Overcoming Bias Blog
Great new blog from the Future of Humanity Institute, on overcoming cognitive bias. It's a group blog, whose authors include at least four professional philosophers, and many prominent transhumanists, including Robin Hanson, Nick Bostrom, Hal Finney, Peter McCluskey, and Eliezer Yudkowsky.
Also: great article in the LA Times about econo-bloggers.
Eugen Leitl
I found this picture of Eugen Leitl on my computer. Eugen is a transhumanist superstar, and also a chemist. We don't agree about everything, though. For example, Eugen thinks that societies and agents will always retain Darwinian elements like pain, conflict, and the like. Also, he thinks that solar is a more viable source of energy than nuclear, which I disagree with. Other than those two items, I agree with him about most things.
His website, if you want to call it that, is here.
All-Purpose Robot Thursday
Found using the new Picasa web albums, which is superior to Flickr, by the way.
NewScientist: “Brilliant Minds Forecast the Next 50 Years”
Most of the respondents only discussed advances they hope will happen in their own scientific field.
But wait, you can't talk about the future, because it hasn't happened yet, right? Looking any further than five years into the future must mean you are childish, and have your head in the clouds.
Well, the point of this section in New Scientist is to say that this attitude is wrong, and that futurism deserves a place in scientific discourse. We make predictions and continuously refine them according to new evidence. For example, the possibility of wireless energy transfer changes the picture for the next 20 or so years, and beyond. There's nothing wrong with futurism, and many futurist predictions of the past have borne out - though more have failed than succeeded.
Remember, Singularitarians such as myself forsee a prediction horizon in the future - a horizon caused by the arrival of superintelligence. One respondent, Steven Pinker, unsurprisingly, brought up his uncertainty about the future in his response:
I absolutely refuse even to pretend to guess about how I might speculate about what, hypothetically, could be the biggest breakthrough of the next 50 years. This is an invitation to look foolish, as with the predictions of domed cities and nuclear-powered vacuum cleaners that were made 50 years ago.
I will stick my neck out about the next five to ten years, however. I think we'll see a confirmation of the fundamental hypothesis of evolutionary psychology - that many aspects of human cognition and emotion are evolutionary adaptations - from various new techniques for assessing signs of selection in genomic variation within and between species. The recent discoveries of selective pressures on genes for the normal versions of genes for microcephaly, for a speech and language disorder, and for development of the auditory system will be, I suspect, the harbinger of a large number of naturally selected genes with effects on the mind.
You got it, Pinker! I respect his general attitude, but I must break with Pinker's reluctance to predict the biggest breakthrough. To me, it seems obvious - the biggest breakthrough will be the one that itself begets more breakthroughs. That is, a breakthrough in brainpower, whether it be Artificial Intelligence, or Intelligence Augmentation. We transhumanist folks call this the Singularity. Some refuse to predict when they think it will happen, but for those who buy into the singularity hypothesis, the general consensus tends to be sometime between 2020 and 2040.
And how about the Singularity? Did any respondents bring it up? Terry Sejnowski, the computational neurobiologist, did...
How far will we get in 50 years? By then we will have machines that pass the Turing test. However, this is a weak test that does not get at the harder problem, which is to understand how the brain creates consciousness. To crack this we must first understand unconscious processing, which does most of the heavy lifting for us. I suspect that when we start to make progress with this the problem of consciousness will, like the Cheshire cat, disappear, leaving only a smile in the air.
I get the feeling that any AI complicated enough to actually pass the Turing Test would probably be conscious, both in the information-theoretic sense of being made of self-watching cognitive loops, but also in the phenomenological sense of having that "I see red" special-sauce of subjective experience. We humans like to think that consciousness is super-special, and that nothing that operates on "mere" computations can ever be granted it without great difficulty, but unfortunately much of this sentiment derives from psuedoscientific dualism that should have died out 60 years ago.
But it was Eric Horwitz that spoke most explicitly about AI:
Within 50 years, lives will be significantly enhanced by automated reasoning systems that people will perceive as "intelligent". Although many of these systems will be deployed behind the scenes, others will be in the foreground, serving in an elegant, often collaborative manner to help people do their jobs, to learn and teach, to reflect and remember, to plan and decide, and to create. Translation and interpretation systems will catalyse unprecedented understanding and cooperation between people. At death, people will often leave behind rich computational artefacts that include memories, reflections and life histories, accessible for all time.
