphic Adaptive Plastic Scalable Electronics, or SyNAPSE, project. It s goal, according to its April 8, 2008
BAA (Broad Agency Announcement) is to create a system with roughly: the same
number of neurons (they want 10^10); same number of synapses (they want 10^14);
and same power as the human brain --- that will fit in a volume of 2 liters or
less, and will draw less than one kilowatt of electric power..
TheSyNAPSE BAA says:
The
vision for the anticipated DARPA SyNAPSE
program is the enabling of electronic neuromorphic
machine technology that is scalable to biological levels. Programmable machines
are limited not only by their computational capacity, but also by an
architecture requiring (human-derived) algorithms to both describe and process
information from their environment. In contrast, biological neural systems
(e.g., brains) autonomously process information in complex environments by
automatically learning relevant and probabilistically stable features and
associations .
and
Architectures
will support critical structures and functions observed in biological systems
such as connectivity, hierarchical organization, core component circuitry,
competitive self-organization, and modulatory/reinforcement
systems. As in biological systems, processing will necessarily be maximally
distributed, nonlinear, and inherently noise- and defect-tolerant.
Guilio Tononi, who has developed An
information integration theory of consciousness (described at http://www.biomedcentral.com/1471-2202/5/42 ), is working on theSyNAPSE project. As is stated in Cognitive
computing: Building a machine that can learn from experience (at http://www.physorg.com/news148754667.html
), Tononi is part of a team that will be developing a
prototype, small-mammal-brain-powered, neuromorphic AGI for the SyNAPSE project.
Tononi, professor of psychiatry at the UW-Madison School of
Medicine and Public Health and an internationally known expert on
consciousness, is part of a team of collaborators from top institutions who
have been awarded a $4.9 million grant from the Defense Advanced Research
Projects Agency (DARPA) for the first phase of DARPA's Systems of Neuromorphic
Adaptive Plastic Scalable Electronics (SyNAPSE)
project.
Tononi and scientists from
Columbia
University and IBM will work on the
"software" for the thinking computer, while nanotechnology and
supercomputing experts from Cornell, Stanford and the
University of
California-Merced will create the
"hardware." Dharmendra Modha
of IBM is the principal investigator.
'The
idea is to create a computer capable of sorting through multiple streams of
changing data, to look for patterns and make logical decisions.
There's
another requirement: The finished cognitive computer should be as small as a the brain of a small mammal and use as little power as a
100-watt light bulb. It's a major challenge. But it's what our brains do every
day.
One
of the keys to making the types of compact, low-power, extremely powerful
supercomputers SyNAPSE envisions within in this
coming decade is the memsistor.
This
is because memristors enable a synapse to be modeled
much more compactly than ever before possible. Memristors
are a type of resistor in which the resistance can be varied by changing the
magnitude or direction of current passed through it, and can be remembered
until the next time it is changed. Hewlet-Packard is
currently the world s leading developer of memsistor
technology and is an important part of the DARPA s SyNAPSE program.
So
now we've found [memristors], might a new era in artificial
intelligence be at hand? The Defense Advanced Research Projects Agency
certainly thinks so. DARPA is a US Department of
Defense outfit with a strong record in backing high-risk, high-pay-off projects
- things like the internet. In April last year, it announced the Systems of Neuromorphic Adaptive Plastic Scalable Electronics Program,SyNAPSE for short, to create "electronic neuromorphic machine technology that is scalable to
biological levels".
Williams's
team from Hewlett-Packard is heavily involved. Late last year, in an obscure US
Department of Energy publication called SciDAC
Review, his colleague Greg Snider set out how a memristor-based
chip might be wired up to test more complex models of synapses. He points out
that in the human cortex synapses are packed at a density of about 10^10 per
square centimetre, whereas today's microprocessors
only manage densities 10 times less. "That is one important reason
intelligent machines are not yet walking around on the street," he says.
'Snider's
dream is of a field he calls "cortical computing" that harnesses the
possibilities of memristors to mimic how the brain's
neurons interact. It's an entirely new idea. "People confuse these kinds
of networks with neural networks," says Williams. But neural networks -
the previous best hope for creating an artificial brain - are software working
on standard computing hardware. "What we're aiming for is actually a
change in architecture," he says.
'The
first steps are already being taken. Williams and Snider have teamed up with
Gail Carpenter and Stephen Grossberg at
Boston
University, who are pioneers in reducing
neural behaviours to systems of differential
equations, to create hybrid transitor-memristor chips
designed to reproduce some of the brain's thought processes. Di Ventra and his colleague Yuriy Pershin have gone further
and built a memristive synapse that they claim
behaves like the real thing(www.arxiv.org/abs/0905.2935).
'The
electronic brain will be a time coming. "We're still getting to grips with
this chip," says Williams. Part of the problem is that the chip is just
too intelligent - rather than a standard digital pulse it produces an analogue
output that flummoxes the standard software used to test chips. So Williams and
his colleagues have had to develop their own test software. "All that
takes time," he says.
Two
recent articles point out successes HP is making in developing memristors. This progress is so impressive that memristors may well become the major form of long
anticipated universal memories (i.e., memory that can be used substantially
like SRAM, DRAM, and flash are today. But first ways will have to be found to
substantially increase how many times memsistor can
have their values changed far beyond the number of times flash memory can be
changed. People at HP currently claim to be confidient
they can achieve such increases.
An
April 7, 2010 NYTimes article (at http://www.nytimes.com/2010/04/08/science/08chips.html
) reported Hewlett-Packard has been making significant progress on memsistor technology. In part it said:
they had devised a new method for storing and retrieving
information from a vast three-dimensional array of memristors.
The scheme could potentially free designers to stack thousands of switches in a
high-rise fashion, permitting a new class of ultradense
computing devices even after two-dimensional scaling reaches fundamental
limits
The
most advanced transistor technology today is based on minimum feature sizes of
30 to 40 nanometers and Dr. Williams said that H.P.
now has working 3-nanometer memristors that can
switch on and off in about a nanosecond, or a billionth of a second.
