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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.

Michio Kaku on the Holy Grail of Nanotechnology

Michio Kaku on Nanotechnology – Michio is the author of many best sellers, recently the Future of the Mind!

The Holy Grail of Nanotechnology

Merging with machines is on the horizon and Nanotechnology will be key to achieving this. The ‘Holy Grail of Nanotechnology’ is the replicator: A microscopic robot that rearranges molecules into desired structures. At the moment, molecular assemblers exist in nature in us, as cells and ribosomes.

Sticky Fingers problem

How might nanorobots/replicators look and behave?
Because of the ‘Sticky /Fat Fingers problem’ in the short term we won’t have nanobots with agile clippers or blow torches (like what we might see in a scifi movie).

The 4th Wave of High Technology

Humanity has seen an acceleration in history of technological progress from the steam engine and industrial revolution to the electrical age, the space program and high technology – what is the 4th wave that will dominate the rest of the 21st century?
Nanotechnology (molecular physics), Biotechnology, and Artificial Intelligence (reducing the curcuitry of the brain down to neurons) – “these three molecular technologies will propel us into the future”!

 

Michio Kaku – Bio

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)

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Amazing Progress in Artificial Intelligence – Ben Goertzel

At a recent conference in Beijing (the Global Innovators Conference) – I did yet another video interview with the legendary AGI guru – Ben Goertzel. This is the first part of the interview, where he talks about some of the ‘amazing’ progress in AI over recent years, including Deep Mind’s AlphaGo sealing a 4-1 victory over Go grandmaster Lee Sedol, progress in hybrid architectures in AI (Deep Learning, Reinforcement Learning, etc), interesting academic research in AI being taken up by tech giants, and finally providing some sobering remarks on the limitations of deep neural networks.

The future of neuroscience and understanding the complexity of the human mind – Brains and Computers

Two of the world’s leading brain researchers will come together to discuss some of the latest international efforts to understand the brain. They will discuss two massive initiatives – the US based Allen Institute for Brain Science and European Human Brain Project. By combining neuroscience with the power of computing both projects are harnessing the efforts of hundreds of neuroscientists in unprecedented collaborations aimed at unravelling the mysteries of the human brain.

This unique FREE public event, hosted by ABC Radio and TV personality Bernie Hobbs, will feature two presentations by each brain researcher followed by an interactive discussion with the audience.

This is your chance to ask the big brain questions.

[Event Registration Page] | [Meetup Event Page]

ARC Centre of Excellence for Integrative Brain Function

Monday, 3 April 2017 from 6:00 pm to 7:30 pm (AEST)

Melbourne Convention and Exhibition Centre
2 Clarendon Street
enter via the main Exhibition Centre entrance, opposite Crown Casino
South Wharf, VIC 3006 Australia

Professor Christof Koch
President and Chief Scientific Officer, Allen Institute for Brain Science, USA

Professor Koch leads a large scale, 10-year effort to build brain observatories to map, analyse and understand the mouse and human cerebral cortex. His work integrates theoretical, computational and experimental neuroscience. Professor Koch pioneered the scientific study of consciousness with his long-time collaborator, the late Nobel laureate Francis Crick. Learn more about the Allen Institute for Brain Science and Christof Koch.

Professor Karlheinz Meier
Co-Director and Vice Chair of the Human Brain Project
Professor of Physics, University of Heidelberg, Germany

Professor Meier is a physicist working on unravelling theoretical principles of brain information processing and transferring them to novel computer architectures. He has led major European initiatives that combine neuroscience with information science. Professor Meier is a co-founder of the European Human Brain Project where he leads the research to create brain-inspired computing paradigms. Learn more about the Human Brain Project and Karlheinz Meier.

 

 

This event is brought to you by the Australian Research Council Centre of Excellence for Integrative Brain Function.

Discovering how the brain interacts with the world.

The ARC Centre of Excellence for Integrative Brain Function is supported by the Australian Research Council.