Robotic scientists will serve as companions in discovery by formulating theories and pursuing their confirmation. By mid-century, advances attributed to automated scientists will include several world-changing breakthroughs.
When Horwitz uses the word "companions" to describe future AIs, he is either purposefully toning himself down or (more likely) he actually believes it. Is it appropriate to refer to a mind that runs on logic elements that operate at 10,000,000 greater serial speed than neurons, a "companion"? In the moral sense, hopefully, in the practical sense, not at all.
The language Horwitz uses for describing future robotic scientists is anthropocentric - he clearly implies rough equivalency of ability between post-Turing AIs and the smartest human scientists. But the points that Moravec and Kurzweil and Yudkowsky and many others have been making for upwards of a decade is that once AI reaches human-equivalency, it necessarily soars past it. Anyone who paints their picture otherwise is 1) unintentionally deceiving the public about the consequences of AI, 2) displaying a quaint naivete about the underlying hardware differences between biological and nonbiological cognitive systems. It's the old vision, one that has been around for decades...
Even though Horwitz talks about AI systems in the background, he still implies that individual AIs will do the cognitive lifting of roughly a single human being. And would you really think that the AI of 2050 would have to be instantiated with the robotics technology of the late 20th century? I mean, you can see the bolts on that robot.
The notion that we will invent AI, and then AI will reason on par with us indefinitely, is based on the assumption that human intelligence is all there is, and there's nothing beyond it. This attitude strikes me as like that of a person in a small rural village who absolutely refuses to acknowledge the existence of any outside world.
Anyway...
Francis Collins talked anti-aging, though of course not SENS, because that is verboten:
Fifty years from now, if I avoid crashing my motorcycle in the interim, I will be 106. If the advances that I envision from the genome revolution are achieved in that time span, millions of my comrades in the baby boom generation will have joined Generation C to become healthy centenarians enjoying active lives.
What a cheery vision! However, it is unambitious. Collins is probably aware of Aubrey de Grey's work and arguments, but like most who do aging research, would prefer to ignore it.
Mr. Collins has little reason to be supportive of the possibility of indefinite lifespans, after all, he became a born-again Christian after observing the faith of his critically ill parents and reading a book by C.S. Lewis. This, my friends, is intellectual failure.
Richard Miller said things similar to Collins:
Turning on the same protective systems in people should, by 2056, be creating the first class of centenarians who are as vigorous and productive as today's run-of-the-mill sexagenarians.
Gregory Chaitin, the information theorist, displayed some nascent transhumanism:
I hope that by 2056 weird astronomical observations will lead to radical new fundamental physics. I expect people will be tampering with the human genome, which should be fun. In my own field, I hope the current desiccated, formal approach has died out and people are more adventurous and creative.
John Halpern, assistant professor of psychiatry at Harvard Medical School, had something very interesting and non-boring to say:
In the coming months I will give psychotherapy assisted by MDMA (ecstasy) to dying cancer patients to see if their anxiety, pain and other end-of-life issues improve. I would like to test whether LSD or psilocybin can relieve debilitating cluster headache, and whether peyote offers Native Americans a treatment for drug and alcohol abuse. Within 10 years, enough positive results could establish that there are special benefits from "psychedelics". This may lead to a new field of medicine in which spirituality is kindled to help us accept our mortality without fear, and where those with addiction problems, anxiety or cluster headache discover a path to genuine healing. Capable of inducing the deeply mystical, these substances may prove to be a source for compassion and hope so desperately needed in these perilous times.
Perhaps psychedelics aren't really as crude or useless as our Puritanical culture would assert.
Meanwhile, Bill Joy, who was so concerned about existential risk just a little while ago, blows this opportunity by talking about energy:
work in the area of green technology for energy and resources. The most significant breakthrough would be to have an inexhaustible source of safe, green energy that is substantially cheaper than any existing energy source.