'He
said the company could have a competitor to flash memory in three years that
would have a capacity of 20 gigabytes a square centimeter.
Hewlett-Packard
has demonstrated memristors ("memory
resistors") cast in an architecture that can be dynamically changed
between logic operations and memory storage. The configurable architecture
demonstrates "stateful logic" that HP
claims could someday obsolete the dedicated central-processing unit (CPU) by
enabling dynamically changing circuits to maintain a constant memory of their
state
HP showed that memristive devices could use stateful logic to perform material implication a "complete" operator that can be interconnected
to create any logical operation, much as early supercomputers were made from NAND gates. Bertrand Russell espoused material implication
in Principia Mathematica, the seminal primer on logic
he co-authored with Alfred Whitehead, but until now engineers have largely
ignored the concept.
HP
realized the material implication gate with one regular resistor connected to
two memristive devices used as digital switches (low
resistance for "on" and high resistance for "off"). By
using three memristors, HP could have realized a NAND gate and thus re-created the conditions under which
earlier supercomputers were conceived. But HP claims that material implication
is better than NAND for memristive
devices, because material implication gates can be cast in an architecture that
uses them as either memory or logic, enabling a device whose function can be
dynamically changed.
All these article indicate advances in memristors
might well hasten the day when human-level AGI s are created.
For
more information on the SyNAPSE project look at the
following two links
===============================================================================================================
COLLECTIVE
INTELLIGENCE --- OUR ONLY HOPE FOR SURVIVING THE SINGULARITY
To deal
with the Singularity, and the concentrations in power
it can bring, a society s collective intelligence should be able to discuss
controversial allegations, and marshal the best evidence available to indicate
which of them seem fair or false. This
is FIG. 21 from U.S. Patent Application Publication US 2002/0059272, now in the
public domain. It describes, in patentese, an intelligent public forum that is a free-form,
selectively-collapsible outline of text and media ordered by collaborative
ranking and editing. It is viewed
through user-selectable combinations of one or more individual or collaborative
filterers. (In this hypothetical screen,
the view is filtered by all users equally.) More advanced forms of such an intelligent forum are described below
under the heading Increasing Collective
Intelligence *Before* The Singularity Takes Off .
COLLECTIVE INTELLIGENCE
--- OUR ONLY HOPE FOR SURVIVING THE SINGULARITY
========================================
Over
the next several decades there will be an explosion in the rate of technical
development. The change is expected to be so great --- many call it the
Singularity. It will drastically transform our --- economy --- society ---
values --- bodies --- and minds --- in ways that could be very good --- or very
bad.
This
explosion will be fueled by the ever increasing power of computers. Within two
decades machine intelligence is likely to vastly surpass all the powers of the
human brain. This will produce superintelligences
that can perform --- learning --- understanding --- mathematical --- scientific
--- programming --- engineering --- robotic --- manufacturing --- and --- human
interfacing --- related mental tasks much faster, better, and less expensively
than humans. (For reasons why superintelligence will
probably happen so soon, see http://fora.humanityplus.org/index.php?/topic/31-human-level-artificial-intelligence-and-its-consequences-are-near/[ on this page
at ] )
Thissuperintelligence will enable breathtaking advances
in many other technologies, including: --- nano-electronics
--- quantum computing --- networking --- brain science --- brain manipulation,
interfacing, & augmentation --- medicine --- life extension ---
biotechnology --- genetic engineering --- synthetic biology --- nanotechnology
--- molecular & self-organizing manufacturing --- robotics --- nano-robotics --- energy --- sensor networks ---
surveillance --- weaponry --- cyber crime & warfare --- and --- interactive
virtual worlds, friends, and lovers --- ones more detailed, interactive, and
exciting than those that are real.
The
Singularity will NOT occur in a vacuum.
It
will NOT occur in a realm of pure science, engineering, or philosophy. It will
NOT occur in one instant, one year, or one decade.
Instead,
it WILL occur --- over multiple decades --- in the real world --- one dominated
by struggles for --- personal --- corporate --- political --- and national ---
survival, money, and power. How the Singularity s wildly transformative
technologies will be developed and deployed will be decided largely by collective
entities --- by corporations --- governments --- political parties ---
militaries --- bureaucracies --- interest groups --- criminal gangs --- the
media --- and public opinion.
The
increasing rate and degree of change made possible by the Singularity --- and
the power it could give a very few to benefit --- or harm --- very many ---
will tend to make the world much less stable --- and much more difficult for
human institutions to govern.
In
three to five decades the Singularity could drastically increase the world s
production of food and necessities ---and/or--- replace almost all human work
for pennies an hour in a way that would prevent most people from earning a
living. It could create a relatively evenly shared plenty --- or --- extremely
concentrated wealth and power. It could enable a plurality of free, networked
voices and collaboration --- or --- enable machines to watch everything people
do, say, and think --- and punish those who disobey. It could greatly lengthen
life and health --- or --- create synthetic life forms that accidentally wreack global havoc and death. It could create machines
that greatly empower individual humans and their minds --- or --- enable superintelligences --- controlled by one group, one person,
or one system of machines --- to hack into --- and take control of ---
virtually all the machines upon which humans depend --- so as to enslave or
kill most, or all, of humanity.
We
cannot stop the advent of superintelligence. Too many
people already know how much --- technological --- economic --- political ---
and --- military --- advantage can be gained by the nations and corporations
that are first to substantially deploy it. It cannot be stopped because
computer technology and our understanding of intelligence are already so
advanced --- that most of the world s leading nations and technology companies
could develop it --- within roughly a decade --- if they tried.
It
is arguable that we will actually --- need --- superintelligence.
It is possible that without it we might not be able to deal with many of the
problems the world already is facing. It is also possible that if we were smart
enough --- as a species --- we could learn how to use it relatively safely to
create tremendous benefits for mankind.
