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AGI Progress & Impediments – Progress in Artificial Intelligence Panel

Panelists: Ben Goertzel, David Chalmers, Steve Omohundro, James Newton-Thomas – held at the Singularity Summit Australia in 2011

Panelists discuss approaches to AGI, progress and impediments now and in the future.
Ben Goertzel:
Ben Goertzle with backdrop of headsBrain Emulation, Broad level roadmap simulation, bottleneck, lack of imaging technology, we don’t know what level of precision we need to reverse engineer biological intelligence. Ed Boyed – optimal brain imageing.
Not by Brain emulation (engineering/comp sci/cognitive sci), bottleneck is funding. People in the field believe/feel they know how to do it. To prove this, they need to integrate their architectures which looks like a big project. Takes a lot of money, but not as much as something like Microsoft Word.

David Chalmers (time 03:42):
DavidChalmersWe don’t know which of the two approaches. Though what form the singularity will take will likely be dependent on the approach we use to build AGI. We don’t understand the theory yet. Most don’t think we will have a perfect molecular scanner that scans the brain and its chemical constituents. 25 Years ago David Chalmers worked in Douglass Hofstadter’s AI lab, but his expertise in AI is now out of date. To get to Human Level AI by brute force or through cognitive psychology knows that the cog-sci is not in very good shape. Third approach is a hybrid of ruffly brain augmentation (through technology we are already using like ipads and computers etc) and technological extension and uploading. If using brain augmentation through tech and uploading as a first step in a Singularity then it is including Humans in the equation along with humanities values which may help shape a Singularity with those values.

Steve Omohundro (time 08:08):
steve_omohundro_headEarly in history AI, there was a distinction: The Neats and the Scruffies. John McCarthy (Stanford AI Lab) believed in mathematically precise logical representations – this shaped a lot of what Steve thought about how programming should be done. Marvin Minsky (MIT Lab) believed in exploring neural nets and self organising systems and the approach of throwing things together to see how it self-organises into intelligence. Both approaches are needed: the logical, mathematically precise, neat approach – and – the probabilistic, self-organising, fuzzy, learning approach, the scruffy. They have to come together. Theorem proving without any explorative aspect probably wont succeed. Purely Neural net based simulations can’t represent semantics well, need to combine systems with full semantics and systems with the ability to adapt to complex environments.

James Newton-Thomas (time 09:57)
james.newton-thomasJames has been playing with Neural-nets and has been disappointed with them not being thinks that Augmentation is the way forward. The AI problem is going to be easier to solve if we are smarter to solve it. Conferences such as this help infuse us with a collective empowerment of the individuals. There is an impediment – we are already being dehumanised with our Ipad, where the reason why we are having a conversation with others is a fact about our being part of a group and not about the information that can be looked up via an IPad. We need to careful in our approach so that we are able to maintain our humanity whilst gaining the advantages of the augmentation.

General Discussion (time 12:05):
David Chalmers: We are already becoming cyborgs in a sense by interacting with tech in our world. the more literal cyborg approach we are working on now. Though we are not yet at the point where the technology is commercialization to in principle allow a strong literal cyborg approach. Ben Goertzel: Though we could progress with some form of brain vocalization (picking up words directly from the brain), allowing to think a google query and have the results directly added to our mind – thus bypassing our low bandwidth communication and getting at the information directly in our heads. To do all this …
Steve Omohundro: EEG is gaining a lot of interest to help with the Quantified Self – brain interfaces to help measure things about their body (though the hardware is not that good yet).
Ben Goertzel: Use of BCIs for video games – and can detect whether you are aroused and paying attention. Though the resolution is very course – hard to get fine grained brain state information through the skull. Cranial jacks will get more information. Legal systems are an impediment.
James NT: Alan Snyder using time altering magnetic fields in helmets that shut down certain areas of the brain, which effectively makes people smarter in narrower domains of skill. Can provide an idiot savant ability at the cost of the ability to generalize. The brain that becomes to specific at one task is doing so at the cost of others – the process of generalization.