Ideally such a source would be safe, in that it couldn’t be made into weapons, nor would it make hazardous or toxic waste or CO2. It seems to me that this is most likely to come from a deep new understanding of a physical effect at the nanoscale (or smaller) that allows safe and simple access to fusion – or another completely unexpected energy technology
It seems to me, Bill, that we already have one - thorium. It's just a matter of building the reactors. In any case, spreading the word about existential risk is more important than green energy. Can't have green energy if your planet is on fire, or the cellular machinery of every member of the human species is being hijacked by malignant nanomachines, now can you?
Focusing on the existential risk aspect is especially important because it's a less fun job. Bill would rather talk about green energy than technological risks, because green energy makes us smile and technological risks don't. This species-universal tendency to ignore the risks makes it all the more important for rationalists to counterbalance it.
Hank Conn on the Singularity Issue
From an ImmInst thread:
(1) Matter, from atoms, to molecules, to molecular components, to cells, to trees, to animals, humans and the human brain (i.e. hardware), when combined with other matter in specific ways, from the strong force within an atom, to atomic and molecular bonding, chemical signaling within an organism, or electrical signaling in the human brain (i.e. software), produces changes to the environment around it (i.e. executes an algorithm).
(2) The algorithm that the human brain and body execute is the algorithm of the human mind. The human mind that you know of as yourself is exactly one instance of one particular implementation in hardware and software out of the infinitely large set of all possible implementations of one specific algorithm out of the infinitely large set of all possible goal-seeking, domain independent, common sense, generally intelligent algorithms (i.e. mind designs- not all mind designs have a psychology anything like that of humans- see this for a more in-depth explanation). This specific algorithm and implementation have been evolved through many generations of natural selection that ultimately led to the combination of your genes being "instantiated" (so to speak): growing into the specific, operational instance of the specific implementation of the specific algorithm within mind design space that is you.
(3) Suppose some instance of a mind has direct access to some means of both improving and expanding both the hardware and software capability of its particular implementation. For example, an intelligence implemented on silicon computing technology of today or advanced nanotechnological computing technology of the years ahead could purchase more memory or processing power, thus improving/expanding the hardware upon which it is implemented, thus supplying more resources for the algorithm to use, thus increasing the relative capability of the algorithm compared to other instances of intelligent algorithms within mind design space. It could further more (1) optimize the central software base upon which the algorithm of its intelligence runs, and (2) add functionality for domain independent cognitive tools and abilities (e.g. data mining, belief calculation, inference, reasoning, etc) as well as domain dependent cognitive tools and abilities (e.g. calculator, web browser, C compiler).
(4) Suppose an instance of a mind has direct access to some means of both improving and expanding both the hardware and software capability of its particular implementation. Suppose also that the goal system of this mind elicits a strong goal that directs its behavior to aggressively take advantage of these means. Given each increase in capability of the mind’s implementation, it could (1) increase the speed at which its hardware is upgraded and expanded, (2) More quickly, cleverly, and elegantly optimize its existing software base to maximize capability, (3) Develop better cognitive tools and functions more quickly and in more quantity, and (4) Optimize its implementation on successively lower levels by researching and developing better, smaller, more advanced hardware. This would create a positive feedback loop- the more capable its implementation, the more capable it is in improving its implementation.
(5) We know that this positive feedback loop (let us label this, for understandable reasons, "recursive self-improvement", and let us label the event in which this mind achieves super-human intelligence, for specific reasons explained elsewhere, the "Singularity"), will either occur on one or more humans, or one or more AIs. We can make a distinction between whether this outcome will be Friendly to humans, or Unfriendly to humans, that is, outcomes including the annihilation of humanity, the descent of humanity into some horrific hellish scenario, or increases in over-all pain and/or suffering and/or death relative to their current levels (or however it is that we would really want to define “bad outcomesâ€, if we knew the actual consequences of making the definition in that particular way) would obviously be Unfriendly, and those that decreased the overall pain and/or suffering and/or death, gave humanity a truly optimal utopia and nearly (and, depending on the laws of physics, possibly) infinite life spans in which to live in them, or however it is that we would really want to define “good outcomesâ€, if we knew the actual consequences of making that definition in that particular way, would obviously be Friendly scenarios.
