If you are interested in collective intelligence, consciousness, the global brain and the evolution of artificial intelligence and superhuman intelligence, you may want to see my talk at the 2008 Singularity Summit. The videos from the Summit have just come online.
(Many thanks to Hrafn Thorisson who worked with me as my research assistant for this talk).
In this interview with Fast Company, I discuss my concept of "connective intelligence." Intelligence is really in the connections between things, not the things themselves. Twine facilitates smarter connections between content, and between people. This facilitates the emergence of higher levels of collective intelligence.
I've been thinking lately about whether or not it is possible to formulate a scale of universal cognitive capabilities, such that any intelligent system -- whether naturally occurring or synthetic -- can be classified according to its cognitive capacity. Such a system would provide us with a normalized scientific basis by which to quantify and compare the relative cognitive capabilities of artificially intelligent systems, various species of intelligent life on Earth, and perhaps even intelligent lifeforms encountered on other planets.
One approach to such evaluation is to use a standardized test, such as an IQ test. However, this test is far too primitive and biased towards human intelligence. A dolphin would do poorly on our standardized IQ test, but that doesn't mean much, because the test itself is geared towards humans. What is needed is a way to evaluate and compare intelligence across different species -- one that is much more granular and basic.
What we need is a system that focuses on basic building blocks of intelligence, starting by measuring the presence or ability to work with fundamental cognitive constructs (such as the notion of object constancy, quantities, basic arithmetic constructs, self-constructs, etc.) and moving up towards higher-level abstractions and procedural capabilities (self-awareness, time, space, spatial and temporal reasoning, metaphors, sets, language, induction, logical reasoning, etc.).
What I am asking is whether we can develop a more "universal" way to rate and compare intelligences? Such a system would provide a way to formally evaluate and rate any kind of intelligent system -- whether insect, animal, human, software, or alien -- in a normalized manner.
Beyond the inherent utility of having such a rating scale, there is an additional benefit to trying to formulate this system: It will lead us to really question and explore the nature of cognition itself. I believe we are moving into an age of intelligence -- an age where humanity will explore the brain and the mind (the true "final frontier"). In order to explore this frontier, we need a map -- and the rating scale I am calling for would provide us with one, for it maps the range of possible capabilities that intelligent systems are capable of.
I'm not as concerned with measuring the degree to which any system is more or less capable of some particular cognitive capability within the space of possible capabilities we map (such as how fast it can do algebra for example, or how well it can recall memories, etc.) -- but that is a useful second step. The first step, however, is to simply provide a comprehensive map of all the possible fundamental cognitive behaviors there are -- and to make this map as minimal and elegant as we can. Ideally we should be seeking the simplest set of cognitive building blocks from which all cognitive behavior, and therefore all minds, are comprised.
So the question is: Are there in fact "cognitive universals" or universal cognitive capabilities that we can generalize across all possible intelligent systems? This is a fascinating question -- although we are human, can we not only imagine, but even prove, that there is a set of basic universal cognitive capabilities that applies everywhere in the universe, or even in other possible universes? This is an exploration that leads into the region where science, pure math, philosophy, and perhaps even spirituality all converge. Ultimately, this map must cover the full range of cognitive capabilities from the most mundane, to what might be (from our perspective) paranormal, or even in the realm of science fiction. Ordinary cognition as well as forms of altered or unhealthy cognition, as well as highly advanced or even what might be said to be enlightened cognition, all have to fit into this model.
Can we develop a system that would apply not just to any form of intelligence on Earth, but even to far-flung intelligent organisms that might exist on other worlds, and that perhaps might exist in dramatically different environments than humans? And how might we develop and test this model?
I would propose that such a system could be developed and tuned by testing it across the range of forms of intelligent life we find on Earth -- including social insects (termite colonies, bee hives, etc.), a wide range of other animal species (dogs, birds, chimpanzees, dolphins, whales, etc.), human individuals, and human social organizations (teams, communities, enterprises). Since there are very few examples of artificial intelligence today it would be hard to find suitable systems to test it on, but perhaps there may be a few candidates in the next decade. We should also attempt to imagine forms of intelligence on other planets that might have extremely different sensory capabilities, totally different bodies, and perhaps that exist on very different timescales or spatial scales as well -- what would such exotic, alien intelligences be like, and can our model encompass the basic building blocks of their cognition as well?
It will take decades to develop and tune a system such as this, and as we learn more about the brain and the mind, we will continue to add subtlety to the model. But when humanity finally establishes open dialog with an extraterrestrial civilization, perhaps via SETI or some other means of more direct contact, we will reap important rewards. A system such as what I am proposing will provide us with a valuable map for understanding alien cognition, and that may prove to be the key to enabling humanity to engage in successful interactions and relations with alien civilizations as we may inevitably encounter as humanity spreads throughout the galaxy. While some skeptics may claim that we will never encounter intelligent life on other planets, the odds would indicate otherwise. It may take a long time, but eventually it is inevitable that we will cross paths -- if they exist at all. Not to be prepared would be irresponsible.
There has been a lot of hype about artificial intelligence over the years. And recently it seems there has been a resurgence in interest in this topic in the media. But artificial intelligence scares me. And frankly, I don't need it. My human intelligence is quite good, thank you very much. And as far as trusting computers to make intelligent decisions on my behalf, I'm skeptical to say the least. I don't need or want artificial intelligence.
No, what I really need is artificial stupidity.
I need software that will automate all the stupid things I presently have to waste far too much of my valuable time on. I need something to do all the stupid tasks -- like organizing email, filing documents, organizing folders, remembering things, coordinating schedules, finding things that are of interest, filtering out things that are not of interest, responding to routine messages, re-organizing things, linking things, tracking things, researching prices and deals, and the many other rote information tasks I deal with every day.
The human brain is the result of millions of years of evolution. It's already the most intelligent thing on this planet. Why are we wasting so much of our brainpower on tasks that don't require intelligence? The next revolution in software and the Web is not going to be artificial intelligence, it's going to be creating artificial stupidity: systems that can do a really good job at the stupid stuff, so we have more time to use our intelligence for higher level thinking.
The next wave of software and the Web will be about making software and the Web smarter. But when we say "smarter" we don't mean smart like a human is smart, we mean "smarter at doing the stupid things that humans aren't good at." In fact humans are really bad at doing relatively simple, "stupid" things -- tasks that don't require much intelligence at all.
For example, organizing. We are terrible organizers. We are lazy, messy, inconsistent, and we make all kinds of errors by accident. We are terrible at tagging and linking as well, it turns out. We are terrible at coordinating or tracking multiple things at once because we are easily overloaded and we can really only do one thing well at a time. These kinds of tasks are just not what our brains are good at. That's what computers are for - or should be for at least.
Humans are really good at higher level cognition: complex thinking, decisionmaking, learning, teaching, inventing, expressing, exploring, planning, reasoning, sensemaking, and problem solving -- but we are just terrible at managing email, or making sense of the Web. Let's play to our strengths and use computers to compensate for our weaknesses.
I think it's time we stop talking about artificial intelligence -- which nobody really needs, and fewer will ever trust. Instead we should be working on artificial stupidity. Sometimes the less lofty goals are the ones that turn out to be most useful in the end.
My company, Radar Networks, has just come out of stealth. We've announced what we've been working on all these years: It's called Twine.com. We're going to be showing Twine publicly for the first time at the Web 2.0 Summit tomorrow. There's lot's of press coming out where you can read about what we're doing in more detail. The team is extremely psyched and we're all working really hard right now so I'll be brief for now. I'll write a lot more about this later.