Given
the complex, and rapidly-changing mix of choices, promises, and threats the
Singularity will present --- if humanity is to have any chance of surviving
well through this century --- we must harness the coming explosion of
technology --- itself --- to vastly increase our collective intelligence,
wisdom, and responsibility.
If
we --- as a species --- are intelligent enough to design machines that think
much more efficiently than we do --- then why can t we also design technology
to enable groups of humans --- when connected by the internet --- and augmented
by machine superintelligences --- to think together
much, much more intelligently, fairly, and responsibly?
Current
computer and internet hardware is already powerful enough to substantially
increase humanity s collective intelligence. And with the technology of the
coming decades we will be able to increase our collective intelligence much,
much more.
The
major barriers will not be technological. They will come --- from human nature
--- from religious, cultural, and national values --- and from selfish
interests.
Seen
from a system-wide viewpoint --- the current collective intelligence of many
human institutions is stunningly stupid. Here are just a few examples:
-The 2008 collapse of the world s financial markets was
caused by: --- the false meme that average American residential real estate
values never drop (although they had done so twice within the previous eighty
years) --- a system of short-term incentives that rewarded people for taking
breathtakingly irresponsible risks with other people s money --- and --- by
financial rating agencies and legislators that were --- in effect --- bribed to
ignore such dangerous risks.
-
America s Social Security Trust Fund has
been an obvious, worthless, sham for decades. It has no net worth. It is
nothing but IOU s from the federal government to itself. The trillions of
dollars of Treasury bonds the fund holds have no more value to the federal
government than the blank paper it is free --- at any time --- to print into
new notes for equal amounts and try to sell --- (i.e. borrow with). And yet our
public forum is so dysfunctional that most politicians, media voices, and
citizens have acted for decades as if the trust fund had many trillions of
dollars of --- actual --- worth. The second President Bush hinted the trust
fund s bonds had little worth --- during his ill-fated attempt to reform Social
Security --- but, for political reasons, he was not willing to drive home just
what an obvious, and harmful, lie both political parties had been telling the
American people for decades.
-America s federal government has been so short sighted it
has run up --- over many decades and under both political parties --- fifty to
eighty trillion dollars of unfunded obligations that will come due in the next
few decades. These obligations are highly likely --- given most current
economic predictions --- to throw our country into an economic crisis much,
much deeper than that we are currently in. That is, unless the federal
government has the political will to substantially raise taxes or reduce the
benefits it has promised under many entitlement programs and pension
agreements. Most political observers believe our government will make such
difficult changes --- but only after our economy has been so drastically harmed
by this expected debt crisis that our government will be absolutely forced to
do so.
As
these examples --- and thousands of others that could be listed --- indicate
--- many of society's current collective systems are not intelligent enough to
deal with many of our current problems.
If
this is true --- it is almost certain that such systems will not be smart and
wise enough to deal well with the much more disruptive choices, changes, and
challenges the Singularity will bring.
SO,
HOW CAN WE RAISE THE COLLECTIVE INTELLIGENCE OF HUMAN SOCIETY AND ITS
INSTITUTIONS TO BEST DEAL WITH THE SINGULARITY?
This
is the subject I would like to see discussed under this topic.
I
will start by adding some of my own thoughts below. But I look forward to
hearing yours.
==================
P.S.
For
some thinking on how to make democratic government more intelligent with
today s technology, go to:
MIT's
Center for Collective Intelligence at http://cci.mit.edu/
, including their experiment in collective intelligence using climate change as
the test subject at http://www.climatecollaboratorium.org/web/guest
For
a video describing one currently proposed collective intelligence system see http://www.youtube.com/watch?v=ue-ibFH9zTA (Thanks to TransAlchemy
for pointing this out under the Sousveillance topic)
WHAT IS COLLECTIVE INTELLIGENCE?
========================================
Much
of important human behavior is performed by groups of people --- such as
businesses, militaries, governments, and the voting public. These collections
are capable of acting like thinking entities --- by obtaining information,
making decisions, and taking actions.
Collective
intelligence is the art and science of increasing the intelligence and
effectiveness of human collective entities. Legal systems, military
hierarchies, corporate management systems, and Robert s Rules of order, are
just a few examples of forms of collective intelligence that were started long
before the computer/internet era.
In
one or two decades an explosion in the rate of technology --- called the
Singularity --- will start. It will
present humanity with a rapidly growing set of extremely powerful and
transformative technologies --- ones that can be used to greatly change ---
benefit --- and/or --- harm mankind. For the world's governments and human
institutions to deal well with these extremely rapid and profound changes we
need much more enlightened and powerful collective intelligence.
If
democratic and reasonably egalitarian human values are to survive into the
Singularity --- humanity will need a much more intelligent public forum. This
forum should be fully empowered by the potential of the internet, computers,
artificial intelligence, and --- within two decades --- by machine superintelligence. It should be designed to increasingly
enlighten public opinion and debate --- and --- to increasingly transfer power
--- from the narrow interests of politicians and political parties in winning
elections and of individual corporations in making money --- to the broader
interests of the people as a whole.
We
will still want political office holders and corporations for many years to
come. But we should be intelligent enough to design feedback loops ---
including that of voters and consumers enlightened by an intelligent public
forum --- that make politicians and corporations better serve society as a
whole.
As
we progress more deeply into the Singularity --- technology will give us
tremendous options to change human existence. Human culture, human thinking,
and human communication will increasingly be dominated by --- machine
intelligence --- electronically or chemically altered states of mind --- and
increased communications between minds and between minds and machines. These
changes can be so great it might become difficult to distinguish what human
does --- or should -- mean. It will increasingly become less clear what makes
an unaltered, flesh-and-blood, person more human than, say --- a superintelligence that similates
one or more uploaded human minds -- or --- a whale with a brain implant that
gives it the added mental capabilities to converse in spoken human natural
language on the web.
