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Ethics, Qualia Research & AI Safety with Mike Johnson

What’s the relationship between valence research and AI ethics?

Hedonic valence is a measure of the quality of our felt sense of experience, the intrinsic goodness (positive valence) or averseness (negative valence) of an event, object, or situation.  It is an important aspect of conscious experience; always present in our waking lives. If we seek to understand ourselves, it makes sense to seek to understand how valence works – how to measure it and test for it.

Also, might there be a relationship to the AI safety/friendliness problem?
In this interview, we cover a lot of things, not least .. THE SINGULARITY (of course) & the importance of Valence Research to AI Friendliness Research (as detailed here). Will thinking machines require experience with valence to understand it’s importance?

Here we cover some general questions about Mike Johnson’s views on recent advances in science and technology & what he sees as being the most impactful, what world views are ready to be retired, his views on XRisk and on AI Safety – especially related to value theory.

This one part of an interview series with Mike Johnson (another section on Consciousness, Qualia, Valence & Intelligence). 

 

Adam Ford: Welcome Mike Johnson, many thanks for doing this interview. Can we start with your background?

Mike Johnson

Mike Johnson: My formal background is in epistemology and philosophy of science: what do we know & how do we know it, what separates good theories from bad ones, and so on. Prior to researching qualia, I did work in information security, algorithmic trading, and human augmentation research.

 

Adam: What is the most exciting / interesting recent (scientific/engineering) news? Why is it important to you?

Mike: CRISPR is definitely up there! In a few short years precision genetic engineering has gone from a pipe dream to reality. The problem is that we’re like the proverbial dog that caught up to the car it was chasing: what do we do now? Increasingly, we can change our genome, but we have no idea how we should change our genome, and the public discussion about this seems very muddled. The same could be said about breakthroughs in AI.

 

Adam: What are the most important discoveries/inventions over the last 500 years?

Mike: Tough question. Darwin’s theory of Natural Selection, Newton’s theory of gravity, Faraday & Maxwell’s theory of electricity, and the many discoveries of modern physics would all make the cut. Perhaps also the germ theory of disease. In general what makes discoveries & inventions important is when they lead to a productive new way of looking at the world.

 

Adam: What philosophical/scientific ideas are ready to be retired? What theories of valence are ready to be relegated to the dustbin of history? (Why are they still in currency? Why are they in need of being thrown away or revised?)

Mike: I think that 99% of the time when someone uses the term “pleasure neurochemicals” or “hedonic brain regions” it obscures more than it explains. We know that opioids & activity in the nucleus accumbens are correlated with pleasure– but we don’t know why, we don’t know the causal mechanism. So it can be useful shorthand to call these things “pleasure neurochemicals” and whatnot, but every single time anyone does that, there should be a footnote that we fundamentally don’t know the causal story here, and this abstraction may ‘leak’ in unexpected ways.

 

Adam: What have you changed your mind about?

Mike: Whether pushing toward the Singularity is unequivocally a good idea. I read Kurzweil’s The Singularity is Near back in 2005 and loved it- it made me realize that all my life I’d been a transhumanist and didn’t know it. But twelve years later, I’m a lot less optimistic about Kurzweil’s rosy vision. Value is fragile, and there are a lot more ways that things could go wrong, than ways things could go well.

 

Adam: I remember reading Eliezer’s writings on ‘The Fragility of Value’, it’s quite interesting and worth consideration – the idea that if we don’t get AI’s value system exactly right, then it would be like pulling a random mind out of mindspace – most likely inimicable to human interests. The writing did seem quite abstract, and it would be nice to see a formal model or something concrete to show this would be the case. I’d really like to know how and why value is as fragile as Eliezer seems to make out. Is there any convincing crisply defined model supporting this thesis?

Mike: Whether the ‘Complexity of Value Thesis’ is correct is super important. Essentially, the idea is that we can think of what humans find valuable as a tiny location in a very large, very high-dimensional space– let’s say 1000 dimensions for the sake of argument. Under this framework, value is very fragile; if we move a little bit in any one of these 1000 dimensions, we leave this special zone and get a future that doesn’t match our preferences, desires, and goals. In a word, we get something worthless (to us). This is perhaps most succinctly put by Eliezer in “Value is fragile”:

“If you loose the grip of human morals and metamorals – the result is not mysterious and alien and beautiful by the standards of human value. It is moral noise, a universe tiled with paperclips. To change away from human morals in the direction of improvement rather than entropy, requires a criterion of improvement; and that criterion would be physically represented in our brains, and our brains alone. … You want a wonderful and mysterious universe? That’s your value. … Valuable things appear because a goal system that values them takes action to create them. … if our values that prefer it are physically obliterated – or even disturbed in the wrong dimension. Then there is nothing left in the universe that works to make the universe valuable.”