Ben Goertzel, David Chalmers, Steve Omohundro - A Thought Experiment

Ben Goertzel, David Chalmers, Steve Omohundro – A Thought Experiment

Automating Science: Panel – Stephen Ames, John Wilkins, Greg Restall, Kevin Korb

A discussion among philosophers, mathematicians and AI experts on whether science can be automated, what it means to automate science, and the implications of automating science – including discussion on the technological singularity.

– implementing science in a computer – Bayesian methods – most promising normative standard for doing inductive inference
– vehicle : causal Bayesian networks – probability distributions over random variables showing causal relationships
– probabilifying relationships – tests whose evidence can raise the probability

05:23 does Bayesianism misrepresent the majority of what people do in science?

07:05 How to automate the generation of new hypotheses?
– Is there a clean dividing line between discovery and justification? (Popper’s view on the difference between the context of discovery and context of justification) Sure we discuss the difference between the concepts – but what is the difference between the implementation?

08:42 Automation of Science from beginning to end: concept formation, discovery of hypotheses, developing experiments, testing hypotheses, making inferences … hypotheses testing has been done – through concept formation is an interestingly difficult problem

Panel---Automating-Science-and-Artificial-Intelligence---Kevin-Korb,-Greg-Restall,-John-Wilkins,-Stephen-Ames-1920x10839:38 – does everyone on the panel agree that automation of science is possible? Stephen Ames: not yet, but the goal is imminent, until it’s done it’s an open question – Kevin/John: logically possible, question is will we do it – Greg Restall: Don’t know, can there be one formal system that can generate anything classed as science? A degree of open-endedness may be required, the system will need to represent itself etc (Godel!=mysticism, automation!=representing something in a formal deductive theory)

13:04 There is a Godel theorem that applies to a formal representation for automating science – that means that the formal representation can’t do everything – therefore what’s the scope of a formal system that can automate science? What will the formal representation and automated science implementation look like?

14:20 Going beyond formal representations to automate science (John Searle objects to AI on the basis of formal representations not being universal problem solvers)

15:45 Abductive inference (inference to the best explanation) – & Popper’s pessimism about a logic of discovery has no foundation – where does it come from? Calling it logic (if logic means deduction) is misleading perhaps – abduction is not deductive, but it can be formalised.

17:10 Some classified systems fall out of neural networks or clustering programs – Google’s concept of a cat is not deductive (IFAIK)

19:29 Map & territory – Turing Test – ‘if you can’t tell the difference between the model and the real system – then in practice there is no difference’ – the behavioural test is probably a pretty good one for intelligence

22:03 Discussion on IBM Watson on Jeopardy – a lot of natural language processing but not natural language generation

24:09 Bayesianism – in mathematics and in humans reasoning probabilistically – it introduced the concept of not seeing everything in black and white. People get statistical problems wrong often when they are asked to answer intuitively. Is the technology likely to have a broad impact?

26:26 Human thinking, subjective statistical reasoning – and the mismatch between the public communicative act often sounding like Boolean logic – a mismatch between our internal representation and the tools we have for externally representing likelihoods
29:08 Low hanging fruit in human communication probabilistic reasoning – Bayesian nets and argument maps (Bayesian nets strengths between premises and conclusions)

29:41 Human inquiry, wondering and asking questions – how do we automate asking questions (as distinct from making statements)? Scientific abduction is connected to asking questions – there is no reason why asking questions can’t be automated – there is contrasted explanations and conceptual space theory where you can characterise a question – causal explanation using causal Bayesian networks (and when proposing an explanation it must be supported some explanatory context)

32:29 Automating Philosophy – if you can automate science you can automate philosophy –