Since
the only purpose of intelligence is to serve goals and values --- to be
collectively intelligent --- humanity will have to decide what are its most
important goals and values --- and to create feedback loops that encourage and
reward human intelligence and behaviors that serve such purposes.
It
is important that we humans have the collective wisdom to shape reality in ways
that makes the transition into the future as happy,
and meaningful, as possible --- for as many people as possible.
INCREASING COLLECTIVE
INTELLIGENCE *BEFORE* THE SINGULARITY TAKES OFF
========================================
Current
computer and internet technology already has the power to greatly improve the
intelligence, effectiveness, and fairness of our society. For example, Wikipedia has demonstrated the tremendous potential of
collective intelligence. I never cease to be amazed at what wonderfully concise
and relatively understandable descriptions it provides on many extremely
complex scientific subjects at which I am a relative novice--- such as string
theory or relativistic space-time curvature --- and how often its coverage on
many controversial social or historical subjects is more balanced than most
articles on similar subjects in the mass media.
We
should try to develop something that applies the virtues of Wikipedia
and other forms of human networked collaboration to making democracy s free
market place of ideas --- and its control of our government through public
opinion --- much more intelligent, fair, and responsible.
To
do so, we need an intelligent, collaborative, public forum. This forum should
be a marketplace of ideas where everybody has an equal voice, but collaborative
filtering and editing causes the most attention to be given to the most
persuasive voices --- and causes those voices to be as articulate as possible.
On
many issues, there is often no commonly agreed to notion of what is right or
wrong --- important or unimportant. Thus, participants in the forum should be
able to rapidly select between sets of human or algorithmic filters to rank
what a given view of the forum presents --- as the most important, most
articulate points for, against, and about policies and issues of interest to
the user. A view that weights the rankings and votes of all participant s
equally should be the default view, and will help people get an overview of how
their city, state, nation, or the world --- as a whole --- views a given set of
issues.
The
intelligent forum should --- like Wikipedia --- build
a permanent, but evolving, record. This record should be a collaboratively
ranked, edited, commented, and voted-on, selection of media, arguments, and
discussions on topics, issues and policies. Any filtered view of it will select
which, and how many, of those entries are shown, and the ranked order and
format in which they are shown. It should include the most important reporting
and interpretations of news events --- as they occur --- and over time. It
should also create a trace of the evolution of the forum, its entries, and its
various rankings and votes over time.
The
increasingly sophisticated natural language understanding tools that are
starting to appear --- and that will get more sophisticated every year ---
should be employed to enable a user to quickly find discussions, opinions, and
facts of interest, including those that most relate to something a user wants
to read, or register an opinion about. It should enable them to see what, if
any posts, are closest to the opinions they want to express. It should enable
them to view, edit, comment, vote upon, and/or increase their ranking of such
prior posts. And it should enable them to enter new posts, if they think that
would do a better job of promoting the opinions they want to express.
This
public forum should be designed to be the electronic brain of society. It should
be the major forum for communicating media related to entertainment, art,
social connections, science, philosophy, religion, and --- (most relevant to
this discussion) --- news, politics, and public policy. This way, almost all
people will become fluent in its use. It should be designed to handle, mix, and
index virtually all major media types. It should be created --- much as Google
Wave is --- to provide a standard interface to such media and commenting --- so
multiple cloud-service providers can display data in the forum --- even if it
was entered using a different cloud provider.
It
is vitally important the forum be built to be as resistant as possible to
corruption by service providers, people attempting to bribe them, or hackers
--- because when major issues are at stake, it is certain some powerful vested
interests would --- if they could --- use unethical means to distort the forum
in their favor. One of the most important tasks of collective intelligence ---
going forward --- should be to highly motivate many of the best minds to
understand how to keep our computers, the web, and the public forum as free
from the malicious influence of hackers, and people trying to cheat such
systems, as possible.
All
news, political, or advertising media should remain permanently accessible
(with continuing advertising-per-view rights belonging to the owners of such
media). Such media should be subject to collaboratively edited and filtered
commenting, to keep it more honest. Whenever political opinions or political
and commercial ads are shown --- a viewer should be able to instantly view,
comment, edit, rank, or vote on the collaboratively commented version of the ad
--- as viewed through any one of a selection of filters. If this is done,
whenever a news report, opinion piece, or advertisement pushes bad facts,
products, policies, or politicians --- chances are users will be able to find
evidence on how misleading the opinions or ads really are. This will decrease
the value of opinions and advertising that are not honest, and increase the
value of those that are --- something that would be very valuable in commerce,
as well as in politics.
Such
a forum should have a social networking component, to enable groups to form
collective filters to represent a given viewpoint, constituency, or attempt at
objectivity. It should be designed to help develop teams to --- review, rank,
comment, and create edited versions of posts on given topic --- review complex
issues or legislation --- and perform investigative journalism or research.
Such teams should have their own intelligent forums --- in which only those
allowed by the team can participate --- to enable them to coordinate their
action. Those who create or manage such teams should be free to allocate
ranking and voting power within their own forums. They should be able to use
collaborative feedback within their own intelligent forum to provide social
network credibility, status, and special privileges for the people whom others
in the team think have done the most good work on such
collective projects. Team members, as well as all other users of the network,
should be allowed to temporarily delegate portions of their ranking and voting
power to one or more teams whose work they like.
In
such a system, users or teams should be able to collaboratively suggest,
refine, rank, and finance requests for real world reporting, research, polls,
or investigation on subjects of interest. The forum should have mechanisms for
collaboratively awarding contracts, and paying, for such work. In general, it
is important that methods be found to fund good reporting and investigative
journalism at city, state, national, and global levels in the internet era. It
is also important the public forum place an emphasis on reputation and evidence,
and provide tools for helping people determine
information regarding each.