If this frame is right, then it’s going to be really really really hard to get AGI right, because one wrong step in programming will make the AGI depart from human values, and “there will be nothing left to want to bring it back.” Eliezer, and I think most of the AI safety community assumes this.

But– and I want to shout this from the rooftops– the complexity of value thesis is just a thesis! Nobody knows if it’s true. An alternative here would be, instead of trying to look at value in terms of goals and preferences, we look at it in terms of properties of phenomenological experience. This leads to what I call the Unity of Value Thesis, where all the different manifestations of valuable things end up as special cases of a more general, unifying principle (emotional valence). What we know from neuroscience seems to support this: Berridge and Kringelbach write about how “The available evidence suggests that brain mechanisms involved in fundamental pleasures (food and sexual pleasures) overlap with those for higher-order pleasures (for example, monetary, artistic, musical, altruistic, and transcendent pleasures).” My colleague Andres Gomez Emilsson writes about this in The Tyranny of the Intentional Object. Anyway, if this is right, then the AI safety community could approach the Value Problem and Value Loading Problem much differently.

 

Adam: I’m also interested in the nature of possible attractors that agents might ‘extropically’ gravitate towards (like a thirst for useful and interesting novelty, generative and non-regressive, that might not neatly fit categorically under ‘happiness’) – I’m not wholly convinced that they exist, but if one leans away from moral relativism, it makes sense that a superintelligence may be able to discover or extrapolate facts from all physical systems in the universe, not just humans, to determine valuable futures and avoid malignant failure modes (Coherent Extrapolated Value if you will). Being strongly locked into optimizing human values may be a non-malignant failure mode.

Mike: What you write reminds me of Schmidhuber’s notion of a ‘compression drive’: we’re drawn to interesting things because getting exposed to them helps build our ‘compression library’ and lets us predict the world better. But this feels like an instrumental goal, sort of a “Basic AI Drives” sort of thing. Would definitely agree that there’s a danger of getting locked into a good-yet-not-great local optima if we hard optimize on current human values.

Probably the danger is larger than that too– as Eric Schwitzgebel notes​, ​

“Common sense is incoherent in matters of metaphysics. There’s no way to develop an ambitious, broad-ranging, self- consistent metaphysical system without doing serious violence to common sense somewhere. It’s just impossible. Since common sense is an inconsistent system, you can’t respect it all. Every metaphysician will have to violate it somewhere.”

If we lock in human values based on common sense, we’re basically committing to following an inconsistent formal system. I don’t think most people realize how badly that will fail.

 

Adam: What invention or idea will change everything?

Mike: A device that allows people to explore the space of all possible qualia in a systematic way. Right now, we do a lot of weird things to experience interesting qualia: we drink fermented liquids, smoke various plant extracts, strap ourselves into rollercoasters, and parachute out of plans, and so on, to give just a few examples. But these are very haphazard ways to experience new qualia! When we’re able to ‘domesticate’ and ‘technologize’ qualia, like we’ve done with electricity, we’ll be living in a new (and, I think, incredibly exciting) world.

 

Adam: What are you most concerned about? What ought we be worrying about?

Mike: I’m worried that society’s ability to coordinate on hard things seems to be breaking down, and about AI safety. Similarly, I’m also worried about what Eliezer Yudkowsky calls ‘Moore’s Law of Mad Science’, that steady technological progress means that ‘every eighteen months the minimum IQ necessary to destroy the world drops by one point’. But I think some very smart people are worrying about these things, and are trying to address them.

In contrast, almost no one is worrying that we don’t have good theories of qualia & valence. And I think we really, really ought to, because they’re upstream of a lot of important things, and right now they’re “unknown unknowns”- we don’t know what we don’t know about them.