A very cool experiment in virtual reality has shown it is possible to trick the mind into identifying with a virtual body:
Through these goggles, the volunteers could see a camera view of their own back - a three-dimensional "virtual own body" that appeared to be standing in front of them.
When the researchers stroked the back of the volunteer with a pen, the volunteer could see their virtual back being stroked either simultaneously or with a time lag.
The volunteers reported that the sensation seemed to be caused by the pen on their virtual back, rather than their real back, making them feel as if the virtual body was their own rather than a hologram.
Volunteers
Even when the camera was switched to film the back of a mannequin being stroked rather than their own back, the volunteers still reported feeling as if the virtual mannequin body was their own.
And when the researchers switched off the goggles, guided the volunteers back a few paces, and then asked them to walk back to where they had been standing, the volunteers overshot the target, returning nearer to the position of their "virtual self".
This has implications for next-generation video games and virtual reality. It also has interesting implications for consciousness studies in general.
I just heard about a very interesting new discovery in neuroscience:. The basic gist is that it appears that axons process information. Until now it has been thought that only the cell body of neurons was the part that processed information. Our present understanding of the brain, and also of psychopharmacology, is based completely on the dendrites and main body of the neuron. If it turns out that axons -- the "wires" that connect neurons -- are actually major contributors to how the brain computes, then it may point to both a new understanding of cognition, as well as a new frontier in treating mental and neurological disorders. (Thanks to Bram for letting me know).
I've been thinking for several years about Knowledge Networking. It's not a term I invented, it's been floating around as a meme for at least a decade or two. But recently it has started to resurface in my own work.
So what is a knowledge network? I define a knowledge network as a form of collective intelligence in which a network of people (two or more people connected by social-communication relationships) creates, organizes, and uses a collective body of knowledge. The key here is that a knowledge network is not merely a site where a group of people work on a body of information together (such as the wikipedia), it's also a social network -- there is an explicit representation of a social relationship within it. So it's more like a social network than for example a discussion forum or a wiki.
I would go so far as to say that knowledge networks are the third-generation of social software. (Note this is based in-part on ideas that emerged in conversations I have had with Peter Rip, so this also his idea):
Just some thoughts on a Saturday morning...
Web 3.0 -- aka The Semantic Web -- is about enriching the connections of the Web. By enriching the connections within the Web, the entire Web may become smarter.
I believe that collective intelligence primarily comes from connections -- this is certainly the case in the brain where the number of connections between neurons far outnumbers the number of neurons; certainly there is more "intelligence" encoded in the brain's connections than in the neurons alone. There are several kinds of connections on the Web:
Are there other kinds of connections that I haven't listed -- please let me know!
I believe that the Semantic Web can actually enrich all of these types of connections, adding more semantics not only to the things being connected (such as representations of information or people or apps) but also to the connections themselves.
In the Semantic Web approach, connections are represented with statements of the form (subject, predicate, object) where the elements have URIs that connect them to various ontologies where their precise intended meaning can be defined. These simple statements are sometimes called "triples" because they have three elements. In fact, many of us are working with statements that have more than three elements ("tuples"), so that we can represent not only subject, predicate, object of statements, but also things like provenance (where did the data for the statement come from?), timestamp (when was the statement made), and other attributes. There really is no limit to what kind of metadata can be stored in these statements. It's a very simple, yet very flexible and extensible data model that can represent any kind of data structure.
The important point for this article however is that in this data model rather than there being just a single type of connection (as is the case on the present Web which basically just provides the HREF hotlink, which simply means "A and B are linked" and may carry minimal metadata in some cases), the Semantic Web enables an infinite range of arbitrarily defined connections to be used. The meaning of these connections can be very specific or very general.
For example one might define a type of connection called "friend of" or a type of connection called "employee of" -- these have very different meanings (different semantics) which can be made explicit and also machine-readable using OWL. By linking a page about a person with the "employee of" link to another page about a different person, we can express that one of them employs the other. That is a statement that any application which can read OWL is able to see and correctly interpret, by referencing the underlying definition of "employee of" which is defined in some ontology and might for example specify that an "employee of" relation connects a person to a person or organization who is their employer. In other words, rather than just linking things with the generic "hotlink" we are all used to, they can now be linked with specific kinds of links that have very particular and unambiguous meaning and logical implications.
This has the potential at least to dramatically enrich the information-carrying capacity of connections (links) on the Web. It means that connections can carry more meaning, on their own. It's a new place to put meaning in fact -- you can put meaning between things to express their relationships. And since connections (links) far outnumber objects (information, people or applications) on the Web, this means we can radically improve the semantics of the structure of the Web as a whole -- the Web can become more meaningful, literally. This makes a difference, even if all we do is just enrich connections between gross-level objects (in other words, connections between Web pages or data records, as opposed to connections between concepts expressed within them, such as for example, people and companies mentioned within a single document).
Even if the granularity of this improvement in connection technology is relatively gross level it could still be a major improvement to the Web. The long-term implications of this have hardly been imagined let alone understood -- it is analogous to upgrading the dendrites in the human brain; it could be a catalyst for new levels of computation and intelligence to emerge.
It is important to note that, as illustrated above, there are many types of connections that involve people. In other words the Semantic Web, and Web 3.0, are just as much about people as they are about other things. Rather than excluding people, they actually enrich their relationships to other things. The Semantic Web, should, among other things, enable dramatically better social networking and collaboration to take place on the Web. It is not only about enriching content.
Now where will all these rich semantic connections come from? That's the billion dollar question. Personally I think they will come from many places: from end-users as they find things, author content, bookmark content, share content and comment on content (just as hotlinks come from people today), as well as from applications which mine the Web and automatically create them. Note that even when Mining the Web a lot of the data actually still comes from people -- for example, mining the Wikipedia, or a social network yields lots of great data that was ultimately extracted from user-contributions. So mining and artificial intelligence does not always imply "replacing people" -- far from it! In fact, mining is often best applied as a means to effectively leverage the collective intelligence of millions of people.
These are subtle points that are very hard for non-specialists to see -- without actually working with the underlying technologies such as RDF and OWL they are basically impossible to see right now. But soon there will be a range of Semantically-powered end-user-facing apps that will demonstrate this quite obviously. Stay tuned!
Of course these are just my opinions from years of hands-on experience with this stuff, but you are free to disagree or add to what I'm saying. I think there is something big happening though. Upgrading the connections of the Web is bound to have a significant effect on how the Web functions. It may take a while for all this to unfold however. I think we need to think in decades about big changes of this nature.
If you are interested in the future of the Web, you might enjoy listening to this interview with me, moderated by Dr. Paul Miller of Talis. We discuss, in-depth: the Semantic Web, Web 3.0, SPARQL, collective intelligence, knowledge management, the future of search, triplestores, and Radar Networks.
We had a bunch of press hits today for my startup, Radar Networks...
PC World Article on Web 3.0 and Radar Networks
Entrepreneur Magazine interview
We're also proud to announce that Jim
Hendler, one of the founding gurus of the Semantic Web, has joined our technical advisory board.
I've been thinking since 1994 about how to get past a fundamental barrier to human social progress, which I call "The Collective IQ Barrier." Most recently I have been approaching this challenge in the products we are developing at my stealth venture, Radar Networks.
In a nutshell, here is how I define this barrier:
The Collective IQ Barrier: The potential collective intelligence of a human group is exponentially proportional to group size, however in practice the actual collective intelligence that is achieved by a group is inversely proportional to group size. There is a huge delta between potential collective intelligence and actual collective intelligence in practice. In other words, when it comes to collective intelligence, the whole has the potential to be smarter than the sum of its parts, but in practice it is usually dumber.