Yes,
most of the time spent in such a public forum will be dedicated to things like
sports, celebrities, movies, and TV shows. But many of those who have the
largest voices and contribute the most to decision making in the worlds of
business, academia, the military, government, and media would be likely to use
it in a more serious way --- as would many more ordinary citizens who are truly
concerned about the future.
Yes,their would be fanatical and dishonest voices in such
a forum --- such as those who say the
earth-is-less-than-ten-thousand-years-old. But collaborative filtering could
point out to any who were interested in knowing the truth, the best arguments
and evidence for and against such voices --- and this would tend to greatly
narrow the appeal of ideas that the substantial weight of evidence suggest are
unreasonable.
If
such an intelligent public forum can be designed to resist corruption and
hacking --- good ideas will be much more likely to win out over bad ones --- no
matter how much money is spent pushing the bad ones. In such a system, speech
will be truly free, and the speech that is most heard or seen will be that
ranked most important by people users trust. This will greatly reduce the
current need for politicians in
Washington to sell their souls for money to
run substantially meaningless TV ads.
All
of this could be done with current technology. It could involve combining
features from Wikipedia, Google, YouTube,
Google Wave, Digg, Facebook,
Wolfram s Alpha, and other current web sites. It is important that network
guru s, network companies, people who are interested in good governance, media
producers, and public-minded copyright attorneys work to design such a largely
open-source, unified, web system --- one that can be hosted by multiple
companies to make it less subject to corruption or bias --- and one that will
provide the money necessary for proper reporting and investigating of issues of
importance..
It
is important that humanity get its collective act together --- in an
intelligent --- relatively democratic --- relatively egalitarian way --- before
our human institutions have to take the reins of the --- wild --- strong ---
fast --- pull into the strange new future --- of the Singularity.
INCREASING COLLECTIVE
INTELLIGENCE *AFTER* THE SINGULARITY TAKES OFF
========================================
Vernor Vinge said it is hard, or
impossible, to predict what the world be like after the Singularity. But we can
imagine the powers of some of the technologies that are likely to be available
once the singularity does, in fact, take off. And we can try to think how thosetechologies could be used to make humanity more
intelligent --- and better able to cope with the Singularity, itself.
The
Singularity will probably produce clouds of machine superintelligence
powerful enough to store --- in semantic deeps structure --- much of the data
in all of the world s books, in all of the internet, and in all publicly available
movies, video, audio, still pictures, and diagrams --- and to reason from that
data thousands or millions of times faster than humans.
This
will enable us to use speech, natural language, and vision interfaces to ask
such superintelligences complex questions. Users will
be able to ask, and see the answers to, such questions through a netbook, smart phone, head-mounted retinal-scanning
computer, or, ultimately a wireless brain implant. The cloud will be able to
clarify and answer such questions --- in a conversationally interactive manner
--- with real-time, articulate text, speech, video, and animation. This will
include providing the evidentiary support for any of the answer s assertions,
if desired by the user. By roughly mid-century it is likely a query of the
complexity of a legal opinion on a specific, novel problem --- one that would
currently take a good human lawyer several days to prepare --- could be
produced --- within seconds --- for the current advertising value of a Google
search.
Such
a cloud could similarly provide arguments and evidence for and against various
proposals, and cite the reasons for trusting and distrusting various sources of
evidence. And it could make models, simulations, and projections regarding
complex economic, political, ecological, or scientific issues and proposals,
and explain all the evidence and assumptions behind such models. In addition,
such superintelligence could provide educations ---
much better than any currently available --- to all of society
. And it could also let people collaboratively think and act together in
ways never before possible.
For
example, people can use such intelligence to help them search, navigate, post
to, edit, comment, and rank entries in a collaborative intelligent forum, like
that described in the section above. Superintelligences
could help humans to: --- instantly find the best information and arguments
regarding a given topic, as ranked by people or machines they trust --- see the
viewpoints on such issues that are held by other groups of people --- more
rapidly research and compose articulate, well-supported entries in such a forum
--- and --- more accurately check the validity or reputation of arguments,
contributors, filterers, or evidence --- including providing metrics on the
accuracy or efficacy of predictions or actions taken by individuals, groups, orsuperintelligences in the past.
Within
one to four decades it is likely many people will have wireless, high bandwidth
network interfaces in or on their brains. This will enable them to send
information to, and receive it from, specific superintelligences,
the intelligent cloud, and other humans similarly connected. This will let us
communicate with much greater speed and fluidity with machines, other human
minds, navigable representational spaces, and virtual realities. Machine superintelligence can be used to enable the thoughts of
thousand, millions, or billions of people to be compared, summarized, filtered,
and broadcast in real time --- or across time --- enabling people to --- in
fact --- think together as one collective mind.
The
Singularity may well enable what Goertzel and Bugaj
call Sousveillance in their interesting article at http://fora.humanityplus.org/index.php?/topic/27-sousveillance-and-artificial-general-intelligence/
. Sousveillance is a form of pervasive surveillance
that is done by everyone and which watches everyone. It is not Big Brother
watching us --- it is all of us watching each other. Ultimately it will be able
to monitor people's thoughts as well as their actions. Although this would
grossly violate most current notions of privacy --- something like this may
well be necessary in the future. This is because --- as the Singularity s
technical advances make it possible for fewer and fewer people --- and fewer
and fewer machines --- to harm more and more other people --- it may well
become necessary for everyone --- and all machines --- to be watched by other
people and by machines people trust. As Goertzel and Bugaj
discuss --- having the intimate closeness sousveilance
could bring might well engender a much deeper sense of shared interest between
humans, and between humans and the machines that interconnect them.
If
we --- as a species --- have the wisdom to use the technology of the
Singularity well --- humanity could achieve collective superintelligence
--- and --- with that collective power and understanding --- humanity might well
thrive --- for many decades ---and, perhaps, many centuries --- into the
rapidly changing future.