Building Brains – How to build physical models of brain circuits in silicon

Event Description: The brain is a universe of 100 billion cells interacting through a constantly changing network of 1000 trillion synapses. It runs on a power budget of 20 Watts and holds an internal model of the world.   Understanding our brain is among the key challenges for science, on equal footing with understanding genesis and the fate of our universe. The lecture will describe how to build physical, neuromorphic models of brain circuits in silicon. Neuromorphic systems can be used to gain understanding of learning and development in biological brains and as artificial neural systems for cognitive computing.

Event Page Here | Meetup Event Page Here

Date: Wednesday 5 April 2017 6-7pm

Venue:  Monash Biomedical Imaging 770 Blackburn Road Clayton

Karlheinz Meier

Karlheinz Meier (* 1955) received his PhD in physics in 1984 from Hamburg University in Germany. He has more than 25 years of experience in experimental particle physics with contributions to 4 major experiments at particle colliders at DESY in Hamburg and CERN in Geneva. After fellowships and scientific staff positions at CERN and DESY he was appointed full professor of physics at Heidelberg University in 1992. In Heidelberg he co-founded the Kirchhoff-Institute for Physics and a laboratory for the development of microelectronic circuits for science experiments. For the ATLAS experiment at the Large Hadron Collider (LHC) he led a 10-year effort to design and build a large-scale electronic data processing system providing on-the-fly data reduction by 3 orders of magnitude enabling among other achievements the discovery of the Higgs Boson in 2012. In particle physics he took a leading international role in shaping the future of the field as president of the European Committee for Future Accelerators (ECFA).
Around 2005 he gradually shifted his scientific interests towards large-scale electronic implementations of brain-inspired computer architectures. His group pioneered several innovations in the field like the conception of a platform-independent description language for neural circuits (PyNN), time-compressed mixed-signal neuromorphic computing systems and wafer-scale integration for their implementation. He led 2 major European initiatives, FACETS and BrainScaleS, that both demonstrated the rewarding Interdisciplinary collaboration of neuroscience and information science. In 2009 he was one of the initiators of the European Human Brain Project (HBP) that was approved in 2013. In the HBP he leads the subproject on neuromorphic computing with the goal of establishing brain-inspired computing paradigms as research tools for neuroscience and generic hardware systems for cognitive computing, a new way of processing and interpreting the spatio-temporal structure of large data volumes. In the HBP he is a member of the project directorate and vice-chair of the science and infrastructure board.
Karlheinz Meier engages in public dissemination of science. His YouTube channel with physics movies has received more than a Million hits and he delivers regular lectures to the public about his research and general science topics.

 

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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AI: The Story So Far – Stuart Russell

stuart russell - redAwesome to have Stuart Russell discussing AI Safety – a very important topic. Too long have people been associating the idea of AI safety issues with Terminator – unfortunately the human condition seems such that people often don’t give themselves permission to take seriously non-mainstream ideas unless they see a tip of the hat from an authority figure.

During the presentation Stuart brings up a nice quote by Norbert Wiener:

If we use, to achieve our purposes, a mechanical agency with whose operation we cannot efficiently interfere once we have started it, because the action is so fast and irrevocable that we have not the data to intervene before the action is complete, then we had better be quite sure that the purpose put into the machine is the purpose which we really desire and not merely a colorful imitation of it.Norbert Wiener

P.s. Stuart Russell co-authored AI A Modern Approach with Peter Norvig – arguably the most popular textbook on AI theory.

The lecture was presented at the 2016 Colloquium Series on Robust and Beneficial AI (CSRBAI) hosted by the Machine Intelligence Research Institute (MIRI) and Oxford’s Future of Humanity Institute (FHI).

What I’m finding is that senior people in the field who have never publicly evinced any concern before are privately thinking that we do need to take this issue very seriously, and the sooner we take it seriously the better.Stuart Russell

Video of presentation:

 

The field [of AI] has operated for over 50 years on one simple assumption: the more intelligent, the better. To this must be conjoined an overriding concern for the benefit of humanity. The argument is very simple:

1. AI is likely to succeed.
2. Unconstrained success brings huge risks and huge benefits.
3. What can we do now to improve the chances of reaping the benefits and avoiding the risks?