34:02 Stanford Computational Metaphysics project (colleagues with Greg Restall) – Stanford Computational Metaphysics project – formalization of representations of relationships between concepts – going back to Leibniz – complex notions can be boiled down to simpler primitive notions and grinding out these primitive notions computationally – they are making genuine discoveries
Weak Reading: can some philosophy be automated – yes
Strong Reading of q: can All of philosophy be automated? – there seem to be some things that count as philosophy that don’t look like they will be automated in the next 10 years

35:41 If what we’re is interested in is to represent and automate the production of reasoning formally (not only to evaluate), as long as the domain is such that we are making claims and we are interested in the inferential connections between the claims, then a lot of the properties of reasoning are subject matter agnostic.

36:46 (Rohan McLeod) Regarding Creationism is it better to think of it as a poor hypothesis or non-science? – not an exclusive disjunct, can start as a poor hypothesis and later become not-science or science – it depends on the stage at the time – science rules things out of contention – and at some point creationism had not been ruled out

38:16 (Rohan McLeod) Is economics a science or does it have the potential to be (or is it intrinsically not possible for it to be a science) and why?
Are there value judgements in science? And if there are how do you falsify a hypothesis that conveys a value judgement? physicists make value judgements on hypothesis “h1 is good, h2 is bad” – economics may have reducible normative components but physics doesn’t (electrons aren’t the kinds of things that economies are) – Michael ??? paper on value judgements – “there is no such thing as a factual judgement that does not involve value” – while there are normative components to economics, it is studied from at least one remove – problem is economists try to make normative judgements like “a good economy/market/corporation will do X”

42:22 Problems with economics – incredibly complex, it’s hard to model, without a model exists a vacuum that gets filled with ideology – (are ideologies normative?)

42:56 One of the problems with economics is it gets treated like a natural system (in physics or chemistry) which hides all the values which are getting smuggled in – commitments and values which are operative and contribute to the configuration of the system – a contention is whether economics should be a science (Kevin: Yes, Stephen: No) – perhaps economics could be called a nascent science (in the process of being born)

44:28 (James Fodor) Well known scientists have thought that their theories were implicit in nature before they found them – what’s the role of intuition in automating science & philosophy? – need intuitions to drive things forward – intuition in the abduction area – to drive inspiration for generating hypothesis – though a lot of what get’s called intuition is really the unconscious processing of a trained mind (an experienced driver doesn’t have to process how to drive a car) – Louis Pasteur’s prepared mind – trained prior probabilities

46:55 The Singularity – disagreement? John Wilkins suspects it’s not physically possible – Where does Moore’s Law (or its equivalents in other hardware paradigms) peter out? The software problem could be solved near or far. Kevin agrees with I.J. Good – recursively improving abilities without (obvious) end (within thermodynamic limits). Kevin Korb explains the intelligence explosion.

50:31 Stephen Ames discusses his view of the singularity – but disagrees with uploading on the grounds of needing to commit to philosophical naturalism

51:52 Greg Restall mistrusts IT corporations to get uploading right – Kevin expresses concerns about using star-trek transporters – the lack of physical continuity. Greg discusses theories of intelligence – planes fly as do birds, but planes are not birds – they are differing

54:07 John Wilkins – way too much emphasis is put on propositional knowledge and communication in describing intelligence – each human has roughly the same amount of processing power – too much rests on academic pretense and conceit.

54:57 The Harvard Rule – under conditions of consistent lighting, feeding etc – the organism will do as it damn well pleases. But biology will defeat simple models.. Also Hulls rule – no matter what the law in biology is there is an exception (inc Hull’s law) – so simulated biology may be difficult. We won’t simulate an entire organism – we can’t simulate a cell. Kevin objects

58:30 Greg R. says simulations and models do give us useful information – even if we isolate certain properties in simulation that are not isolated in the real world – John Wilkins suggests that there will be a point where it works until it doesn’t