SOME OF THE ISSUES COLLECTIVE SUPERINTELLIGENCE
MIGHT HELP US SOLVE
The
Singularity will create many questions that collective superintelligence
can help humanity better answer. Among many others --- these include the
following:
-1- ONCE COMPUTERS AND ROBOTS CAN DO ALMOST
EVERYTHING BETTER THAN HUMANS, FOR PENNIES AN HOUR: --- HOW WILL MOST HUMANS
EARN A LIVING --- WHAT MEANINGFUL WORK WILL THEY HAVE --- AND --- HOW SHOULD
POWER AND WEALTH BE DISTRIBUTED?
========================================
In
1976 James Albus --- an early leading thinker in
robotics and artificial intelligence who has held important positions in NASA
and the National Institute of Standards and Technology --- published a book
called People s Capitalism: The Economics of the Robot Revolution. It
envisioned that one day machines would put most people out of well paying work.
To counter this, he proposed that virtually all people be granted ownership of
enough corporate stock that most could earn a middle-class income from their
ownership of the companies that owned the machines.
Something
of this scale will probably have to be done to prevent the age of superintelligent machines --- and the robots they control
--- from concentrating almost all wealth and income into a relatively small
ownership class. We will need collective wisdom to know how to best do this. We
need to develop a new, intelligent, realistic, social contract to deal with
such issues.
If
most people are going to have to be subsidized, I think it is important that
they work for their subsidies. I believe it is important that most humans
continue to work --- even if machines could do their jobs for less. This is to
--- make people feel they are earning a living --- add purpose to their lives
--- and keep them and their skills in touch with the real world, other humans,
and human needs. For these purposes most people would only need to work 20 to
30 hours a week --- giving them plenty of free time to pursue their personal
interests. It is important that individuals and groups be rewarded --- in terms
of money and power --- as a function of how much they contribute to others ---
and that we develop proper metrics for measuring such contribution. Properly
designed feedback loops are essential to continued human well-being.
If
we are collectively intelligent there are likely to be more than enough jobs
for most people to perform.
One
important class of jobs we should keep people in --- even if they could be
performed less expensively by machines alone --- are many human service jobs.
This includes --- raising and helping educate children --- providing social,
medical, and psychological services --- waiting on tables --- being airline
stewards and stewardesses --- providing personal grooming --- and many forms of
personal counseling, coaching, and religious or spiritual guidance. Keeping
people in such roles --- even if their work is amplified by machines --- would
make the world seem more "human" and will increase the importance of
real world interactions between people. Other types of work we should keep
people in include sports, the arts, entertainment, blogging,
reporting, and investigating.
Another
major occupation for humans should be the monitoring and management of
machines, and mechanized manufacturing, farming, transportation, and the
provision of other economic goods and services. We should keep private
corporations and businesses, so competition can be used to help reward the
development of many important human skills, products, and services. Such
competition should be monitored and reasonably regulated by a government
ultimately controlled by the intelligent public forum.
One
type of machine monitoring that is particularly important, is the work of
protecting humans and our trusted machines --- including those in
manufacturing, infrastructure, transportation, the cloud, and the intelligent
public forum, itself --- from malicious people or machines, and their attempts
to hack into and take control of our trusted machines.
Yet
another major type of work for humans after the Singularity is to provide
neighborhood, city, state, national, and world governance --- aided by a superintelligence-enhanced public forum. This would involve
having a high percent of people participate in collaborative panels,
committees, and governing structures to study and deliberate on issues and
problems facing society, and various proposals for dealing with them. It would
also involve having more people act as judges and juries, in virtual courtrooms
in which judges and jurors have access to superintelligent
legal advice --- so as to make the legal process much faster, efficient, fair
--- and much less expensive. Presumably much of litigation could be argued by superintelligent virtual litigators --- ones controlled by
the client, a trusted friend, or perhaps one or more human lawyers. This way each side would be likely to get a roughly equally
talented, attractive, and charming virtual lawyer, all for very little money.
Machines
could perform many governing and judging tasks better than people --- but it is
important for humanity to keep people in the driver s seat, as much as
possible, in such vital feedback loops.
-2- WHAT DEGREE OF INDIVIDUALISM, PRIVACY, AND
COMPETITION SHOULD WE HAVE IN AN AGE WHEN WE ARE ALL NETWORKED TOGETHER ---
ULTIMATELY THROUGH BRAIN IMPLANTS.
========================================
Diversity
has value. Computer evolutionary learning systems --- such as genetic
algorithms --- benefit from having the transfer of genes come largely from
within diverse --- loosely interconnected --- breeding sub-populations. This is
because it enables alternative evolutionary approaches to be developed over
multiple learning generations.
For
similar reasons, it is important to maintain a certain amount of human and
cultural plurality, individualism, and competition --- as humans advance deep
into the Singularity. In the rapidly changing future --- humanity will need an
efficient marketplace of ideas --- one that rewards the creation --- and
bringing to the fore --- of multiple good approaches for dealing with important
changes as they happen. Similarly we need competition to create feedback loops
that reward individuals and organizations for developing productive
intelligence, skills, discipline, focuses, ideas, products, and services. This
is particularly true because the Singularity will generate many extremely
tempting artificial realities, and, thus, it is vital we reward people who stay
plugged into the real world.
But
too much diversity of thought and values can result in destructive dislike and
conflict, and too much selfish competition can hurt society.
Society
works best if people are selfish enough to focus on caring sufficiently for
themselves and those around them, and if they are motivated to be competitive
in productive ways. We want people to have enough ego
to seek to distinguish themselves from others in non-harmful ways that make
them interesting. But we have all seen the harm that too much selfishness and
ego can cause.
Hopefully
a superintelligent public forum --- and other means
for better communication between human minds --- can help humanity to best
decide how to balance the competing demands between diversity and compatibility
--- and betwen selfishness and community.
-3-
HOW DO WE KEEP HUMANS IN THE
LOOP
--- AND --- PREVENT SUPERINTELLIGENCES FROM HARMING
US.