(6) Through recursive self-improvement (RSI), there is currently no way to know what kind of outcome to the Singularity that any kind of human will elicit. The sheer amount of knowledge and ability that will be gained will present the intelligence with power and awareness literally beyond the wildest dreams and experiences of any lesser intelligence (to speak specifically in terms of a human intelligence. Note that while we do have evidence of people's goals and behavior changing for the worse as they gain large amounts of power, this does not provide a technical, measurable test for knowing the bounds of Friendly or Unfriendly outcomes of a given human mind in RSI). Also, as the algorithm and implementation of the human mind arose from evolution by natural selection, the design process in no way took into account the tractability of the provability of bounds of outcomes of the mind through RSI, thus essentially making the problem extremely more complex in human minds relative to other possible mind designs.
(7) However, AI has a particular advantage in that an AI could be an instance of a mind design intelligently chosen from the space of all possible mind designs, with an intelligently defined goal system. If such an AI were designed specifically with mathematical provability of the stability of its goal system through RSI in mind, it could be built to reliably maintain certain causal or probabilistic bounds on Friendly and Unfriendly outcomes of the Singularity, and the Singularity could be initiated in such a way that we are measurably confident of how Friendly the outcome of the Singularity will be under this design.
(8) Unfortunately, proving bounds on the Friendliness of the outcome of a goal system of an AI through recursive self-improvement is (1) by definition, harder, and (2) likely very extremely, harder, than just designing an AI with a working goal system. This, in combination with the intractability of calculating bounds on the outcome of a human (and the vast majority of AIs) in RSI, is what can be known as the "Friendliness problem", in relation to the Singularity, which is an extremely serious and imminent existential risk.
~~~~
Hank Conn is a computer science student at University of Georgia.
Tech Items
The world's largest mobile machine is 300 meters long and weighs 45,500 tons. It is used for pit mining.
Kalpana One is a superior space colony design. It avoids all the shortcomings of past designs, while maximing the ratio of habitable area to hull mass. It is a cylinder and receives natural lighting 24/7 through its endcaps.
We are using gene doping to create supermice in a new way. This same technology can be used to enhance brain size and neuron density in humans.
Soon we will be able to tell exactly how we differed from Neanderthals.
A breakthrough in the theory underlying self-healing robots.
The wireless energy transfer everybody's been talking about.
Launch rings may one day be used to send raw materials up into space.
Questioning the Origin of Priors
This evening I read a recent paper by Robin Hanson, entitled Uncommon Priors Require Origin Disputes. It is quite fascinating and has far-reaching implications for everyday reasoning, in addition to artificial intelligence and decision theory. The paper is only six pages, so you might as well go take a look if the topic interests you.
A prior probability is the likelihood that some event will happen, some condition will be met, or that some belief is true. Priors are always subjective, just like everything else, but are often commonly accepted knowledge. For example, according to Wikipedia, there are about 1,000 winners of the California State Lottery every year, out of a total California population of approximately 33 million. So the prior probability of a California state resident winning the lottery in an average year, ignoring any other information, is about .003%.
But not every prior is common knowledge. For scenarios where the prior is not so clear-cut, such as in complex political, economic, and social situations, priors may differ between individuals. For example, what is the prior probability that Zune will outrun the iPod?
In times like these, circumstances call for examining your particular priors, and asking why the priors you have are better than anyone else's. Some of you may have thought of this situation before if you've been exposed to Bayesian statistics, but it wasn't until Robin Hanson that a theoretical framework was created for making calculations about the probabilistic origins of the priors themselves.
Abstract:
In standard belief models, priors are always common knowledge. This prevents such models from representing agents’ probabilistic beliefs about the origins of their priors. By embedding standard models in a larger standard model, however, pre-priors can describe such beliefs. When an agent’s prior and pre-prior are mutually consistent, he must believe that his prior would only have been different in situations where relevant event chances were different, but that variations in other agents’ priors are otherwise completely unrelated to which events are how likely. Due to this, Bayesians who agree enough about the origins of their priors must have the same priors.