One failure case that I worry about is that we could trade away what makes life worth living in return for some minor competitive advantage. As Bostrom notes in Superintelligence,

“When it becomes possible to build architectures that could not be implemented well on biological neural networks, new design space opens up; and the global optima in this extended space need not resemble familiar types of mentality. Human-like cognitive organizations would then lack a niche in a competitive post-transition economy or ecosystem. We could thus imagine, as an extreme case, a technologically highly advanced society, containing many complex structures, some of them far more intricate and intelligent than anything that exists on the planet today – a society which nevertheless lacks any type of being that is conscious or whose welfare has moral significance. In a sense, this would be an uninhabited society. It would be a society of economic miracles and technological awesomeness, with nobody there to benefit. A Disneyland with no children.”

Nick Bostrom

Now, if we don’t know how qualia works, I think this is the default case. Our future could easily be a technological wonderland, but with very little subjective experience. “A Disneyland with no children,” as Bostrom quips.

 

 

Adam: How would you describe your ethical views? What are your thoughts on the relative importance of happiness vs. suffering? Do things besides valence have intrinsic moral importance?

Mike: Good question. First, I’d just like to comment that Principia Qualia is a descriptive document; it doesn’t make any normative claims.

I think the core question in ethics is whether there are elegant ethical principles to be discovered, or not. Whether we can find some sort of simple description or efficient compression scheme for ethics, or if ethics is irreducibly complex & inconsistent.

The most efficient compression scheme I can find for ethics, that seems to explain very much with very little, and besides that seems intuitively plausible, is the following:

  1. Strictly speaking, conscious experience is necessary for intrinsic moral significance. I.e., I care about what happens to dogs, because I think they’re conscious; I don’t care about what happens to paperclips, because I don’t think they are.
  2. Some conscious experiences do feel better than others, and all else being equal, pleasant experiences have more value than unpleasant experiences.

Beyond this, though, I think things get very speculative. Is valence the only thing that has intrinsic moral importance? I don’t know. On one hand, this sounds like a bad moral theory, one which is low-status, has lots of failure-modes, and doesn’t match all our intuitions. On the other hand, all other systematic approaches seem even worse. And if we can explain the value of most things in terms of valence, then Occam’s Razor suggests that we should put extra effort into explaining everything in those terms, since it’d be a lot more elegant. So– I don’t know that valence is the arbiter of all value, and I think we should be actively looking for other options, but I am open to it. That said I strongly believe that we should avoid premature optimization, and we should prioritize figuring out the details of consciousness & valence (i.e. we should prioritize research over advocacy).

Re: the relative importance of happiness vs suffering, it’s hard to say much at this point, but I’d expect that if we can move valence research to a more formal basis, there will be an implicit answer to this embedded in the mathematics.

Perhaps the clearest and most important ethical view I have is that ethics must ultimately “compile” to physics. What we value and what we disvalue must ultimately cash out in terms of particle arrangements & dynamics, because these are the only things we can actually change. And so if people are doing ethics without caring about making their theories cash out in physical terms, they’re not actually doing ethics- they’re doing art, or social signaling, or something which can serve as the inspiration for a future ethics.

Perhaps the clearest and most important ethical view I have is that ethics must ultimately “compile” to physics. What we value and what we disvalue must ultimately cash out in terms of particle arrangements & dynamics, because these are the only things we can actually change.

The analogy I’d offer here is that we can think about our universe as a computer, and ethics as choosing a program to run on this computer. Unfortunately, most ethicists aren’t writing machine-code, or even thinking about things in ways that could be easily translated to machine-code. Instead, they’re writing poetry about the sorts of programs that might be nice to run. But you can’t compile poetry to machine-code! So I hope the field of ethics becomes more physics-savvy and quantitative (although I’m not optimistic this will happen quickly).

Eliezer Yudkowsky refers to something similar with his notions of “AI grade philosophy”, “compilable philosophy”, and “computable ethics”, though I don’t think he quite goes far enough (i.e., all the way to physics).

 

Adam: What excites you? What do you think we have reason to be optimistic about?

Mike: The potential of qualia research to actually make peoples’ lives better in concrete, meaningful ways. Medicine’s approach to pain management and treatment of affective disorders are stuck in the dark ages because we don’t know what pain is. We don’t know why some mental states hurt. If we can figure that out, we can almost immediately help a lot of people, and probably unlock a surprising amount of human potential as well. What does the world look like with sane, scientific, effective treatments for pain & depression & akrasia? I think it’ll look amazing.

 

Adam: If you were to take a stab at forecasting the Intelligence Explosion – in what timeframe do you think it might happen (confidence intervals allowed)?