========================================
We
need to keep humans in the loop --- even if --- as some transhumanist
predict --- it is necessary that humanity increasingly become more and more
machine. It is important that we not overly rely on machine intelligence. It is
important that large numbers of humans have intimate understanding of machine intelligence,
machine and network security, and hacking --- and how they all work. It is
vital that we know what types of machine intelligences are relatively safe, and
those that are relatively dangerous. It is important that many people, in
conjunction with trusted machines, monitor all powerful machines for threats.
We
need to have many people who know and monitor these things --- because we can
be certain malicious people, corporations, nations, or machines will try to
hack into our trusted superintelligences and take
control of them. It is essential that those of us who abide by the social
contract --- when combined with our trusted superintelligences
--- can detect and counter such hacking.
If
machine intelligences are allowed to evolve independently of supervision by
humans and their trusted machines, it is almost certain such intelligences
would evolve, over time, to satisfy their own interests --- not ours. If a
powerful enough set of superintelligences turned
against humans, it is almost certain they could kill us all.
Thetranshumanists may well be right. We humans largely
rule the earth because our intelligence and knowledge excels that of all other
species. By analogy, it only makes sense that --- starting in several decades
when there are likely to be networks of many superintelligences --- each thousands of times
smarter than humans --- there will ultimately come a time when machines take
domination away from us. That is, perhaps, unless we join them, and make them
part us, and us part them. There are already many who look forward to
connecting their brains to superintelligences --- and
it is almost certain, that once superintelligence
arrives, the people who use such implanted, high bandwidth, connections to such
machines will be more successful than those who do not. This closeness to
machines, and the better use of them it could provide, might help humans to
survive.
I
am confident extremely powerful and relatively safe superintelligences
can be made. What I worry about is: --- will more "dangerous forms of
machine intelligence be more useful and more powerful than more
"safe" forms --- and if so, by how much? This is a concern, because
less safe forms of AI that have more freedom to adapt their goal and control
structures and to redesign themselves --- might well --- because of their adaptivity, evolution, and unpredictability --- prove much
more powerful and creative than most stable and safe forms of intelligence ---
and much more capable of out-foxing them. If this proves true --- it is almost
certain unethical people, or machines, would try to use such less-safe forms ofsuperintelligence for competitive advantage --- such
as for hacking into other AI s, so as to control them for selfish or dangerous
purposes. That may well be why, in the future, we will need something like
Goertzel and Bugaj s sousveillance
--- with trusted machines watching all other machines.
In
the early 1970 s I used to tell the few people that would listen to me --- that
the future of mankind might well rest on how well humanity --- using millions
of relatively safe, what I called Fido, machines
--- could fight off threats created by the more free thinking, and presumably
more powerful and hard to control, machines.
I
still think this face-off might well determine the fate of humanity.
-4-
HOW MUCH SHOULD WE CHANGE OUR VALUES, BODIES, MINDS, AND HUMAN NATURE --- HOW
MUCH SHOULD WE MERGE WITH MACHINES --- AND --- WHAT ASPECTS OF HUMANITY ARE
MOST IMPORTANT TO PRESERVE.
========================================
America s Founding Fathers --- and Sigmund
Freud s Society and its Discontents --- both agreed on one thing: --- human
nature is deeply flawed.
Human
nature did not evolve to be happy or coherent, as much as to breed and have
offspring that survive. This has given humans emotions and drives that, at
times, are harmful to themselves and others --- such
as --- sexual jealousies --- inappropriate selfishness and aggressiveness ---
and --- harmful impulsiveness, urges, and addictions. The Singularity will give
us enough understanding of our brains that we will be able to dramatically
change our minds, drives, emotions, and mental self-control. We need tremendous
collective intelligence and wisdom to best decide what, if anything, we should,
or must, change in our brains and in our human nature.
Similarly
we need to decide how intimate a relationship we want, or need, with machine
intelligences and with the consciousnesses of other humans --- and to what
degree we want to actually become machine. We will probably start with headsets
having --- retnal scanning, to give us see-through HD
visual input --- earbuds to give us audio --- eyetracking to give is faster-than-mouse pointing and
selection --- microphones and subvocalization
detectors for speech input --- cameras to record everything around us --- and a
high-bandwidth, wireless connection to the superintelligent
cloud. Then we will move on to brain implants that can directly communicate brainstate information from and to the mind. As brain
science advances we will be able to use electronics and chemistry to have much
greater control over ours, or other people s, brains. Once molecular
fabrication becomes commercially feasible, we will be able to make powerful,
small superintelligent add-ons that can be implanted
into our brains. And, of course, many transhumanist
look forward to the day when people can upload their minds to run on artificial
brains.
It
is not clear how human these progressively altered minds would be.
One
of the issues I have with the uploading of human minds is that --- it is not at
all clear it would be safe to have minds --- with all the problematic emotions
and drives of humans --- running on a superintelligence.
It is not clear how long computer hardware running an uploaded mind of someone
like Bernie Madoff would be willing to stay within
the rules for human friendly AI that people like EliezerYudkowsky, of the Singularity Institute, are trying
to write. And if there were millions or billions of human brains uploaded and
running on machines --- might not a large schism develop between the
flesh-and-blood and the uploaded humans. This schism would tend to grow if it
proves easier expand the intelligence of minds running on hardware than those
running inside human bodies --- which might well be the case.
Superintelligence will be able to create artificial worlds, friends, and
lovers for us that are likely to be much more romantic, emotionally satisfying,
and addictive than real ones. The transhumanist
suggest this will make it much more pleasant for us to accept the man-machine
merger they claim is necessary --- if we want any remnant of what we call
human to remain competitive for more than several decades after the advent of
machine superintelligence.