Why does this barrier exist? Why are groups generally so bad at tapping the full potential of their collective intelligence? Why is it that smaller groups are so much better than large groups at innovation, decision-making, learning, problem solving, implementing solutions, and harnessing collective knowledge and intelligence?
I think the problem is technological, not social, at its core. In this article I will discuss the problem in more depth and then I will discuss why I think the Semantic Web may be the critical enabling technology for breaking through the Collective IQ Barrier.
Continue reading "Breaking the Collective IQ Barrier -- Making Groups Smarter" »
Here at Radar Networks we are working on practical ways to bring the Semantic Web to end-users. One of the interesting themes that has come up a lot, both internally, as well as in discussions with VC's, is the coming plateau in the productivity of keyword search. As the Web gets increasingly large and complex, keyword search becomes less effective as a means for making sense of it. In fact, it will even decline in productivity in the future. Natural language search will be a bit better than keyword search, but ultimately won't solve the problem either -- because like keyword search it cannot really see or make use of the structure of information.
I've put together a new diagram showing how the Semantic Web will enable the next step-function in productivity on the Web. It's still a work in progress and may change frequently for a bit, so if you want to blog it, please link to this post, or at least the .JPG image behind the thumbnail below so that people get the latest image. As always your comments are appreciated. (Click the thumbnail below for a larger version).
Today a typical Google search returns up to hundreds of thousands or even millions of results -- but we only really look at the first page or two of results. What about the other results we don't look at? There is a lot of room to improve the productivity of search, and the help people deal with increasingly large collections of information.
Keyword search doesn't understand the meaning of information, let alone its structure. Natural language search is a little better at understanding the meaning of information -- but it still won't help with the structure of information. To really improve productivity significantly as the Web scales, we will need forms of search that are data-structure-aware -- that are able to search within and across data structures, not just unstructured text or semistructured HTML. This is one of the key benefits of the coming Semantic Web: it will enable the Web to be navigated and searched just like a database.
Starting with the "data web" enabled by RDF, OWL, ontologies and SPARQL, structured data is becoming increasingly accessible, searchable and mashable. This in turn sets the stage for a better form of search: semantic search. Semantic search combines the best of keyword, natural language, database and associative search capabilities together.
Without the Semantic Web, productivity will plateau and then gradually decline as the Web, desktop and enterprise continue to grow in size and complexity. I believe that with the appropriate combination of technology and user-experience we can flip this around so that productivity actually increases as the size and complexity of the Web increase.
See Also: A Visual Timeline of the Past, Present and Future of the Web
Thanks to Bram for pointing me to this article about how new research indicates that communication in the brain is quite different than we thought. Essentially neurons may release neurotransmitters all along axons, not just within synapses. This may enable new forms of global communication or state changes within the brain, beyond the "circuit model" of neuronal signaling that has been the received view for the last 100 years. It also may open up a wide range of new drugs and discoveries in brain science.
Another article of note on the subject of our evolving digital lives and what user-experience designers should be thinking about:
Our lives are becoming increasingly digitized—from the ways we communicate, to our entertainment media, to our e-commerce transactions, to our online research. As storage becomes cheaper and data pipes become faster, we are doing more and more online—and in the process, saving a record of our digital lives, whether we like it or not.
(snip...)
In the coming years, our ability to interact with the information we’re so rapidly generating will determine how successfully we can manage our digital lives. There is a great challenge at our doorsteps—a shift in the way we live with each other.
As designers of user experiences for digital products and services, we can make people’s digital lives more meaningful and less confusing. It is our responsibility to envision not only techniques for sorting, ordering, and navigating these digital information spaces, but also to devise methods of helping people feel comfortable with such interactions. To better understand and ultimately solve this information management problem, we should take a holistic view of the digital person. While our data might be scattered, people need to feel whole.
Nice article in Scientific American about Gordon Bell's work at Microsoft Research on the MyLifeBits project. MyLifeBits provides one perspective on the not-too-far-off future in which all our information, and even some of our memories and experiences, are recorded and made available to us (and possibly to others) for posterity. This is a good application of the Semantic Web -- additional semantics within the dataset would provide many more dimensions to visualize, explore and search within, which would help to make the content more accessible and grokkable.
Google's Larry Page recently gave a talk to the AAAS about how Google is looking towards a future in which they hope to implement AI on a massive scale. Larry's idea is that intelligence is a function of massive computation, not of "fancy whiteboard algorithms." In other words, in his conception the brain doesn't do anything very sophisticated, it just does a lot of massively parallel number crunching. Each processor and its program is relatively "dumb" but from the combined power of all of them working together "intelligent" behaviors emerge.
Larry's view is, in my opinion, an oversimplification that will not lead to actual AI. It's certainly correct that some activities that we call "intelligent" can be reduced to massively parallel simple array operations. Neural networks have shown that this is possible -- they excel at low level tasks like pattern learning and pattern recognition for example. But neural networks have not proved capable of higher level cognitive tasks like mathematical logic, planning, or reasoning. Neural nets are theoretically computationally equivalent to Turing Machines, but nobody (to my knowledge) has ever succeeded in building a neural net that can in practice even do what a typical PC can do today -- which is still a long way short of true AI!
Somehow our brains are capable of basic computation, pattern detection and learning, simple reasoning, and advanced cognitive processes like innovation and creativity, and more. I don't think that this richness is reducible to massively parallel supercomputing, or even a vast neural net architecture. The software -- the higher level cognitive algorithms and heuristics that the brain "runs" -- also matter. Some of these may be hard-coded into the brain itself, while others may evolve by trial-and-error, or be programmed or taught to it socially through the process of education (which takes many years at the least).
Larry's view is attractive but decades of neuroscience and cognitive science have shown conclusively that the brain is not nearly as simple as we would like it to be. In fact the human brain is far more sophisticated than any computer we know of today, even though we can think of it in simple terms. It's a highly sophisticated system comprised of simple parts -- and actually, the jury is still out on exactly how simple the parts really are -- much of the computation in the brain may be sub-neuronal, meaning that the brain may actually a much much more complex system than we think.
Perhaps the Web as a whole is the closest analogue we have today for the brain -- with millions of nodes and connections. But today the Web is still quite a bit smaller and simpler than a human brain. The brain is also highly decentralized and it is doubtful than any centralized service could truly match its capabilities. We're not talking about a few hundred thousand linux boxes -- we're talking about hundreds of billions of parallel distributed computing elements to model all the neurons in a brain, and this number gets into the trillions if we want to model all the connections. The Web is not this big, and neither is Google.
Check out this very impressive user-interface prototype for a desktop that works more like a real desk -- a messy desk in fact. Very delightful design work that makes want to use it now!
Read this fun article that lists and defines some of the key concepts that every post-singularity transhumanist meta-intellectual should know! (via Kurzweil)
NOTES
Prelude
Many years ago, in the late 1980s, while I was still a college student, I visited my late grandfather, Peter F. Drucker, at his home in Claremont, California. He lived near the campus of Claremont College where he was a professor emeritus. On that particular day, I handed him a manuscript of a book I was trying to write, entitled, "Minding the Planet" about how the Internet would enable the evolution of higher forms of collective intelligence.