1:00:08 One of the biggest differences between humans and mice is 40 million years of evolution in both directions – the problem is in evo biol is your inductive projectability – we’ve observed it in these cases, therefore we expect it in this – it fades out relatively rapidly in direct disproportion to the degree of relatedness

1:01:35 Colin Kline – PSYCHE – and other AI programs making discoveries – David Chalmers have proposed the Hard Problem of Consciousness – pZombies – but we are all pZombies, so we will develop systems that are conscious because there is to such thing as consciousness. Kevin is with Dennet – info processing functioning is what consciousness supervenes upon
Greg – concept formation in systems like PSYCHE – but this milestone might be very early in the development of what we think of as agency – if the machine is worried about being turned off or complains about getting board, then we are onto something

Utopias in Fiction and Future – Cory Doctorow

Interview with Cory Doctorow on Utopias by Adam Ford
00:11 Kim Stanley Robinson is absolutely my favorite utopian because he depicts in his utopias not worlds where all problems have been solved, but worlds in which the collective and action problem – of how we get along while we solve problems – has been in large part solved. He writes worlds in not where there has been no disaster, but in which disaster has been attended by kindness, conscientiousness and a sense of shared human destiny as opposed to greed and fear and a sense of individual destiny – that kind of Mad Max future where the only way to survive is at the expense of everyone else. And that to me is the genuinely optimistic prediction – because we live in a dynamic universe right? Whatever works today will no longer work tomorrow because something will have changed by tomorrow – and so the important thing isn’t whether all the circumstances are good – the important thing is what happens when the circumstances are poor – it’s not how well the system works, it’s what happens when it fails that distinguishes a utopia from a dystopia.

Cory Doctorow - Utopias in Fiction and Future01:21 So you take Stan Robinson and a book like 2312 – that’s a book that has futures that are every bit as grim as ‘The Road’ by Cormac McCarthy – but the reason that Stan’s book is a utopia and McCarthy’s book is a dystopia is that McCarthy visits upon the human race the slander that when the lights go out people go over to their neighbours house and kill them and eat them – literally in the case of McCarthy – and Robinson aspires to a future that when the lights go out people go over to their neighbours housea and see how they can help – you know – that when the power fails people open their freezers and barbecue everything inside them – because it’s going to thore out anyways – and share it with their neighbours.

02:06 And you know, books like ‘Paradise Made in Hell’ by Rebecca Solnit document systematically how in times of disaster we have a narrative – especially those of us at a distance – that is both racialized and tinged with class anxiety about poor people acting in a barbaric way and visiting upon the rich, you know, a kind of vengeance for inequality – but that when you actually look upon the ground, that apart from elites who are gripped in a panic of their own making about this coming vengeance – this sense, I guess, of a kind of retributive guilt, you know, they having lived so high off the hog for so many years in the midst of people with nothing, that surely vengeance must be soon. But actual normal people just kind of help each other out – and that where you see horrific violence, it is almost always the fault of an anticipatory pre-emptive violence against everyday people on the grounds that they must be on the verge of breaking loose into barbarism – the pre-emptive shooting of looters, that sort of thing.

03:26 Looting in times of existential disaster is really just liberating of supplies. And literally in the case of Hurricane Katrina CNN aired footage of white people breaking into chemist shops and taking medicine, water and food – and describing it as ‘commandeering’ – and black people doing the same things and describing it as ‘looting’. So that elite panic is one of the most horrific narratives we have, and is itself a source of unimaginable suffering in times of crisis. And so utopianism is not just important as a way of thinking about the human race but as countervailing force to that narrative as a way of keeping people from assuming that their neighbours are going to come over and eat them so going over and preemptively shooting their neighbours before it happens.