Mike: I don’t see any intractable technical hurdles to an Intelligence Explosion: the general attitude in AI circles seems to be that progress is actually happening a lot more quickly than expected, and that getting to human-level AGI is less a matter of finding some fundamental breakthrough, and more a matter of refining and connecting all the stuff we already know how to do.

The real unknown, I think, is the socio-political side of things. AI research depends on a stable, prosperous society able to support it and willing to ‘roll the dice’ on a good outcome, and peering into the future, I’m not sure we can take this as a given. My predictions for an Intelligence Explosion:

  • Between ~2035-2045 if we just extrapolate research trends within the current system;
  • Between ~2080-2100 if major socio-political disruptions happen but we stabilize without too much collateral damage (e.g., non-nuclear war, drawn-out social conflict);
  • If it doesn’t happen by 2100, it probably implies a fundamental shift in our ability or desire to create an Intelligence Explosion, and so it might take hundreds of years (or never happen).

 

If a tree falls in the forest and no one is around to hear it, does it make a sound? It would be unfortunate if a whole lot of awesome stuff were to happen with no one around to experience it.  <!–If a rainbow appears in a universe, and there is no one around to experience it, is it beautiful?–>

Also see the 2nd part, and 3nd part (conducted by Andrés Gómez Emilson) of this interview series conducted by Andrés Gómez Emilson and this interview with Christof Koch will likely be of interest.

 

Mike Johnson is a philosopher living in the Bay Area, writing about mind, complexity theory, and formalization. He is Co-founder of the Qualia Research Institute. Much of Mike’s research and writings can be found at the Open Theory website.
‘Principia Qualia’ is Mike’s magnum opus – a blueprint for building a new Science of Qualia. Click here for the full version, or here for an executive summary.
If you like Mike’s work, consider helping fund it at Patreon.

Can we build AI without losing control over it? – Sam Harris

San Harris (author of The Moral Landscape and host of the Waking Up podcast) discusses the need for AI Safety – while fun to think about, we are unable to “martial an appropriate emotional response” to improvements in AI and automation and the prospect of dangerous AI – it’s a failure of intuition to respond to it like one would a sci-fi like doom scenario.

Scared of superintelligent AI? You should be, says neuroscientist and philosopher Sam Harris — and not just in some theoretical way. We’re going to build superhuman machines, says Harris, but we haven’t yet grappled with the problems associated with creating something that may treat us the way we treat ants.

Anders Sandberg -The Technological Singularity

Anders Sandberg.00_23_53_16.Still031Anders gives a short tutorial on the Singularity – clearing up confusion and highlighting important aspects of the Technological Singularity and related ideas, such as accelerating change, horizons of predictability, self-improving artificial intelligence, and the intelligence explosion.

Tutorial Video:

Points covered in the tutorial:

  • The Mathematical Singularity
  • The Technological Singularity: A Horizon of predictability
  • Confusion Around The Technological Singularity
  • Drivers of Accelerated Growth
  • Technology Feedback Loops
  • A History of Coordination
  • Technological Inflection Points
  • Difficult of seeing what happens after an Inflection Point
  • The Intelligence Explosion
  • An Optimisation Power Applied To Itself
  • Group Minds
  • The HIVE Singularity: A Networked Global Mind
  • The Biointelligence explosion
  • Humans are difficult to optimise

An Overview of Models of the Technological Singularity

anders-sandberg-technology-feedback-loopsSee Anders’ paper ‘An overview of models of technological singularity
This paper reviews different definitions and models of technological singularity. The models range from conceptual sketches to detailed endogenous growth models, as well as attempts to fit empirical data to quantitative models. Such models are useful for examining the dynamics of the world-system and possible types of future crisis points where fundamental transitions are likely to occur. Current models suggest that, generically, even small increasing returns tends to produce radical growth. If mental capital becomes copyable (such as would be the case for AI or brain emulation) extremely rapid growth would also become likely.
http://agi-conf.org/2010/wp-content/uploads/2009/06/agi10singmodels2.pdf

[The] Technological singularity is of increasing interest among futurists both as a predicted possibility in the midterm future and as subject for methodological debate. The concept is used in a variety of contexts, and has acquired an unfortunately large number of meanings. Some versions stress the role of artificial intelligence, others refer to more general technological change. These multiple meanings can overlap, and many writers use combinations of meanings: even Vernor Vinge’s seminal essay that coined the term uses several meanings. Some of these meanings may imply each other but often there is a conflation of different elements that likely (but not necessarily) occur in parallel. This causes confusion and misunderstanding to the extent that some critics argue that the term should be avoided altogether. At the very least the term ‘singularity’ has led to many unfortunate assumptions that technological singularity involves some form of mathematical singularity and can hence be ignored as unphysical.Anders Sandberg