My grandfather read my manuscript and later that afternoon we sat together on the outside back porch and he said to me, "One thing is certain: Someday, you will write this book." We both knew that the manuscript I had handed him was not that book, a fact that was later verified when I tried to get it published. I gave up for a while and focused on college, where I was studying philosophy with a focus on artificial intelligence. And soon I started working in the fields of artificial intelligence and supercomputing at companies like Kurzweil, Thinking Machines, and Individual.
A few years later, I co-founded one of the early Web companies, EarthWeb, where among other things we built many of the first large commercial Websites and later helped to pioneer Java by creating several large knowledge-sharing communities for software developers. Along the way I continued to think about collective intelligence. EarthWeb and the first wave of the Web came and went. But this interest and vision continued to grow. In 2000 I started researching the necessary technologies to begin building a more intelligent Web. And eventually that led me to start my present company, Radar Networks, where we are now focused on enabling the next-generation of collective intelligence on the Web, using the new technologies of the Semantic Web.
But ever since that day on the porch with my grandfather, I remembered what he said: "Someday, you will write this book." I've tried many times since then to write it. But it never came out the way I had hoped. So I tried again. Eventually I let go of the book form and created this weblog instead. And as many of my readers know, I've continued to write here about my observations and evolving understanding of this idea over the years. This article is my latest installment, and I think it's the first one that meets my own standards for what I really wanted to communicate. And so I dedicate this article to my grandfather, who inspired me to keep writing this, and who gave me his prediction that I would one day complete it.
This is an article about a new generation of technology that is sometimes called the Semantic Web, and which could also be called the Intelligent Web, or the global mind. But what is the Semantic Web, and why does it matter, and how does it enable collective intelligence? And where is this all headed? And what is the long-term far future going to be like? Is the global mind just science-fiction? Will a world that has a global mind be good place to live in, or will it be some kind of technological nightmare?
Continue reading "Minding The Planet -- The Meaning and Future of the Semantic Web" »
A Harvard University researcher believes that moral judgement is hard-wired into the brain:
The moral grammar now universal among people presumably evolved to its final shape during the hunter-gatherer phase of the human past, before the dispersal from the ancestral homeland in northeast Africa some 50,000 years ago. This may be why events before our eyes carry far greater moral weight than happenings far away, Dr. Hauser believes, since in those days one never had to care about people remote from ones environment.
Dr. Hauser believes that the moral grammar may have evolved through the evolutionary mechanism known as group selection. A group bound by altruism toward its members and rigorous discouragement of cheaters would be more likely to prevail over a less cohesive society, so genes for moral grammar would become more common.
New research seems to indicate that memory loss may be related to common viral infections that cross the blood-brain barrier and chip away at cognitive function. Over a person's lifetime, after two or three of these infections a year, it starts to add up to significant memory loss.
All living things are made up of proteins. Each protein is a string of amino acids. There are 20 different amino acids, and each protein can consist of dozens to thousands of them.
Scientists write down these amino acid sequences as series of text letters. Clark and her colleagues assign musical notes to the different values of the amino acids in each sequence. The result is music in the form of "protein songs."
By listening to the songs, scientists and students alike can hear the structure of a protein. And when the songs of the same protein from different species are played together, their similarities and differences are apparent to the ear.
"It's an illustration transferred into a medium people will find more accessible than just [text] sequences," Clark said. "If you look at protein sequences, if you just read those as they are written down, recorded in a database, it's hard to get a sense for the pattern."
When people look at a page full of text corresponding to protein sequences, Clark explained, they tend spot clusters of letters but fail to see the larger pattern.
"If you play [the protein song for that sequence] you get that sense of the pattern much more strongly," she said. "That's my feeling at least. You hear stuff you can't see."
From National Geographic
This is a surprisingly good article on the nature of consciousness -- providing a survey of the current state-of-the-art in cognitive science research. It covers the question from a number of perspectives and interviews many of the leading current researchers.
Below is the text of my bet on Long Bets. Go there to vote.
"By 2050 no synthetic computer nor machine intelligence will have become truly self-aware (ie. will become conscious)."
Spivack's Argument:
(This summary includes my argument, a method for judging the outcome of this bet and some other thoughts on how to measure awareness...)
A. MY PERSPECTIVE...
Even if a computer passes the Turing Test it will not really be aware that it has passed the Turing Test. Even if a computer seems to be intelligent and can answer most questions as well as an intelligent, self-aware, human being, it will not really have a continuum of awareness, it will not really be aware of what it seems to "think" or "know," it will not have any experience of it's own reality or being. It will be nothing more than a fancy inanimate object, a clever machine, it will not be a truly sentient being.
Self-awareness is not the same thing as merely answering questions intelligently. Therefore even if you ask a computer if it is self-aware and it answers that it is self-aware and that it has passed the Turing Test, it will not really be self-aware or really know that it has passed the Turing Test.
As John Searle and others have pointed out, the Turing Test does not actually measure awareness, it just measures information processing---particularly the ability to follow rules or at least imitate a particular style of communication. In particular it measures the ability of a computer program to imitate humanlike dialogue, which is different than measuring awareness itself. Thus even if we succeed in creating good AI, we won't necessarily succeed in creating AA ("Artificial Awareness").
But why does this matter? Because ultimately, real awareness may be necessary to making an AI that is as intelligent as a human sentient being. However, since AA is theoretically impossible in my opinion, truly self-aware AI will never be created and thus no AI will ever be as intelligent as a human sentient being even if it manages to fool someone into thinking it is (and thus passing the Turing Test).
This study is strange. But plausible.
Today, Cornell University researchers are reporting what appears to be a statistically significant relationship between autism rates and television watching by children under the age of 3. The researchers studied autism incidence in California, Oregon, Pennsylvania, and Washington state. They found that as cable television became common in California and Pennsylvania beginning around 1980, childhood autism rose more in the counties that had cable than in the counties that did not. They further found that in all the Western states, the more time toddlers spent in front of the television, the more likely they were to exhibit symptoms of autism disorders.
From: Slate
This article discusses an interesting fact -- some women have extra color receptors enabling them to distinguish a vastly larger range of colors than everyone else. Instead of seeing in 3 colors, they see in 4 -- enabling them to tell the difference between 100 million different colors.
Wow...
A severely brain-damaged woman in an unresponsive, vegetative state showed clear signs of conscious awareness on brain imaging tests, researchers are reporting today, in a finding that could have far-reaching consequences for how unconscious patients are cared for and diagnosed.
In response to commands, the patient’s brain flared with activity, lighting the same language and planning regions that are active when healthy people hear the commands. Previous studies had found similar activity in partly conscious patients, who occasionally respond to commands, but never before in someone who was totally
This opens up a whole new range of possibilities. For example, what if there was a way to fit a comatose patient with a brain activity sensor that could enable them to think of certain things in order to trigger things in their environment? For example, suppose that the woman above could think of playing tennis and that would cause the radio to turn on or off in her hospital room? Similarly, if she thought about moving around her house, suppose that could alert a nurse that she needed pain medication or to be repositioned, etc.? This could provide a way for comatose people to communicate with their caregivers and have some control over their environments. It might even be possible to teach them things to think about in order to indicate "yes" and "no" answers to questions. So someone could ask them questions about what they experience and they could answer yes or no. It might even be possible to teach them to communicate letters so they could spell out messages.
The whole premise that a comatose person has no conscious awareness or sensation may be overturned by this. Perhaps they are much more aware than we thought but they are simply unable to control their bodies in order to speak or move? If that is the case, they must be desperate for a way to communicate and this could be the answer.
This is a cool pair of images showing a striking similarity between the structure of neurons and that of our universe. I've often wondered whether the entire universe isn't some kind of a mind or a brain in which we are like subatomic particles.