But
such artificial realities could also be used by machines --- or humans
manipulating such machines --- to get emotional control over our minds. That is
why I think we need to design a future that keeps humans in important
real-world control and feedback loops. Virtual worlds are great for R&R --- and for representing, viewing, and navigating
complex scientific, mathematical, economic, and social information ---
including information in the intelligent public forum --- but it is important
that as many people as possible keep at least one foot firmely
grounded in real reality.
In
sum, as we transition into the Singularity --- we need to understand: --- what
it is we truly value about ourselves and other humans --- what sort of
existence we want for our children, and their decendants
(even if, as some transhumanist suggest
, their descendants might become increasingly more machine) --- and ---
how to best maintain those values and goals as far as possible into the coming
age of unimaginable change.
Advances
in brain science, human psychology, the psychology of machine intelligence ---
and the understanding and enginering of
consciousness, itself --- in the coming decades --- should help us better
understand our own minds and emotions --- and how they can best be served by
social institutions and machine intelligence. This understanding--- combined
with closer connections between human minds --- and between human minds and
collective superintelligence --- might well make ---
humanity's transition into the future --- a largely happy and meaningful one.
CONTROLLING AGI S BY THE COLLECTIVE WILL OF
HUMANITY: GOERTZEL S THEORY OF COHERENT AGGREGATED
VOLITION
========================================
In
the comments that follow Ben s initial post, I argue it will require more
collective intelligence to properly derive such Coherent Aggregated Volition.
This
is a BORG Manifesto Ed. Better Organised Robotic
Genius. Bring it on. By the way Ed, I think that the drive of your ideas comes
from a enhancement hominist
world view, not humanist.
======
Ed Porter
There
is a good chance humanity has no choice but to head increasingly toward Borgdom. Humanity's increasing addiction to the Internet is
just the start.
In
the blog by Goertzel I linked to I am arguing for
taking steps to help make the Borgdom that is coming
be a more intelligent democratic, reasonably egalitarian, and human-centered.
With
regard to "hominist" vs.
"humanist," I am not even sure what "hominist"
means. One def I found on the web said "One who advocates equal rights for
men", which I definately support. Another
implied it was a male sexist, which I don't. I had a bright, strong mother, and
most of the women I like are bright and strong, and so I am opposed to male
sexism --- but I am also opposed to female sexism. Having been in an extremely bitter
custody dispute, I can tell you men have no monopoly on selfishness.
When
it comes to the man/machine divide, I am probably more of a speciesist
than some on this list, even though I think machines are likely to win in the
end. But perhaps by then we will have been able to increasingly become more
machine ourselves --- and perhaps we will have learned enough about the
engineering of conscioiusness to share our
consciousnesses with machines, in a way that makes us vastly more consciously
aware.
A
RESPONSE TO GOERTZEL S COSMIST MANIFESTO
========================================
The
following is my response to
Ben Goertzel s A Cosmist Manifesto as it existed
at as of
April 12th, 2010, at http://cosmistmanifesto.blogspot.com/
The
core of Ben s philosophy of Cosmism --- as I understand it --- is to
emotionally embrace the radical change the singularity will bring, and to be
optimistic that is will be for the good of what we as humans should care about
--- for our own future happiness.
Barring
some extreme setback to humanity --- the radical change that will be created by
the advent of machine superintelligence is
unavoidable. Thus, it makes sense for humans to view the inevitable aspects of
such change in the most emotionally pleasing possible light --- for our own
emotional wellbeing.
So
there is very much to say in favor of Ben s joyous embrace of the future.
There
is a long tradition of philosophies that emphasize optimism. Studies have shown
that a healthy dose of optimism tends to improve the outcomes of individual who
indulge in it. And it has long been understood that acceptance of the
inevitable is an important part of wisdom.
But
like Voltaire s Candide, I believe that --- instead of
just being optimistic and believing "all is for the best in the best of
all possible worlds" --- we must also cultivate our own garden ---
otherwise the weeds and worms of reality will destroy it. Blind optimism alone
is not enough. There are many harmful and destructive force within reality,
including, those history has proven to be within human nature itself.
It
is not clear Ben s Cosmist Manifesto denies the necessity to fight reality s
destructive forces --- but it certainly does not emphasize that need.
History
is full of man s cruelty to man. If summed, all the holocausts of the 20th
century killed 150 million to 180 million people. If your spiritualism is
anything other than selfish --- preventing killings at such a level should be
of concern to you. And if we blow the transition to the future, the level of
killing and horror could be much greater. A small group of selfish humans using
the power of machines --- or the machines themselves --- could enslave or kill
all of humanity. Biotechnology or nanotechnology gone astray could kill all of
humanity in something much worse than the Black Death --- that is --- a
complete extermination of all mankind, or even of all higher life forms.
Is
the possibility of such a disaster something to be blissfully and blindly
joyous about?
Yes,
one could just say "whatever happens is for the good," so there is no
reason to strive to change to the flow of history, even if such a change is
necessary to avoid mass exterminations. By this standard, the world *should*
have done nothing to avoid Hitler s slaughtering of the Jews, or of the much
larger number of non-Jews his forces killed. After all, if Hitler had killed
all non-Germans on earth --- man, woman, and child --- and replaced them with
an equal number of German Aryans --- there would have been no net loss of
intelligence and no net loss of consciousness.
Would
the Cosmist Manifesto say that a repeat of such a mass killing would not be
something to mightily and fiercely oppose --- alleging that it is only by a
narrow, old fashioned, overly humanistic concept of self that the deaths of
millions or billions of humans is in anyway a loss --- as long as those lives
are replaced by machine consciousnesses of equal number and/or quality.
So
--- I would say --- the Cosmist Manifesto SHOULD NOT ONLY ask us to embrace the
possibilities of the future, and to embrace to the abilities of machine
intelligences to enlarge and expand our notions of what is valuable in a mind
---- BUT SHOULD ALSO ask us to be wide eyed, vigilant, and collectively
intelligent about the dangers of the Singularity --- so we can best avoid them
--- and have the best chance of reaching the enlightened future the manifesto,
itself, envisions.