A list of models described in the paper:

A. Accelerating change

Exponential or superexponential technological growth (with linked economical growth and social change) (Ray Kurzweil (Kur05), John Smart (Smang))

B. Self improving technology

Better technology allows faster development of new and better technology. (Flake (Fla06))

C. Intelligence explosion

Smarter systems can improve themselves, producing even more intelligence in a strong feedback loop. (I.J. Good (Goo65), Eliezer Yudkowsky)

D. Emergence of superintelligence

(Singularity Institute) 1

E. Prediction horizon

Rapid change or the emergence of superhuman intelligence makes the future impossible to predict from our current limited knowledge and experience. (Vinge, (Vin93))

F. Phase transition

The singularity represents a shift to new forms of organisation. This could be a fundamental difference in kind such as humanity being succeeded by posthuman or artificial intelligences,
a punctuated equilibrium transition or the emergence of a new meta-system level. (Teilhard de Chardin, Valentin Turchin (Tur77), Heylighen (Hey07))

G. Complexity disaster

Increasing complexity and interconnectedness causes increasing payoffs, but increases instability. Eventually this produces a crisis, beyond which point the dynamics must be different.
(Sornette (JS01), West (BLH+07))

H. Inflexion point

Large-scale growth of technology or economy follows a logistic growth curve. The singularity represents the inflexion point where change shifts from acceleration to de-acceleration. (Extropian
FAQ, T. Modis (Mod02))

I. Infinite progress

The rate of progress in some domain goes to infinity in nite time. (Few, if any, hold this to be plausible 2 )

anders-sandberg-the-technological-singularity-predictability-horizon

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Singularity Skepticism or Advocacy – to what extent is it warranted?

Why are some people so skeptical of the possibility of Super-intelligent Machines, while others take it quite seriously?
Hugo de Garis addresses both ‘Singularity Skepticism’ and advocacy – reasons for believing machine intelligence is not only possible but quite probable!
The Singularity will likely be an unprecedentedly huge issue that we will need to face in the coming decades.

Singularity Skepticism - Hugh de Garis. 2jpg

If you take the average person in the street and you talk to them about a future intelligent machine – there is a lot of skepticism – because today’s machines aren’t intelligent right? I know from my own personal experience that I get incredibly frustrated with computers, they crash all the time, they don’t do what I want… literally I say “I hate computers” but I really love them – so I have an ambivalent relationship with computers..Hugo de Garis
.

The exponential growth of technology and resolution of brain-scanning may lead to advanced neuro-engineering. Brain simulation right down to the chemical synapse, or just plain old functional brain representation might be possible within our lifetimes – this would likely lead to a neuromorphic flavour of the singularity.

There have been some enthusiastic and skeptical responses to this video so far on YouTube:

AZR NSMX1 commented that “Computers already have a better memory and a higher speed than human brain, they can learn and recognice the human voice since 1982 with the first software made for Kurzweil Industries, the expert systems are the first steps for thinking, then in 90’s we learned that emotions are more easy for machines than we believed, an emotion is just an uncontrolled reaction an automatic preservation code that may be good or not for a robot to reach its goal. Now in 2010 the Watson supercomputer show us that is able to structure the human language to produce a logic response, if that is not what does the thought, then somebody explain me what means to think. The only thing they still can’t do is the creative thinking and conciousness, but that will be reached between 2030 and 2035. Conciousness is just the amout and quality of the information you can process, IBM Blue Brain team said this, for example we the humans are very stupid when it comes to use and exploit all the possibilities offered by the smell sense compared to dogs or bears, in this dimension a cockroach is smarter than us because they can map the direction of smell to find the food or other members of their group, we can’t do this, we just have no consciusness in that world. Creativity is the most complex thing, if machines reaches creativity then our world will change because we will not only have to work anymore, but what is better we will not have to think anymore haha. Machines gonna do everything.”
 My response: There has certainly been some impressive strides in technological advancement, it might asymptote at some stage – not sure when, but my take is that there won’t likely be many fundamental engineering or scientific bottlenecks that will block or stifle progress – the biggest problems I think will be sociological impediments – human caused. 