Check out The Broth -- it's a "global mosaic" in which you can move tiles around in real time with other people to create emergent artworks. It's really cool to watch images grow and morph from the combined imagination of people around the Net. Beautiful.
US military researchers are working on devices that augment human sensory perception, through the tongue:
By routing signals from helmet-mounted cameras, sonar and other equipment through the tongue to the brain, they hope to give elite soldiers superhuman senses similar to owls, snakes and fish.
My father, Mayer Spivack, has written an interesting piece on managing thinking styles in organizations. He points out the difference between the thinking styles in early and later stage companies, and the challenge of managing and integrating these two aspects of the organization's cognitive process. I think that the syncretic-associative mode (curious, inventive, exploratory, enthusiastic, adventurous) tends to be more externally focused, whereas the linear-logical mode tends to be more internally focused (careful, reductivist, analyticial, skeptical, habitual). You could say this is the difference between an organization being extraverted or introverted, and the challenge is for organizations to evolve balanced personalities. This could be an interesting way to approach management consulting -- and I wouldn't be surprised if there are others thinking about organizations in these terms.
The Syncretic Management Process
Understanding The Value Of Associative Thinking In A World Of Linear Decision-MakingDecisions and communications among individuals in organizations are frequently initiated, managed and concluded almost entirely from within a framework of linear-logical thinking. Paradoxically, the products and services comprising the intellectual property and capital creative upon which most business are founded owe their existence to a non-linear, but nonetheless logical, syncretic process of associative thinking. Syncretic thinking is a mental process that makes non-linear, and therefore often unexpected, connections among seemingly divergent phenomena or data on the basis of common qualities.
By understanding this paradox between the creative syncretic process characterizing the founding stage of an organization, and the conservative linear processes that characterize later stages we can generate a new mix of creative thinking that effectively includes both elements. These two modes of thought highlight several differences between the mind-sets that typify the young innovative start-up phase of a business compared with that same business at a later more mature phase, settled into it’s niche. The associative and inventive thinking that generated a novel product or service and founded an organization or industry may, at maturity, have yielded to a more rigorous calculus of risk, competition and strategic analysis. In this later phase of organization, linear frameworks of thinking that tend to conserve capital and to advance the organizations goals incrementally within an established niche are strongly reinforced and rewarded. Thus linearity, alone, is widely believed to be essential for survival. However, neither framework in isolation is likely to encourage the growth of new ideas that may form the future of the organization. Nor could an organization develop far beyond the initial concept stage without the benefit of both modalities operating together.
New research into the mathematical properties of whale songs reveals that they have a complex language:
The songs of the humpback whale are among the most complex in the animal kingdom. Researchers have now mathematically confirmed that whales have their own syntax that uses sound units to build phrases that can be combined to form songs that last for hours.
Until now, only humans have demonstrated the ability to use such a hierarchical structure of communication. The research, published online in the March 2006 issue of the Journal of the Acoustical Society of America, offers a new approach to studying animal communication, although the authors do not claim that humpback whale songs meet the linguistic rigor necessary for a true language.
"Humpback songs are not like human language, but elements of language are seen in their songs," said Ryuji Suzuki, a Howard Hughes Medical Institute (HHMI) predoctoral fellow in neuroscience at Massachusetts Institute of Technology and first author of the paper.
This research is important because it brings us one step closer to someday being able to decode whalesongs and eventually even communicate with whales. In the long-term it may also contribute to the development of general techniques for interspecies language translation -- techniques that could someday come in handy if and when we start to interact with extraterrestrial species.
Researchers continue to make progress in fusing living neurons with computer chips:
The line between living organisms and machines has just become a whole lot blurrier. European researchers have developed "neuro-chips" in which living brain cells and silicon circuits are coupled together.
The achievement could one day enable the creation of sophisticated neural prostheses to treat neurological disorders or the development of organic computers that crunch numbers using living neurons.
To create the neuro-chip, researchers squeezed more than 16,000 electronic transistors and hundreds of capacitors onto a silicon chip just 1 millimeter square in size.
They used special proteins found in the brain to glue brain cells, called neurons, onto the chip. However, the proteins acted as more than just a simple adhesive.
"They also provided the link between ionic channels of the neurons and semiconductor material in a way that neural electrical signals could be passed to the silicon chip," said study team member Stefano Vassanelli from the University of Padua in Italy.
The proteins allowed the neuro-chip's electronic components and its living cells to communicate with each other. Electrical signals from neurons were recorded using the chip's transistors, while the chip's capacitors were used to stimulate the neurons.
From: http://www.livescience.com/humanbiology/060327_neuro_chips.html
Today I read an interesting article in the New York Times about a company called Rite-Solutions which is using a home-grown stock market for ideas to catalyze bottom-up innovation across all levels of personnel in their organization. This is a way to very effectively harness and focus the collective creativity and energy in an organization around the best ideas that the organization generates.
Using virtual stock market systems to measure community sentiment is not a new concept but it is a new frontier. I don't think we've even scratched the surface of what this paradigm can accomplish. For lots of detailed links to resources on this topic see the wikipedia entry on prediction markets. This prediction markets portal also has collected interesting links on the topic. Here is an informative blog post about recent prediction market attempts. Here is a scathing critique of some prediction markets.
There are many interesting examples of prediction markets on the Web:
Here are some interesting, more detailed discussions of prediction market ideas and potential features.
Another area that is related, but highly underleveraged today, are ways to enable communities to help establish whether various ideas are correct using argumentation. By enabling masses of people to provide reasons to agree or disagree with ideas, and with those reasons as well, we can automatically rate what ideas are most agreed with or disagreed with. One very interesting example of this is TruthMapping.com. Some further concepts related to this approach are discussed in this thread.
Introduction:
This article proposes the creation of a new open, nonprofit service on the Web
that will provide something akin to “collective self-awareness” back to the
Web. This service is like a "Google Zeitgeist" on steroids, but with a
lot more real-time, interactive, participatory data, technology and features in
it. The goal is to measure and visualize the state of the collective mind of
humanity, and provide this back to humanity in as close to real-time as is possible,
from as many data sources as we can handle -- as a web service.
By providing this service, we will enable higher levels of collective intelligence to emerge and self-organize on the Web. The key to collective intelligence (or any intelligence in fact) is self-awareness. Self-awareness is, in essence, a feedback loop in which a system measures its own internal state and the state of its environment, then builds a representation of that state, and then reasons about and reacts to that representation in order to generate future behavior. This feedback loop can be provided to any intelligent system -- even the Web, even humanity as-a-whole. If we can provide the Web with such a service, then the Web can begin to “see itself” and react to its own state for the first time. And this is the first step to enabling the Web, and humanity as-a-whole, to become more collectively intelligent.
It should be noted that by "self-awareness" I don’t mean consciousness or sentience – I think that the consciousness comes from humans at this point and we are not trying to synthesize it (we don't need to; it's already there). Instead, by "self-awareness" I mean a specific type of feedback loop -- a specific Web service -- that provides a mirror of the state of the whole back to its parts. The parts are the conscious elements of the system – whether humans and/or machines – and can then look at this meta-mirror to understand the whole as well as their place in it. By simply providing this meta-level mirror, along with ways that the individual parts of the system can report their state to it, and get the state of the whole back from it, we can enable a richer feedback loop between the parts and the whole. And as soon as this loop exists the entire system suddenly can and will become much more collectively intelligent.