It’s not how well the system works, it’s what happens when it fails that distinguishes a Utopia from a DystopiaCory Doctorow

– Thanks to Andrew Dun who helped film
Cory Doctorow wrote an interesting review that is very relevant to this interview: ‘Kim Stanley Robinson’s 2312: a novel that hints at what we might someday have (and lose)

Biography

Cory Efram Doctorow is a Canadian-British blogger, journalist, and science fiction author who serves as co-editor of the weblog Boing Boing. He is an activist in favour of liberalising copyright laws and a proponent of the Creative Commons organization, using some of their licenses for his books. Some common themes of his work include digital rights management, file sharing, and post-scarcity economics.

Doctorow began selling fiction when he was 17 years old and sold several stories followed by publication of his story “Craphound” in 1998.

Down and Out in the Magic Kingdom, Doctorow’s first novel, was published in January 2003, and was the first novel released under one of the Creative Commons licences, allowing readers to circulate the electronic edition as long as they neither made money from it nor used it to create derived works. The electronic edition was released simultaneously with the print edition. In March 2003, it was re-released with a different Creative Commons licence that allowed derivative works such as fan fiction, but still prohibited commercial usage. It was nominated for a Nebula Award, and won the Locus Award for Best First Novel in 2004. A semi-sequel short story named Truncat was published on Salon.com in August 2003.

Doctorow’s other novels have been released with Creative Commons licences that allow derived works and prohibit commercial usage, and he has used the model of making digital versions available, without charge, at the same time that print versions are published.

His Sunburst Award-winning short story collection A Place So Foreign and Eight More was also published in 2004: “0wnz0red” from this collection was nominated for the 2004 Nebula Award for Best Novelette.

Doctorow released the bestselling novel Little Brother in 2008 with a Creative Commons Attribution-Noncommercial-ShareAlike licence. It was nominated for a 2009 Hugo Award, and won the 2009 Prometheus Award, Sunburst Award, and the John W. Campbell Memorial Award.

His novel Makers was released in October 2009, and was serialized for free on the Tor Books website.

Doctorow released another young adult novel, For The Win, in May 2010. The novel is available free on the author’s website as a Creative Commons download, and is also published in traditional paper format by Tor Books. The book concerns massively multiplayer online role-playing games.

Doctorow’s short story collection “With a Little Help” was released in printed format on May 3, 2011. It is a project to demonstrate the profitability of Doctorow’s method of releasing his books in print and subsequently for free under Creative Commons.

In September 2012, Doctorow released The Rapture of the Nerds, a novel written in collaboration with Charles Stross. In February 2013, Doctorow released Homeland, the sequel to his novel Little Brother.

Doctorow’s young adult novel, Pirate Cinema, was released in October 2012, and won the 2013 Prometheus Award.

Science, Technology & the Future

Vernor Vinge on the Turing Test, Artificial Intelligence

Preface

the_imitation_game_bOn the coat-tails of a the blockbuster film “The Imitation Game” I saw quite a bit of buzz on the internet about Alan Turing, and the Turing Test.  The title of the movie refers to the idea of the Turing Test may someday show that machines would ostensibly be (at least in controlled circumstances) indistinguishable from humans.
Vernor Vinge is a mathematician and science fiction author who is well known for many Hugo Award-winning novels and novellas*   and his 1993 essay “The Coming Technological Singularity”, in which he argues that the creation of superhuman artificial intelligence will mark the point at which “the human era will be ended”, such that no current models of reality are sufficient to predict beyond it.

 

Alan Turing and the Computability of Intelligence

Adam Ford: Alan Turing is considered the “Father of Theoretical Computer Science and Artificial Intelligence” – his view about the potential of AI contrasts with much of the skepticism that has subsequently arose.  What is at the root of this skepticism?

Vinge_Singularity_Omni_face250x303Vernor Vinge: The emotional source of the skepticism is the ineffable feeling that many (most?)  people have against the possibility that self-awareness could arise from simple, constructed devices.

 

AF: Many theorists feel that the combined talents of pure machines and humans will always produce more creative and therefore useful output – what are your thoughts?