Darian Rachel says “Around the 8 minute or so point he makes a statement that a machine will be built that is intelligent and conscious. He seems to pull this idea that it will be conscious “out of the air” somewhere. It seems to be a rather silly idea.”
 My response: while I agree that a conscious machine is likely difficult to build, there doesn’t seem to be much agreement among humans about whether it exists, what consciousness actually is, whether it is a byproduct of (complex?) information processing and whether it is actually computable (using classical computation). Perhaps Hugo de Garis views consciousness as just being self-aware. 

Exile438 responded that the “human brain has 100billion neurons and each connects to 10,000 other neurons, 10^11*10^4=10^15 human brain capacity estimate. Brain scanning resolution and speed of computers doubles every so often so within the next 2 to 3 decades we can simulate a brain on a computer. If we can do that it would run electronically 4million times faster then our chemical brains. This leads to singularity.”
 My response: it’s certainly a strange and exciting time to be alive – the fundamental questions that we have been wrestling with since before recorded history – questions around personal identity and what makes us what we – may be unraveled within the lifetimes of most of us here today. 

The long-term future of AI (and what we can do about it) : Daniel Dewey at TEDxVienna

daniel deweyThis has been one of my favourite simple talks on AI Impacts – Simple, clear and straight to the point. Recommended as an introduction to the ideas (referred to in the title).

I couldn’t find the audio of this talk at TED – it has been added to archive.org:

 

Daniel Dewey is a research fellow in the Oxford Martin Programme on the Impacts of Future Technology at the Future of Humanity Institute, University of Oxford. His research includes paths and timelines to machine superintelligence, the possibility of intelligence explosion, and the strategic and technical challenges arising from these possibilities. Previously, Daniel worked as a software engineer at Google, did research at Intel Research Pittsburgh, and studied computer science and philosophy at Carnegie Mellon University. He is also a research associate at the Machine Intelligence Research Institute.

http://www.tedxvienna.at/

 

Michio Kaku – A History of a Time to Come

Science, Technology & the Future interviews Dr. Michio Kaku on Artificial Intelligence and the Singularity, Biotech and Nanotechnology

  • What is it that is driving this revolution?
  • How do you think your background in Theoretical Physics shape your view on the future of the mind?
  • Intelligence enhancement, Internet of the mind – brain-net, like a hive mind? Where are we at with AI?
  • Many AI experts and scientists agree that some time in the future a Singularity will be possible (often disagreeing about when). What are your thoughts on the Singularity?
  • What about advances in Nanotechnology?
  • Is the Sticky Fingers problem a show stopper?

Michio is the author of many best sellers, most recently “the Future of the Mind” – We are entering a golden age of neuroscience – today it seems much of the discourse today seems to be it’s use in helping understand and treat mental illness (which is great) – though in the future, there will be other profound implications to understanding neuroscience – such as understanding the mechanics of intelligence…

Michio-Kaku-2014-06_24

Michio Kaku’s Biography

Michio Kaku (born January 24, 1947) is an American theoretical physicist, the Henry Semat Professor of Theoretical Physics at the City College of New York, a futurist, and a communicator and popularizer of science. He has written several books about physics and related topics, has made frequent appearances on radio, television, and film, and writes extensive online blogs and articles. He has written three New York Times Best Sellers: Physics of the Impossible (2008), Physics of the Future (2011), and The Future of the Mind (2014).

Kaku is the author of various popular science books:
– Beyond Einstein: The Cosmic Quest for the Theory of the Universe (with Jennifer Thompson) (1987)
– Hyperspace: A Scientific Odyssey through Parallel Universes, Time Warps, and the Tenth Dimension (1994)
– Visions: How Science Will Revolutionize the 21st Century[12] (1998)
– Einstein’s Cosmos: How Albert Einstein’s Vision Transformed Our Understanding of Space and Time (2004)
– Parallel Worlds: A Journey through Creation, Higher Dimensions, and the Future of the Cosmos (2004)
– Physics of the Impossible: A Scientific Exploration into the World of Phasers, Force Fields, Teleportation, and Time Travel (2008)
– Physics of the Future: How Science Will Shape Human Destiny and Our Daily Lives by the Year 2100 (2011)
– The Future of the Mind: The Scientific Quest to Understand, Enhance, and Empower the Mind (2014)

Also see this previous interview with Michio Kaku:

 

The Future of the Mind‘ – Book on Amazon.