What I am proposing is something quite common in artificial intelligence. For example, in the field of robotics, such as when building an autonomous robot. Until a robot is provided with a means by which it can sense its own internal state and the state of its nearby environment, it cannot behave intelligently or very autonomously. But once this self-representation and feedback loop is provided, it can then react to it’s own state and environment and suddenly can behave far more intelligently. All cybernetic systems rely on this basic design pattern. I’m simply proposing we implement something like this for the entire Web and the mass of humanity that is connected to it. It's just a larger application of an existing pattern. Currently people get their views of “the whole” from the news media and the government – but these views suffer from bias, narrowness, lack of granularity, lack of real-time data, and the fact that they are one-way, top-down services with no feedback loop capabilities. Our global collective self-awareness -- in order to be truly useful and legitimate really must be two-way, inclusive, comprehensive, real-time and democratic. In the global collective awareness, unlike traditional media, the view of the whole is created in a bottom-up, emergent fashion from the sum of the reports from all the parts (instead of just a small pool of reporters or publishers, etc.).
The system I envision would visualize the state of the global mind on a number of key dimensions, in real-time, based on what people and software and organizations that comprise its “neurons” and “regions” report to it (or what it can figure out by mining artifacts they create). For example, this system would discover and rank the current most timely and active topics, current events, people, places, organizations, events, products, articles, websites, in the world right now. From these topics it would link to related resources, discussions, opinions, etc. It would also provide a real-time mass opinion polling system, where people could start polls, vote on them, and see the results in real-time. And it would provide real-time statistics about the Web, the economy, the environment, and other key indicators.
The idea is to try to visualize the global mind – to make it concrete and real for people, to enable them to see what it is thinking, what is going on, and where they fit in it – and to enable them to start adapting and guiding their own behavior to it. By giving the parts of the system more visibility into the state of the whole, they can begin to self-organize collectively which in turn makes the whole system function more intelligently
Essentially I am proposing the creation of the largest and most sophisticated mirror ever built – a mirror that can reflect the state of the collective mind of humanity back to itself. This will enable an evolutionary process which eventually will result in humanity becoming more collectively self-aware and intelligent as-a-whole (instead of what it is today -- just a set of separeate interacting intelligent parts). By providing such a service, we can catalyze the evolution of higher-order meta-intelligence on this planet -- the next step in human evolution. Creating this system is a grand cultural project of profound social value to all people on earth, now and in the future.
This proposal calls for creating a nonprofit orgnaization to build and host this service as a major open-source initiative on the Web, like the Wikipedia, but with a very different user-experience and focus. It also calls for implementing the system with a hybrid central and distributed architecture. Although this vision is big, the specific technologies, design patterns, and features that are necessary to implement it are quite specific and already exist. They just have to be integrated, wrapped and rolled out. This will require an extraordinary and multidisciplanary team. If you're interested in getting involved and think you can contribute resources that this project will need, let me know (see below for details).
Further Thoughts
Today I re-read this beautiful, visionary article by Kevin Kelley, about the birth of the global mind, in which he states:
Kevin's article got me thinking once again about an idea that has been on my mind for over a decade. I have often thought that the Web is growing into the collective nervous system of our species. This will in turn enable the human species to function increasingly as an intelligent superorganism, for example, like a beehive, or an ant colony -- but perhaps even more intelligent. But the key to bringing this process about is self-awareness. In short, the planetary supermind cannot become truly intelligent until it evolves a form of collective self-awareness. Self-awareness is the most critical component of human intelligence -- the sophistication of human self-awareness is what makes humans different from dumb machines, and from less intelligent species.
The Big Idea that I have been thinking about for over a decade is that if we can build something that functions like a collective self-awareness, then this could catalyze a huge leap in collective intelligence that would essentially "wake up" the global supermind and usher in a massive evolution in its intelligence and behavior. As the planetary supermind becomes more aware of its environment, its own state, and its own actions and plans, it will then naturally evolve higher levels of collective intelligence around this core. This evolutionary leap is of unimaginable importance to the future of our species.
In order for the collective mind to think and act more intelligently it must be able to sense itself and its world, and reason about them, with more precision -- it must have a form of self-awareness. The essence of self-awareness is self-representation -- the ability to sense, map, reason about, and react to, one's own internal state and the state of one's nearby environment. In other words, self-awareness is a feedback loop by which a system measures and reacts to its own self-representations. Just as is the case with the evolution of individual human intelligence, the evolution of more sophisticated collective human intelligence will depend on the emergence of better collective feedback loops and self-representations. By enabling a feedback loop in which information can flow in both directions between the self-representations of individuals and a meta-level self-representation for the set of all individuals, the dynamics of the parts and the whole become more closely coupled. And when this happens, the system can truly start to adapt to itself intelligently, as a single collective intelligence instead of a collection of single intelligences.
In summary, in order to achieve higher levels of collective intelligence and behavior, the global mind will first need something that functions as its collective self-awareness -- something that enables the parts to better sense and react to the state of the whole, and the whole to better sense and react to the state of its parts. What is needed essentially is something that functions as a collective analogue to a self -- a global collective self.
Think of the global self as a vast mirror, reflecting the state of the global supermind back to itself. Mirrors are interesting things. At first they merely reflect, but soon they begin to guide decisionmaking. By simply providing humanity with a giant virtual mirror of what is going on across the minds of billions of individuals, and millions of groups and organizations, the collective mind will crystallize, see itself for the first time, and then it will begin to react to its own image. And this is the beginning of true collective cognition. When the parts can see themselves as a whole and react in real-time, then they begin to function as a whole instead of just a collection of separate parts. As this shift transpires the state of the whole begins to feedback into the behavior of the parts, and the state of the parts in turns feeds back to the state of the whole. This cycle of bidirectional feedback between the parts and whole is the essence of cognition in all intelligent systems, whether individual brains, artificial intelligences, or entire worlds.
I believe that the time has come for this collective self to emerge on our planet. Like a vast virtual mirror, it will function as the planetary analogue to our own individual self-representations -- that capacity of our individual minds which represents us back to ourselves. It will be comprised of maps that combine real-time periodic data updates, and historical data, from perhaps trillions of data sources (one for each person, group, organization and software agent on the grid). The resulting visualizations will be something like a vast fluid flow, or a many particle simulation. It will require a massive computing capability to render it -- perhaps a distributed supercomputer comprised of the nodes on the Web themselves, each hosting a part of the process. It will require new thinking about how to visualize trends in such vast amounts of data and dimensions. This is a great unexplored frontier in data visualization and knowledge discovery.
How It Might Work
I envision the planetary self functioning as a sort of portal -- a Web service that aggregates and distributes all kinds of current real-time and historical data about the state of the whole, as well as its past states and future projected states. This portal would collect opinions, trends, and statistics about the human global mind, the environment, the economy, society, geopolitical events, and other indicators, and would map them graphically in time, geography, demography, and subject space -- enabling everyone to see and explore the state of the global mind from different perspectives, with various overlays, and at arbitrary levels of magnification.
I think this system should provide an open data model, and open API for adding and growing data sets, querying, remixing, visualizing, and subscribing to the data. All services that provide data sets, analysis or visualizations (or other interpretations) of potential value to understanding the state of the whole would be able to post data into our service for anyone to find and use. Search engines could post in the top search query terms. Sites that create tag clouds could post in tags and tag statistics. Sites that analyze the blogosphere could post in statistics about blogs, bloggers, and blog posts. Organizations that do public opinion polling, market and industry research, trend analysis, social research, or economic research could post in statistics they are generating. Academic researchers could post in statistics generated by projects they are doing to analyze trends on the Web, or within our data-set itself.