VV: When it comes to intelligence, biology just doesn’t have legs. _However_ in the near term, teams of people plus machines can be much smarter than either — and this is one of the strongest reasons for being optimistic that we can manage the new era safely, and project that safety into the farther future.

 

AF: Is the human brain essentially a computer?

VV: Probably yes, but if not the lack can very likely be made up for with machine improvements that we humans can devise.

 

AF: Even AI critics John Searle and Hubert Dreyfus (i.e. “What Computers (Still) Can’t Do”) agree that a brain simulation is possible in theory, though they argue that merely mimicking the functioning brain would in itself be an admission of ignorance (concerning intelligence) – what are your thoughts?

VV: The question of whether there is self-awareness behind a mimick may be the most profound issue, but for almost all practical purposes it isn’t relevant: in a few years, I think we will be able to make machines that can run circles around any human mind by all externally measured criteria. So what if no one is really home inside that machine?

Offhand, I can think of only one practical import to the answer, but that _is_ something important: If such minds are self-aware in the human sense, then uploads suddenly become very important to us mortality-challenged beings.

For reductionists interested in _that_ issue, some confidence might be achieved with superintelligence architectures that model those structures in our minds that reductionists come to associate with self-awareness. (I can imagine this argument being carried on by the uploaded supermind children of Searle and Moravec — a trillion years from now when there might not be any biological minds around whatsoever.)

 

AF: Do you think Alan Turing’s reasons for believing in the potential of AI are different from your own and other modern day theorists?  If so in what ways?

VV: My guess is there is not much difference.

 

AF: Has Alan Turing and his work influenced your writing? If it has, how so?

VV: I’m not aware of direct influence. As a child, what chiefly influenced me was the science-fiction I was reading! Of course, those folks were often influenced by what was going in science and math and engineering of the time.

Alan Turing has had a multitude of incarnations in science fiction…   I think that besides being a broadly based math and science genius, Turing created accessible connections between classic philosophical questions and current issues.

 

AF: How do you think Alan Turing would respond to the specific concept of the Technological Singularity as described by you in your paper “The Coming Technological Singularity: How to Survive in the Post-Human Era“?

VV: I’d bet that Turing (and many AI pioneers) had extreme ideas about the consequences of superhuman machine intelligence. I’m not sure if Turing and I would agree about the potential for Intelligence Amplification and human/machine group minds.

I’d be _very_ interested in his reaction to modern analysis such as surveyed in Bostrom’s recent _Superintelligence_ book.

 

AF: In True Names, agents seek to protect their true identity. The guardian of the Coven’s castle is named ‘Alan Turing’ – what was the reason behind this?

It was a tip of the hat in Turing’s direction. By the time I wrote this story I had become quite aware of Alan Turing (contrasting with my childhood ignorance that I mentioned earlier).

 

AF: Your first novella Bookworm Run! was themed around brute forcing simpler-than-human-intelligence to super-intelligence (in it a chimpanzee’s intelligence is amplified).  You also explore the area of intelligence amplification in Marooned in Realtime.
Do you think it is possible for a Singularity to bootstrap from brute forcing simple cognitive models? If so do you think Super-Intelligence will be achieved through brute-forcing simple algorithms?

VV: I view “Intelligence Amplification” (IA) as a finessing of the hardest questions by building on top of what already exists. Thus even UI design lies on the path to the Singularity. One could argue that Intelligence Amplification is the surest way of insuring humanity in the super-intelligence (though some find that a very scary possibility in itself).

 

The Turing Test and Beyond

AF: Is the Turing Test important? If so, why, and how does it’s importance match up to tracking progress in Strong AI?

VV: In its general form, I regard the Turing Test as a marvelous, zen-like, bridge between reductionism and the inner feelings most people have about their own self-awareness.  Bravo Dr. Turing!

 

AF: Is a text conversation is ever a valid test for intelligence? Is blackbox testing enough for a valid test for intelligence?