Shortly into the paper, he continues, describing the concept of a pre-prior:
Just as beliefs in a standard model depend on ordinary priors, beliefs in the larger model depend on pre-priors. We do not require that these pre-priors be common; pre-priors can vary. But to keep priors and pre-priors as consistent as possible with each other, we impose a pre-rationality condition. This condition in essence requires that each agent's ordinary prior be obtained by updating his pre-prior on the fact that nature assigned the agents certain particular priors.
This pre-rationality condition has strong implications regarding the rationality of uncommon priors. Consider, for example, two astronomers who disagree about whether the universe is open (and infinite) or closed (and finite). Assume that they are both aware of the same relevant cosmological data, and that they try to be Bayesians, and therefore want to attribute their difference of opinion to differing priors about the size of the universe.
This paper shows that neither astronomer can believe that, regardless of the size of the universe, nature was equally likely to have switched their priors. Each astronomer must instead believe that his prior would only have favored a smaller universe in situations where a smaller universe was actually more likely. Furthermore, he must believe that the other astronomer’s prior would not track the actual size of the universe in this way; other priors can only track universe size indirectly, by tracking his prior. Thus each person must believe that prior origination processes make his prior more correlated with reality than others’ priors.
As a result, these astronomers cannot believe that their differing priors arose due to the expression of differing genes inherited from their parents in the usual way. After all, the usual rules of genetic inheritance treat the two astronomers symmetrically, and do not produce individual genetic variations that are correlated with the size of the universe. This paper thereby shows that agents who agree enough about the origins of their priors must have the same prior. This is a new argument for common priors, and one that depends only on consistency relations between the beliefs of a single agent.
Another example is given concerning a pair of siblings - one is more optimistic and one is more pessimistic, but these innate qualities derive from the genetic lottery, and one random genetic result would have no predisposition to track the truth more accurately than another random genetic result, so these pecularities must be debiased from the reasoning process in order to obtain better priors.
Whenever the process behind the origin of the prior has no special tendency to track reality when compared to alternative origins, it must be treated on equal ground with these alternatives. This can make judgements less concrete or specific than we may have desired, but it is essential for reasoning accurately. As the principle of maximum entropy states, probability distributions must maximize entropy while remaining consistent with the given information, that is, they can never postulate additional information beyond that which is strictly justified.
So if a particular cultural climate in India causes people to assign a prior probability of 20% to an event, but a different cultural climate in the United States causes the prior to be assigned a value of 30%, then either there are aspects of the cultural system which give a particular side an advantage, that is, aspects of the system that better correlate with the truth, or the cultural system is an incidental artifact that is supervening on the process whereby priors are generated, and must be averaged out to satisfy the principle of maximum entropy.
From the beginning of the discussion section on page 5:
These constraints on beliefs about the origins of priors are strong and highly asymmetric. Each agent must believe that his prior would "track truth" in the sense that his prior would only assign a higher probability to an event in situations where that event actually was more likely. Furthermore, he must believe that other agent's priors would only track truth to the extent that their priors covaried with his prior; he believes any additional variation in the priors of others must be completely unrelated to other events of interest.
In contrast, standard scientific beliefs about the origins of individual human variations do not offer much support for the belief that some people's initial belief tendencies track truth much better than other people's tendencies.
It gets worse. Even if you were somehow able to hold a species-average genetic attitude, you'd have to justify the truth-tracking superiority of your prior-originating processes relative to the prior-originating processes of aliens, genetically engineered human beings, artificial intelligences, or any of the multitudes of other intelligent species that could have been created under different evolutionary timelines.
Mindspace-averaged agents may be capable of satisfying Hanson's pre-rationality condition, but no human is capable of doing so completely. However, the overall quality of reasoning can be improved by questioning the processes underlying your priors, comparing them to potential alternatives, and asking whether you would use different numbers if you were a different person.
How, for example, might wealth influence our priors?
Model train controlled via brain-machine interface
Via Pink Tentacle:
Hitachi has successfully tested a brain-machine interface that allows users to turn power switches on and off with their mind. Relying on optical topography, a neuroimaging technique that uses near-infrared light to map blood concentration in the brain, the system can recognize the changes in brain blood flow associated with mental activity and translate those changes into voltage signals for controlling external devices. In the experiments, test subjects were able to activate the power switch of a model train by performing mental arithmetic and reciting items from memory.