As data is pushed to us, or pulled by us, we would grow the largest central data repository about the state of the whole. Others could then write programs to analyze and remix our data, and then post their results back into the system for others to use as well. We would make use of our data for our own analysis, but anyone else could also do research and share their analysis through our system. End users and others could also subscribe to particular data, reports, or visualizations from our service, and could post in their own individual opinions, attention data feeds, or other inputs. We would serve as a central hub for search, analysis, and distribution of collective self-awareness.
The collective self would provide a sense of collective identity: who are we, how do we appear, what are we thinking about, what do we think about what we are thinking about, what are we doing, how well are we doing it, where are we now, where have we been, where are we going next. Perhaps it could be segmented by nation, or by age group, or by other dimensions as well to view various perspectives on these questions within it. It could gather its data by mining for it, as well as through direct push contributions from various data-sources. Individuals could even report on their own opinions, state, and activities to it if they wanted to, and these votes and data points would be reflected back in the whole in real time. Think of it as a giant emergent conversation comprised of trillions of participants, all helping to make sense of the same subject -- our global self identity -- together. It could even have real-time views that are animated and alive -- like a functional brain image scan -- so that people could see the virtual neurons and pathways in the global brain firing as they watch.
If this global self-representation existed, I would want to subscribe to it as a data feed on my desktop. I would want to run it in a dashboard in the upper right corner of my monitor -- that I could expand at any time to explore further. It would provide me with alerts when events transpired that matched my particular interests, causes, or relationships. It would solicit my opinions and votes on issues of importance and interest to me. It would simultaneously function as my window to the world, and the world's window to me. It would be my way of participating in the meta-level whole, whenever I wanted to. I could tell it my opinions about key issues, current events, problems, people, organizations, or even legislative proposals. I could tell it about the quality of life from my perspective, where I am living, in my industry and demographic niche. I could tell it about my hopes and fears for the future. I could tell it what I think is cool, or not cool, interesting or not interesting, good or bad, etc. I could tell it what news I was reading and what I think is noteworthy or important. And it would listen and learn, and take my contributions into account democratically along with those of billions of other people just like me all around the world. From this would emerge global visualizations and reports about what we are all thinking and doing, in aggregate, that I could track and respond to. Linked from these flows I could then find relevant news, conversations, organizations, people, products, services, events, and knowledge. And from all of this would emerge something greater than anything I can yet imagine -- a thought process too big for any one human mind to contain.
I want to build this. I want to build the planetary Self. I am not suggesting that we build the entire global mind, I am just suggesting that we build the part of the system that functions as its collective self-awareness. The rest of the global mind is already there, as raw potential at least, and doesn't have to be built. The Web, human minds, software agents, and organizations already exist. Their collective state just needs to be reflected in a single virtual mirror. As soon as this mirror exists they can begin to collectively self-organize and behave more intelligently, simply because they will have, for the first time, a way of measuring their collective state and behavior. Once there is a central collective self-awareness loop, the intelligence of the global mind will emerge and self-organize naturally over time. This collective self-awareness infrastructure is the central enabling technology that has to be there first for the next-leap in intelligence of the global mind to evolve.
Project Structure
I think this should be created as a non-profit open-source project. In fact, that is the only way that it can have legitimacy -- it must be independent of any government, cultural or commercial perspective. It must be by and for the people, as purely and cleanly as possible. My guess is that to build this properly we would need to create a distributed grid computing system to collect, compute, visualize and distribute the data -- it could be similar to SETI@Home; everyone could help host it. At the center of this grid, or perhaps in a set of supernodes, would be a vast supercomputing array that would manage the grid, do focused computations and data fusion operations. There would also need to be some serious money behind this project as well -- perhaps from major foundations and donors. This system would be a global resource of potential incalculable value to the future of human evolution. It would be a project worth funding.
My Past Writing On This Topic
A Physics of Ideas: Measuring the Physical Properties of Memes
Towards a Worldwide Database
The Metaweb: A Graph of the Future
From Semantic Web to Global Mind
The Birth of the Metaweb
Are Organizations Organisms?
From Application-Centric to Data-Centric Computing
The Human Menome Project
Other Noteworthy Projects
Principia Cybernetica -- the Global Mind Group
The Global Consciousness Project
W3C - The Semantic Web Working Group
Amazon's Mechanical Turk
CHI -- Harnessing Networks of Humans
The Edge has published mini-essays by 119 "big thinkers" on their "most dangerous ideas" -- fun reading.
The history of science is replete with discoveries that were considered socially, morally, or emotionally dangerous in their time; the Copernican and Darwinian revolutions are the most obvious. What is your dangerous idea? An idea you think about (not necessarily one you originated) that is dangerous not because it is assumed to be false, but because it might be true?
I recently read a report of new neuroscience research in which researchers are able to predict what a person will recall by analyzing their brainstate. You can read a summary here.
This reminds me of an idea I had a while back for using biofeedback to guide brainstates, in order to improve memory. Here's a hypothetical experiment that illustrates the idea. Show a person a set of photographs, and while they are observing each photo use functional brain imaging to record their brainstate. Later, show them the same photos several more times and make additional recordings of their brainstate, in order to generate a database of brainstates that correspond to their perception of each photo. Next, select a photo secretly (without telling the human subject) and lookup its corresponding recorded brainstates in the database. Then, guide the human subject to generate a brainstate that corresponds to the secretly chosen photo using biofeedback that is tied to their real-time brainstate. For example, provide the human subject with a sound or a computer image that corresponds to their real-time brainstate, and which provides them with positive or negative feedback based on the "distance" from their present brainstate to the desired target brainstate, enabling them to guide their brainstate the correct configuration. After the subject becomes accustomed to using the biofeedback system, apply it to guide them to generate a brainstate that matches or is closely within range of the desired brainstates for the selected photo. Then ask the subject to report which photo they are thinking of. We can measure how well the method works by the accuracy by which the subject reports thinking of the photo we selected originally.
If this process works it could be used someday as a new kind of memory aid. For example, suppose that someday functional brain imaging gets small and portable, or even wearable or implantable, so that everyone has access to their real-time brainstate data. When they want to "remember" something they simply hit the "record" button on their personal brainstate recorder and it measures their brainstate while they are thinking of and/or perceiving what they want to recall. Then they simply give this dataset a label or filename in their personal memory database. Later when they want to recall a specific thing, they just select the label and the system uses biofeedback to guide them back to generating that brainstate, at which point they can then recall whatever it is they were trying to remember.
A group of computer scientists have come up with a mathematical technique to detect surprising features in dense information streams. They tested their method by comparing it to what human's considered surprising, and the results were... surprisingly good! A mathematical model of surprise could be very useful in next-generation information systems, user-interfaces, situation rooms, and even fighter jet cockpits, for filtering signal from noise and helping to focus attention on what's most important at a given time.
I am playing around with the barely functional live beta of Google Base that just launched. There's not much there, but what I do see is interesting. At the very least this is going to be serious competition for Ning. Beyond that it may compete with Craigslist and other classifieds and events listing services. It's an interesting first step.
But I also see several potential major problems with the approach that Google Base is taking -- in particular there does not seem to be any notion of real semantics under the hood. Is the data at least available as RDF? But even if it is -- how will it be integrated as everyone starts creating their own types? From what I can see, without data type standards, Google Base is likely to develop into billions of non-integrated data record types -- an unuseable "data soup." Searching across these non-normalized records will be next to impossible without an ontology or some form of higher-level data integration. I wonder if the folks at Google have thought this through? At my own startup, Radar Networks, we've spent several years exploring these issues in our own work and in our DARPA work -- all of which is centered around making use of richer semantics in applications. And we've built a working system that makes this much more practical.