VV: “Passing the Turing Test” depends very much on the setup:
a) The examining human (child? adult? fixated or afflicted adult? –see Sherry Turkle’s examples of college students who passed a chatbot).
b) The duration of the test.
c) The number of human examiners participating.
d) Restrictions on the examination domain.

In _The Emperor’s New Mind_, Penrose has a (mostly negative) critique of the Turing Test. But at the end he says that if the test was very broad, lasting years, and convincing to him (Penrose), then it might be meaningful to talk about a “pass grade”.

 

AF: The essence of Roger Penrose’s argument (in the Emperor’s New Mind)
–  It is impossible for a Turing machine to enumerate all possible Godel sentences. Such a program will always have a Godel sentence derivable from its program which it can never discover
–  Humans have no problem discovering these sentences and seeing the truth of them
And he concludes that humans are not reducible to turing machines.  Do you agree with Roger’s assessment  – Are humans not reducible to turing machines?

VV: This argument depends on comparing a mathematical object (the Turing Machine) with whatever kind of object the speaker considers a “human mind” to be.  As a logical argument, it leaves me dubious.

 

AF: Are there any existing interpretations of the Turing Test that you favour?

VV: I think Penrose’s version (described above) is the most important.

In conversation, the most important thing is that all sides know which flavor of the test they are talking about 🙂

 

AF: You mentioned it has been fun tracking Turing Test contests, what are your thoughts on attempts at passing the Turing Test so far?

VV: So far, it seems to me that the philosophically important thresholds are still far away. Fooling certain people, or fooling people for short periods of time seems to have been accomplished.

 

AF: Is there any specific type of intelligence we should be testing machines for?

VV: There are intelligence tests that would be very interesting to me, but I rather not call them versions of the Turing Test. For instance, I think we’re already in the territory where more and more [forms->sorts] of superhuman forms of creativity and “intuition” are possible.

I think there well also be performance tests for IA and group mind projects.

 

AF: Some argue that testing for ‘machine consciousness’ is more interesting – what are your thoughts?

VV: Again, I’d keep this possibility separate from Turing Test issues, though I do think that a being that could swiftly duplicate itself and ramp intellect up or down per resource and latency constraints would have a vastly different view of reality compared to the severe and static time/space/mortality restrictions that we humans live with.

 

AF: The Turing Test seems like a competitive sport.  Though some interpretations of the Turing Test have conditions which seem to be quite low.  The competitive nature of how the Turing Test is staged seems to me to select for the cheapest and least sophisticated methods to fool judges on a Turing Test panel.

VV: Yes.

 

AF: Should we be focusing on developing more complex and adaptive Turing style tests (more complex measurement criteria? more complex assessment)? What alternatives to a Turing Test competition (if any) would you suggest to motivate regular testing for machine intelligence?

VV: The answers to these questions may grow out of hard engineering necessity more than from the sport metaphor. Going forward, I imagine that different engineering requirements will acquire various tests, but they may look more like classical benchmark tests.

 

Tracking Progress in Artificial Intelligence

AF: Why is tracking progress towards AI important?

VV: Up to a point it could be important for the sort of safety reasons Bostrom discusses in _Superintelligence_. Such tracking could also provide some guidance for machine/human/society teams that might have the power to guide events along safe paths.

 

AF: What do you see as the most useful mechanisms for tracking progress towards a) human equivalence in AI, b) a Technological Singularity?

VV: The approach to human equivalence might be tracked with a broad range of tests. Such would also apply to the Singularity, but for a soft takeoff, I imagine there would be a lot of economic effects that could be tracked. For example:
–  trends in employment of classic humans, augmented humans, and computer/human teams;
–  trends in what particular jobs still have good employment;
–  changes in the personal characteristics of the most successful CEOs.

Direct tests of automation performance (such as we’ve discussed above) are also important, but as we approach the Singularity, the center of gravity shifts from the programmers to the programs and how the programs are gaming the systems.