Some organizations are already considering these questions, including the Future of Humanity Institute at Oxford, the Centre for the Study of Existential Risk at Cambridge, the Machine Intelligence Research Institute in Berkeley, and the Future of Life Institute at Harvard/MIT. I serve on the Advisory Boards of CSER and FLI.

Just as nuclear fusion researchers consider the problem of containment of fusion reactions as one of the primary problems of their field, it seems inevitable that issues of control and safety will become central to AI as the field matures. The research questions are beginning to be formulated and range from highly technical (foundational issues of rationality and utility, provable properties of agents, etc.) to broadly philosophical.

– Stuart Russell (Quote Source)

Nick Bostrom: Why Focus on Existential Risk related to Machine Intelligence?

One can think of Existential Risk as a subcategory of a Global Catastrophic Risk – while GCR’s are really bad, civilization has the potential to recover from such a global catastrophic disaster.
An existential Risk is one in which there is no chance of recoverability. An example of the sort of disaster that fits the category of existential risk is human extinction which reduces the probability of [human] lives worth living – theories of value that imply even relatively small reductions in net existential risk have enormous expected value mostly fall under population ethics that consider an average or total utilitarian view of the well-being of the future of life in the universe.  Since we haven’t seen any convincing evidence of life outside earth’s gravity well, it may be that there is no advanced technologically capable life elsewhere in the observable universe.  If we value lives worth living, and lots of lives worth living, we might also value filling the uninhabited parts of the universe with lives worth living – and arguably we need an advanced technologically able civilization to achieve this.  Hence, if humans become extinct it may be that evolution will never again produce a life form capable of escaping the gravity well and colonizing the universe with valuable life.

Here we focus on the reasons to focus on Existential Risk related to machine intelligence.

Say machine intelligence is created with a theory of value outside of, contradictory to, or simply different enough to one in which valued human existence, or the existence of valuable life in the universe.  Also imagine that this machine intelligence could enact on it’s values in an exacting manner – it may cause humanity to become extinct on purpose, or as a side effect of implementing it’s values.

The paper ‘Existential Risk Prevention as Global Priority‘ by Nick Bostrom clarifies the concept of existential risk further:

Existential risks are those that threaten the entire future of humanity. Many theories of value imply that even relatively small reductions in net existential risk have enormous expected value. Despite their importance, issues surrounding human-extinction risks and related hazards remain poorly understood. In this paper, I clarify the concept of existential risk and develop an improved classification scheme. I discuss the relation between existential risks and basic issues in axiology, and show how existential risk reduction (via the maxipok rule) can serve as a strongly action-guiding principle for utilitarian concerns. I also show how the notion of existential risk suggests a new way of thinking about the ideal of sustainability. http://www.existential-risk.org

Interview with Nick Bostrom on Machine Intelligence and XRisk

I had the pleasure of doing an interview with Oxford philosopher Nick Bostrom on XRisk:

Transcription of interview:

In recent couple of years we’ve been focusing quite heavily on machine intelligence partly because it seems to raise some significant existentialist down the road part also because relatively little attention has been given to this risk. So when we are prioritizing what we want to spend our time researching then one variable that we take into account is how important is this topic that we could research? But another is how many other people are there who are already studying it? Because the more people who already studying it – the smaller the difference that having a few extra minds focusing on that topic.
So, say the topic of peace and war and how you can try to avoid international conflict is a very important topic – and many existential risks will be reduced if there is more global corporation.
However it is also hard to see how a very small group of people could make a substantial difference to today’s risk of arms races and wars. There is a big interest involved in this and so many people already working either on disarmament and peace and/or military strength that it’s an area where it would be great to make a change – but it’s hard to make a change if there are a smaller number people by contrast with something like the risk from machine intelligence and the risk of Super-Intelligence.
Only been a relatively small number of people have been thinking about this and there might be some low-hanging fruit there – some insights that might make a big difference. So that’s one of the criteria.
Now we are also looking at other existential risks and we are also looking at things other than existential risk like – with try to get a better understanding of what humanity’s situation is in the world and so we have been thinking some about the Fermi Paradox for example, some methodological tools that you need like observation selection theory how you can reason about these things. And to some extent also more near term impacts of technology and of course the opportunities involved in all of this – is that always worth to remind oneself that although enormous technological powers will pose great new dangers including existential risks they also of course make it possible to achieve enormous amount of good.
So one should bear in mind this ..the opportunities as well that are unleashed with technological advance.