We believe that "the world wide database" requires the Semantic Web as its key enabling infrastructure. The technologies of the Semantic Web (RDF/OWL principally, and perhaps XML Topic Maps as well) enable a truly interoperable, open data exchange layer. From what I can see neither Ning nor Google see this, but they are interesting first steps at least. If anyone from Google or Yahoo is reading this, I would be interested in speaking further with you.
Update: Google has taken Google Base offline for a while it seems.
Japanese researchers have developed a technology for the remote control of humans. Hmm... sounds kind of creepy. The system uses weak electrical stimulation of the vestibular system, causing the subject to shift balance and change direction. This technology can also be used to create vestibular illusions -- for example, it can be used to make a person playing a computer game think they are experiencing motion.
A cutting-edge research program is injecting human brain cells into monkey brains, to investigate whether this causes their brains to become more "human." This poses a potential ethical challenge: If the monkeys do become more human, would they be considered "human subjects" and be protected by ethical guidelines governing research onto humans? At which point does a monkey qualify as a legal Person? Could a more humanlinke monkey, or a state attorney on it's behalf, file suit against scientists who harmed it or deprived it of its rights? If a monkey becomes more humanlike, do we have the right to hold it against its will? Super-intelligent monkeys used to be the stuff of the Wizard of Oz, and Flash Gordon science fiction -- now we're actually making them -- what a world we live in! Hey, I have an idea, instead of trying to make monkeys more like men, could we figure out a way to make men LESS like monkeys??? Let's start with the politicians!
Alex is a very smart parrot indeed. To the surprise of researchers, he understands the concept of zero, something which human children don't grasp until they are 2 or 3 years old. Read more about Alex here.
Fascinating article about research which has successfully extracted video from monitoring cat neurons. They have actually reconstructed what the cat actually saw from its neural signals. This opens the door to recording our day-to-day perceptions (lifelogs) and perhaps even to recording our dreams. And of course there might be options for playback as well. This is cool stuff.
In a very interesting new finding, researchers have discovered the people's brains contain individual neurons, or small groups of neurons, that seem exist only to recognize particular people or concepts. This would imply that there is one neuron, or at least a small group of neurons, in our brains for every unique thing that we know. However, that raises certain questions -- for example, if this is true, then the brain should be a lot larger since there wouldn't be room to represent everything a typical adult knows with unique neurons in that amount of space. On the other hand, perhaps the memories are not stored on the neuronal level at all, but instead are stored and computed on the sub-neuronal tubulin "quantum computing" level, which is the subject of much research these days. For more on that check out this book on research into quantum computing in the brain (found by: Josh).
Researchers in Europe have completed the first phase of what may be the largest computational physics experiment in history: They built and ran a simulated universe through 14 billion years of development. The experiment used up 25 million megabytes of memory, and the biggest supercomputer in Europe for a month. The result was a "Cube of Creation" of 20 billion light years per side, containing 20 million simulated galaxies. Now they're studying it to see what evolved. They hope to gain insights into the function of black holes, and other cosmological principles. This is an amazing piece of work -- definitely the future of cosmology research.
In previous articles, I've speculated that our own universe might also be such a simulation, perhaps run by a much more advanced civilization in a meta-universe outside ours. But in fact, I think our universe is probably quite different from a mere computer simulation (despite how cool it would be if it were a computer simulation!) -- because I don't believe we can explain everything there is in terms of information and computation: I think consciousness doesn't fit in that model. After exploring this issue for more than 20 years from the perspectives of computer science and physics, philosophy and religion, I've come to believe that consciousness cannot be reduce to, or emerge from, information or computation. As far as I can tell, it's something at least as or more fundamental than space, time, matter and energy. I would even go so far as to say that we won't ever really understand what the universe is or how it develops or functions without first understanding consciousness much more deeply.
Continue reading "Simulated Universes and the Nature of Consciousness" »
NASA's research on subvocalization technology is moving forward. Their system intercepts nerve signals to the vocal cords before the speaker makes a sound and then figures out what words they signify. This technology will enable people to speak silently on the phone or to their computers, without moving their lips or making a sound. It's almost telepathy. I blogged about this last year when it first came out. It's actually a technology I dreamed about a while back -- "silent speech" is one of those things that has to happen in order to truly free humans from keyboards (although I must confess, I love to type).
A number of readers sent me links this week about the new Sony patent for ultrasonic neural stimulation. It is definitely interesting and could represent a useful new approach to non-invasive brainstate manipulation. However, it is by no means anywhere near being useful for entertainment, virtual reality, or mind control. Our understanding of how the brain works is still far too primitive. Even if the Sony technology was actually working (which it is not, by the way -- it is just an idea, no working prototype was built or tested), it would be a long time before we would know where to aim it. By the time neuroscience has reached a point where thoughts can be stimulated reliably by an external source, this Sony patent and its continuations will have long-since expired. I am guessing we are at least 100 years away from having enough of an understanding of the brain for such a technology to be applicable to mass markets. Meanwhile it might be a useful tool for research -- it's certainly more precise than magnetic stimulation, and it is a lot less damaging than creating physical lesions. It will be interesting to see where this goes, if anywhere. But even if it does go somewhere, there is a chance that mere neural stimulation may not be enough to generate fully-immersive states of consciousness. While such stimulation may trigger particular memories or maybe even perceptual experiences, the complexity required to generate a complete experience -- encompassing all sensory modalities and with enough internal detail and logical consistency to be believable -- is far beyond what we can presently even imagine. In the end, I think it would be more fruitful to leverage the brain's ability to generate dreams than to attempt to build conscious experiences from scratch. We should really do more research into the mechanism of dreaming, and in particular, into the mechanisms of lucid dreaming. By combining hypnosis with lucid dreaming we can create completely immersive states of consciousness today, without any special technology or neural stimulation. And these "simulations" are already far richer and more interactive than anything Sony will come up with in the next several hundred years.
After 30 years of research, a very interesting new theory of cognition has been announced. The theory posits that all human cognition and behavior is based on just one simple, non-algorithmic procedure that has been named confabulation. If the theory is correct it could offer a radical new approach to artificial intelligence, knowledge discovery, and knowledge management.
Dr. Ian Stevenson has amassed 3000 documented cases of children remembering events from past lives.
In each case of children’s past life memory, Dr. Stevenson methodically documents the child's statements. Then he identifies the deceased person the child remembers being, and verifies the facts of the deceased person's life that match the child's memory. He even matches birthmarks and birth defects to wounds and scars on the deceased, verified by medical records. His strict methods systematically rule out all possible "normal" explanations for the child’s memories.
Dr. Stevenson has devoted the last forty years to the scientific documentation of past life memories of children from all over the world. He has over 3000 cases in his files. Many people, including skeptics and scholars, agree that these cases offer the best evidence yet for reincarnation.
Dr. Stevenson's credentials are impeccable. He is a medical doctor and had many scholarly papers to his credit before he began paranormal research. He is the former head of the Department of Psychiatry at the University of Virginia, and now is Director of the Division of Personality Studies at the University of Virginia.
As one reviewer put it, "Either Dr. Stevenson is making a colossal mistake, or he will be known as the Galileo of the 20th century." (Dr Harold Lief in the Journal of Nervous and Mental Disease)
Learn more about Dr. Stevenson's research here.
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