 

AF: If you had a tardis and you could bring Alan Turing forward into the 21st century, would he be surprised at progress in AI?  What kinds of progress do you think he would be most interested in?

VV: I don’t have any special knowledge of Turing, but my guess is he would be pleased — and he would want to _understand_ by becoming a super himself.

 

AF: If and when the Singularity becomes imminent – is it likely that the majority of people will be surprised?

VV: A hard takeoff would probably be a surprise to most people. I suspect that a soft takeoff would be widely recognized.

 

Implications

AF: What opportunities could we miss if we are not well prepared (This includes opportunities for risk mitigation)?

VV: Really, the risk mitigation is the serious issue. Other categories of missed opportunities will probably be quickly fixed by the improving tech.  For pure AI, some risk mitigation is the sort of thing MIRI is researching.

For pure AI, IA, and group minds, I think risk mitigation involves making use of the human equivalent minds that already exist in great numbers (namely, the human race). If these teams and early enhancements recognized the issues, they can form a bridge across to the more powerful beings to come.

 

AF: You spoke about an AI Hard Takeoff as being potentially very bad – can you elaborate here?

VV: A hard takeoff is too fast for normal humans to react and accommodate to.  To me, a Hard Takeoff would be more like an explosion than like technological progress. Any failure in mitigation planning is suddenly beyond the ability of normal humans to fix.

 

AF: What stood out for you after reading Nick Bostrom’s book ‘Superintelligence – paths, dangers, strategies’?

VV: Yes. I think it’s an excellent discussion especially of the pure AI path to superintelligence. Even people who have no intense interest in these issues would find the first few chapters interesting, as they sketch out the problematic issues of pure AI superintelligence — including some points that may have been missed back in the twentieth century. The book then proceeds to a fascinating analysis of how to cope with these issues.

My only difference with the analysis presented is that while pure AI is likely the long term important issue, there could well be a period (especially in the case of a Soft Takeoff) where the IA and groupmind trajectories are crucial.

vernor_vinge_LosCon

Vernor Vinge at Los Con 2012

Notes:
* Hugo award winning novels & novellas include: A Fire Upon the Deep (1992), A Deepness in the Sky (1999), Rainbows End (2006), Fast Times at Fairmont High (2002), and The Cookie Monster (2004), and The Peace War (1984).

Also see video interview with Vernor Vinge on the Technological Singularity.

Future Day

Future Day – March 1st

Why are nearly all our holidays focused on celebrating the past, or the cyclical processes of nature? Why not celebrate the amazing future we are collectively creating?

That’s the concept behind a new global holiday, Future Day (March 1), conceived by AI researcher Dr. Ben Goertzel.

past-and-futureFuture Day 2012 gatherings were held in more than a dozen cities, as well as in Second Life. In 2013 there were even more events – 2014 gatherings in Melbourne were fun!
Get in contact and tell us what you want to do for Future Day!

“Celebrating and honoring the past and the cyclical processes of nature is a valuable thing,” says Goertzel. “But in these days of rapid technological acceleration, it is our future that needs more attention, not our past.

“My hope is that Future Day can serve as a tool for helping humanity focus its attention on figuring out what kind of future it wants, and striving to bring these visions to reality.”

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What Sort of Future do You Want?

What sort of future do you want? Future Day is a celebration of imaginative and rational thinking about the future where you can participate.

“Future Day is designed to center the impossible in the public mind once a year as a temptation too delicious to resist.” – Howard Bloom, Author and Publicist

You can use Future Day to harness energy, and help spread the importance of future thinking to a wider audience. Much like Earth Day has. Today with Earth Day there are campaigns to turn off lights, to be more aware of energy consumption, and focus on ecological problems. We hope that Future Day will influence people to take action for a better long term future.
Lets raise a toast to our power to create dramatic new solutions to the problems of today — and let’s have fun in the process. Let’s celebrate the amazing opportunities we have right now to work towards a beneficial future!
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