About Professor Nick Bostrom

Director & James Martin Research Fellow

Bostrom Xrisk 2Nick Bostrom is Professor in the Faculty of Philosophy at Oxford University and founding Director of the Future of Humanity Institute and of the Programme on the Impacts of Future Technology within the Oxford Martin School. He is the author of some 200 publications, including Anthropic Bias (Routledge, 2002), Global Catastrophic Risks (ed., OUP, 2008), and Human Enhancement (ed., OUP, 2009), and a forthcoming book on Superintelligence. He previously taught at Yale, and he was a Postdoctoral Fellow of the British Academy. Bostrom has a background in physics, computational neuroscience, and mathematical logic as well as philosophy.

He is best known for his work in five areas: (i) the concept of existential risk; (ii) the simulation argument; (iii) anthropics (developing the first mathematically explicit theory of observation selection effects); (iv) transhumanism, including related issues in bioethics and on consequences of future technologies; and (v) foundations and practical implications of consequentialism. He is currently working on a book on the possibility of an intelligence explosion and on the existential risks and strategic issues related to the prospect of machine superintelligence.

In 2009, he was awarded the Eugene R. Gannon Award (one person selected annually worldwide from the fields of philosophy, mathematics, the arts and other humanities, and the natural sciences). He has been listed in the FP 100 Global Thinkers list, the Foreign Policy Magazine’s list of the world’s top 100 minds. His writings have been translated into more than 21 languages, and there have been some 80 translations or reprints of his works. He has done more than 500 interviews for TV, film, radio, and print media, and he has addressed academic and popular audiences around the world.

CV: http://www.nickbostrom.com/cv.pdf

Personal Web: http://www.nickbostrom.com

FHI Bio: https://www.fhi.ox.ac.uk/about/the-team/

Also consider joining the Facebook Group on Existential Risk: https://www.facebook.com/groups/ExistentialRisk

Conference: Thinking Machines in the Physical World

“Thinking Machines in the Physical World” invites cross-disciplinary conversations about the opportunities and threats presented by advances in cognitive computing:
  – What concrete, real-world possibilities does intelligence-focused technology open up?
  – What potential effects will “smart computers” exert on labor and jobs around the globe?
  – What are the broader social implications of these changes?

When: Wednesday, July 13, 2016 8:30 AM until Friday ~6pm (then dinner)
Where: Melbourne Uni Law School Building, Level 10 185 Pelham Street, Carlton

Keynotes (see details here):

Prof Brian Anderson – Distinguished Professor at ANU College of Engineering and Computer Science.

Dr James Hughes – Executive Director of the Institute for Ethics and Emerging Technologies.

Prof M. Vidyasagar – Cecil & Ida Green Chair in Systems Biology Science

Prof Judy Wajcman – Anthony Giddens Professor of Sociology, London School of Economics

Dr. Juerg von Kaenel, IBM Research – Cognitive Computing – IBM Watson

Register here | Main website | Program

Professor Graeme Clark, AC Laureate Professor Emeritus  says “It gives me great pleasure to have the opportunity to welcome your interest in the work of Norbert Wiener and invite you to Melbourne to participate in this important conference.”

Official Website: http://21stcenturywiener.org/
Video: https://www.youtube.com/watch?v=etBMY6Orj50
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