Many thanks to Think Inc. who brought Dr Kaku to Australia!

Subscribe to the Science, Technology & the Future YouTube Channel

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Science, Technology & the Future

Michio Kaku – The Future of the Mind – Intelligence Enhancement & the Singularity

Scifuture interview with popular scientist Michio Kaku on the Scientific Quest to Understand, Enhance & Empower the Mind!

The audio of this interview is found here.

Dr. Michio Kaku advocates thinking about some of the radical Transhumanist ideas we all know and love – here he speaks on the frontiers of Neuroscience, Intelligence Enhancement, the Singularity, and his new book ‘The Future of the Mind’!

String theory stems from Albert Einstein’s legacy; it combines the theory of general relativity and quantum mechanics by assuming the multiverse of universes. String field theory then uses the mathematics of fields to put it all into perspectives. Dr Kaku’s goal is to unite the four fundamental forces of nature into one ‘unified field theory’, a theory that seeks to summarise all fundamental laws of the universe in one simple equation.

Note Scifuture did another interview with Michio Kaku – the article can be found here, audio can be found here, and the video can be found here.

MichioKaku12162013

The Future of the Mind‘ – Book on Amazon.

Many thanks to Think Inc. who brought Dr Kaku to Australia!

Subscribe to the Science, Technology & the Future YouTube Channel

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Science, Technology & the Future

The Singularity & Prediction – Can there be an Intelligence Explosion? – Interview with Marcus Hutter

Can there be an Intelligence Explosion?  Can Intelligence Explode?
The technological singularity refers to a hypothetical scenario in which technological advances virtually explode. The most popular scenario is the creation of super-intelligent algorithms that recursively create ever higher intelligences. What could it mean for intelligence to explode?
We need to provide more careful treatment of what intelligence actually is, separate speed from intelligence explosion, compare what super-intelligent participants and classical human observers might experience and do, discuss immediate implications for the diversity and value of life, consider possible bounds on intelligence, and contemplate intelligences right at the singularity.

Let an ultraintelligent machine be defined as a machine that can far surpass all the intellectual activities of any man however clever. Since the design of machines is one of these intellectual activities, an ultraintelligent machine could design even better machines; there would then unquestionably be an ‘intelligence explosion,’ and the intelligence of man would be left far behind. Thus the first ultraintelligent machine is the last invention that man need ever make. Irving John Good - 'Good Thinking: The Foundations of Probability and Its Applications'

team-marcus-hutterPaper: M.Hutter, Can Intelligence Explode, Journal of Consciousness Studies, Vol.19, Nr 1-2 (2012) pages 143–166.
http://www.hutter1.net/publ/singularity.pdf
http://arxiv.org/abs/1202.6177

See also:
http://2012.singularitysummit.com.au/2012/08/can-intelligence-explode/
http://2012.singularitysummit.com.au/2012/08/universal-artificial-intelligence/

Can Intelligence Explode? – Marcus Hutter at Singularity Summit Australia 2012

Abstract: The technological singularity refers to a hypothetical scenario in which technological advances virtually explode. The most popular scenario is the creation of super-intelligent algorithms that recursively create ever higher intelligences. After a short introduction to this intriguing potential future, I will elaborate on what it could mean for intelligence to explode. In this course, I will (have to) provide a more careful treatment of what intelligence actually is, separate speed from intelligence explosion, compare what super-intelligent participants and classical human observers might experience and do, discuss immediate implications for the diversity and value of life, consider possible bounds on intelligence, and contemplate intelligences right at the singularity.

 


 

Slides (pdf): http://www.hutter1.net/publ/ssingularity.pdf
Slides (PowerPoint): http://www.hutter1.net/publ/ssingularity.ppsx
Paper: M.Hutter, Can Intelligence Explode, Journal of Consciousness Studies, Vol.19, Nr 1-2 (2012) pages 143–166.
http://www.hutter1.net/publ/singularity.pdf

Also see:
http://2012.singularitysummit.com.au/2012/08/can-intelligence-explode/
http://2012.singularitysummit.com.au/2012/08/universal-artificial-intelligence/
http://2012.singularitysummit.com.au/2012/08/panel-intelligence-substrates-computation-and-the-future/
http://2012.singularitysummit.com.au/2012/01/marcus-hutter-to-speak-at-the-singularity-summit-au-2012/
http://2012.singularitysummit.com.au/agenda

Marcus Hutter (born 1967) is a German computer scientist and professor at the Australian National University. Hutter was born and educated in Munich, where he studied physics and computer science at the Technical University of Munich. In 2000 he joined Jürgen Schmidhuber’s group at the Swiss Artificial Intelligence lab IDSIA, where he developed the first mathematical theory of optimal Universal Artificial Intelligence, based on Kolmogorov complexity and Ray Solomonoff’s theory of universal inductive inference. In 2006 he also accepted a professorship at the Australian National University in Canberra.