The prototype brain-machine interface allows only simple control of switches, but with a better understanding of the subtle variations in blood concentrations associated with various brain activities, the signals can be refined and used to control more complex mechanical operations.
In the long term, brain-machine interface technology may help paralyzed patients become independent by empowering them to carry out actions with their minds. In the short term, Hitachi sees potential applications for this brain-machine interface in the field of cognitive rehabilitation, where it can be used as an entertaining tool for demonstrating a patient’s progress.
The company hopes to make this technology commercially available in five years.
The article writer forgot to mention the application where you use the system to control a cloud of utility fog 100m on a side that you pumped out of your home nanofactory over the course of a week.
Immediate Virus Detection Technology!
From Eurekalert:
Silver bullet: UGA researchers use laser, nanotechnology to rapidly detect viruses
Athens, Ga. – Waiting a day or more to get lab results back from the doctor's office soon could become a thing of a past. Using nanotechnology, a team of University of Georgia researchers has developed a diagnostic test that can detect viruses as diverse as influenza, HIV and RSV in 60 seconds or less.
In addition to saving time, the technique – which is detailed in the November issue of the journal Nano Letters – could save lives by rapidly detecting a naturally occurring disease outbreak or bioterrorism attack.
"It saves days to weeks," said lead author Ralph Tripp, Georgia Research Alliance Eminent Scholar in Vaccine Development at the UGA College of Veterinary Medicine. "You could actually apply it to a person walking off a plane and know if they're infected."
The technique, called surface enhanced Raman spectroscopy (SERS), works by measuring the change in frequency of a near-infrared laser as it scatters off viral DNA or RNA. This change in frequency, named the Raman shift for the scientist who discovered it in 1928, is as distinct as a fingerprint.
This phenomenon is well known, but Tripp explained that previous attempts to use Raman spectroscopy to diagnose viruses failed because the signal produced is inherently weak.
But UGA physics professor Yiping Zhao and UGA chemistry professor Richard Dluhy experimented with several different metals and methods and found a way to significantly amplify the signal. Using a method they've patented, they place rows of silver nanorods 10,000 times finer than the width of a human hair on the glass slides that hold the sample. And, like someone positioning a TV antenna to get the best reception, they tried several angles until they found that the signal is best amplified when the nanorods are arranged at an 86-degree angle.
"The enhancement factors are extraordinary," Dluhy said. "And the nice thing about this fabrication methodology is that it's very easy to implement, it's very cheap and it's very reproducible."
Tripp said the technique is so powerful that it has the potential to detect a single virus particle and can also discern virus subtypes and those with mutations such as gene insertions and deletions. This specificity makes it valuable as a diagnostic tool, but also as a means for epidemiologists to track where viruses originate from and how they change as they move through populations.
The researchers have shown that the technique works with viruses isolated from infected cells grown in a lab, and the next step is to study its use in biological samples such as blood, feces or nasal swabs. Tripp said preliminary results are so promising that the researchers are currently working to create an online encyclopedia of Raman shift values. With that information, a technician could readily reference a Raman shift for a particular virus to identify an unknown virus.
To make their finding commercially viable, they're developing a business model, seeking venture capital and exploring ways to mass produce the silver nanorods. Next year, they plan on moving their enterprise to the Georgia BioBusiness Center, an UGA incubator for startup bio-science companies.
Presently, viruses are first diagnosed with methods that detect the antibodies a person produces in response to an infection. Tripp explained that these tests are prone to false positives because a person can still have antibodies in their system from a related infection decades ago. The tests are also prone to false negatives because some people don't produce high levels of antibodies.
Because of these limitations, antibody based tests often must be confirmed with a test known as polymerase chain reaction (PCR), which detects the virus itself by copying it many times. The test can take anywhere from several days to two weeks. Tripp said the latter is clearly too long, especially in light of emerging threats such as H5N1 avian influenza.
"For some respiratory viruses, you've either cleared the infection at that point or succumbed to the infection," Tripp said. "What we've developed is the next generation of diagnostic testing."
Big win! This will be useful to avoid the coming Doomsday Virus. ;)