Hutter’s notion of universal AI describes the optimal strategy of an agent that wants to maximize its future expected reward in some unknown dynamic environment, up to some fixed future horizon. This is the general reinforcement learning problem. Solomonoff/Hutter’s only assumption is that the reactions of the environment in response to the agent’s actions follow some unknown but computable probability distribution.

team-marcus-hutter

Professor Marcus Hutter

Research interests:

Artificial intelligence, Bayesian statistics, theoretical computer science, machine learning, sequential decision theory, universal forecasting, algorithmic information theory, adaptive control, MDL, image processing, particle physics, philosophy of science.

Bio:

Marcus Hutter is Professor in the RSCS at the Australian National University in Canberra, Australia. He received his PhD and BSc in physics from the LMU in Munich and a Habilitation, MSc, and BSc in informatics from the TU Munich. Since 2000, his research at IDSIA and now ANU is centered around the information-theoretic foundations of inductive reasoning and reinforcement learning, which has resulted in 100+ publications and several awards. His book “Universal Artificial Intelligence” (Springer, EATCS, 2005) develops the first sound and complete theory of AI. He also runs the Human Knowledge Compression Contest (50’000€ H-prize).

Should We Fear or Welcome the Singularity? Nobel Week Dialogue 2015 – The Future of Intelligence

Panel - Ray Kurzweil Stuart Russell Max Tegmark Harry Shum - mod Margaret BodenShould science and society welcome ‘the singularity’ – the idea of the hypothetical moment in time when artificial intelligence surpasses human intelligence?
The discussion has been growing over decades, institutes dedicated to solving AI friendliness have popped up, and more recently the ideas have found popular advocates. Certainly super intelligent machines could help solve classes of problems that humans struggle with, and also if not designed well may cause more problems that they solve.

Is the question of fear or hope in AI a false dichotomy?

Ray Kurzweil

Ray Kurzweil

While Kurzweil agrees that AI risks are real argues that we already face risks involving biotechnology – I think Kurzweil believes we can solve the biotech threat and other risks though building superintelligence.

Stuart Russell believes that a) we should be exactly sure what we want before we let the AI genie out of the bottle, and b) it’s a technological problem in much the same way as the containment of nuclear fusion is a technological problem.

Max Tegmark says we should both welcome and fear the Technological Singularity. We shouldn’t just bumble into it unprepared. All technologies have been double edged swords – in the past we learned from mistakes (i.e. with out of control fires) but with AI we may only get one chance.

Harry Shum says we should be focussing on what we believe we can develop with AI in the next few decades. We find it difficult to talk about AGI. Most of the social fears are around killer robots.

Maggie Boden

Maggie Boden

Maggie Boden poses an audience question about how will AI cope with our lack of development in ethical and moral norms?

Stuart Russell answers that machines have to come to understand what human values are. If the first sudo-general-purpose AI’s don’t get human values well enough they may end up cooking it’s owners cat – this could irreparably tarnish the AI and home robot industry.

Kurzweil adds that human society is getting more ethical – it seems that statistically we are making ethical progress.

Max Tegmark

Max Tegmark

Max Tegmark brings up that intelligence is defined by the degree of ability to achieve goals – so we can’t ignore the question of what goals to give the system if we are building highly intelligent AI. We need to make AI systems understand what humans really want, not what they say they want.

Harry Shum says that the important ethical question for AI systems needs to address data and user privacy.

Panelists: Harry Shum (Microsoft Research EVP of Tech), Max Tegmark (Cosmologist, MIT) Stuart Russell (Prof. of Computer Science, UC Berkeley) and Ray Kurzweil (Futurist, Google Director of Engineering). Moderator: Margaret Boden (Prof. of Cognitive Science, Uni. of Sussex).

This debate is from the 2015 edition of the meeting, held in Gothenburg, Sweden on 9 Dec.