AI: The Future of Us — a fireside chat with Ron Chrisley and Stephen Upstone

As mentioned in a previous post, I was invited to speak at “AI: The Future of Us” at the British Museum earlier this month.  Rather than give a lecture, it was decided that I should have a “fireside chat” with Stephen Upstone, the CEO and founder of LoopMe, the AI company hosting the event.  We had fun, and got some good feedback, so we’re looking into doing something similar this Autumn — watch this space.

Our discussion was structured around the following questions/topics being posed to me:

  • My background (what I do, what is Cognitive Science, how did I start working in AI, etc.)
  • What is the definition of consciousness and at what point can we say an AI machine is conscious?
  • What are the ethical implications for AI? Will we ever reach the point at which we will need to treat AI like a human? And how do we define AI’s responsibility?
  • Where do you see AI 30 years from now? How do you think AI will revolutionise our lives? (looking at things like smart homes, healthcare, finance, saving the environment, etc.)
  • So on your view, how far away are we from creating a super intelligence that will be better than humans in every aspect from mental to physical and emotional abilities? (Will we reach a point when the line between human and machine becomes blurred?)
  • So is AI not a threat? As Stephen Hawking recently said in the Guardian “AI will be either the best or worst thing for humanity”. What do you think? Is AI something we don’t need to be worried about?

You can listen to our fireside chat here.

What philosophy can offer AI

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My piece on “What philosophy can offer AI” is now up at AI firm LoopMe’s blog. This is part of the run-up to my speaking at their event, “Artificial Intelligence: The Future of Us”, to be held at the British Museum next month.  Here’s what I wrote (the final gag is shamelessly stolen from Peter Sagal of NPR’s “Wait Wait… Don’t Tell Me!”):

Despite what you may have heard, philosophy at its best consists in rigorous thinking about important issues, and careful examination of the concepts we use to think about those issues.  Sometimes this analysis is achieved through considering potential exotic instances of an otherwise everyday concept, and considering whether the concept does indeed apply to that novel case — and if so, how.

In this respect, artificial intelligence (AI), of the actual or sci-fi/thought experiment variety, has given philosophers a lot to chew on, providing a wide range of detailed, fascinating instances to challenge some of our most dearly-held concepts:  not just “intelligence”, “mind”, and “knowledge”, but also “responsibility”, “emotion”, “consciousness”, and, ultimately, “human”.

But it’s a two-way street: Philosophy has a lot to offer AI too.

Examining these concepts allows the philosopher to notice inconsistency, inadequacy or incoherence in our thinking about mind, and the undesirable effects this can have on AI design.  Once the conceptual malady is diagnosed, the philosopher and AI designer can work together (they are sometimes the same person) to recommend revisions to our thinking and designs that remove the conceptual roadblocks to better performance.

This symbiosis is most clearly observed in the case of artificial general intelligence (AGI), the attempt to produce an artificial agent that is, like humans, capable of behaving intelligently in an unbounded number of domains and contexts

The clearest example of the requirement of philosophical expertise when doing AGI concerns machine consciousness and machine ethics: at what point does an AGI’s claim to mentality become real enough that we incur moral obligations toward it?  Is it at the same time as, or before, it reaches the point at which we would say it is conscious?  At when it has moral obligations of its own? And is it moral for us to get to the point where we have moral obligations to machines?  Should that even be AI’s goal?

These are important questions, and it is good that they are being discussed more even though the possibilities they consider aren’t really on the horizon.  

Less well-known is that philosophical sub-disciplines other than ethics have been, and will continue to be, crucial to progress in AGI.  

It’s not just the philosophers that say so; Quantum computation pioneer and Oxford physicist David Deutsch agrees: “The whole problem of developing AGIs is a matter of philosophy, not computer science or neurophysiology”.  That “not” might overstate things a bit (I would soften it to “not only”), but it’s clear that Deutch’s vision of philosophy’s role in AI will not be limited to being a kind of ethics panel that assesses the “real work” done by others.

What’s more, philosophy’s relevance doesn’t just kick in once one starts working on AGI — which substantially increases its market share.  It’s an understatement to say that AGI is a subset of AI in general.  Nearly all, of the AI that is at work now providing relevant search results, classifying images, driving cars, and so on is not domain-independent AGI – it is technological, practical AI, that exploits the particularities of its domain, and relies on human support to augment its non-autonomy to produce a working system. But philosophical expertise can be of use even to this more practical, less Hollywood, kind of AI design.

The clearest point of connection is machine ethics.  

But here the questions are not the hypothetical ones about whether a (far-future) AI has moral obligations to us, or we to it.  Rather the questions will be more like this: 

– How should we trace our ethical obligations to each other when the causal link between us and some undesirable outcome for another, is mediated by a highly complex information process that involves machine learning and apparently autonomous decision-making?  

– Do our previous ethical intuitions about, e.g., product liability apply without modification, or do we need some new concepts to handle these novel levels of complexity and (at least apparent) technological autonomy?

As with AGI, the connection between philosophy and technological, practical AI is not limited to ethics.  For example, different philosophical conceptions of what it is to be intelligent suggest different kinds of designs for driverless cars.  Is intelligence a disembodied ability to process symbols?  Is it merely an ability to behave appropriately?  Or is it, at least in part, a skill or capacity to anticipate how one’s embodied sensations will be transformed by the actions one takes?  

Contemporary, sometimes technical, philosophical theories of cognition are a good place to start when considering what way of conceptualising the problem and solution will be best for a given AI system, especially in the case of design that has to be truly ground breaking to be competitive.

Of course, it’s not all sweetness and light. It is true that there has been some philosophical work that has obfuscated the issues around AI, thereby unnecessarily hindering progress. So, to my recommendation that philosophy play a key role in artificial intelligence, terms and conditions apply.  But don’t they always?

The Ethics of AI and Healthcare

ai-doctor2-570x300I was interviewed by Verdict.co.uk recently about the ethics of AI in healthcare.  One or
two remarks of mine from that interview
are included near the end of this piece that appeared last week:

http://www.verdict.co.uk/the-ai-impact-healthcare-industry-is-changing/

My views are on this are considerably more nuanced than these quotes suggest, so I am thinking of turning my extensive prep notes for the interview into a piece to be posted here and/or on a site like TheConversation.com.  These thoughts are completely distinct from the ones included in the paper Steve Torrance and I wrote a few years back, “Modelling consciousness-dependent expertise in machine medical moral agents“.

Robot crime?

1041809723Yesterday I was interviewed by Radio Sputnik to comment on some recent claims about robot/AI crime.  They have made a transcription and recording of the interview available here.

Some highlights:

“We need to be worried about criminals using AI in three different ways. One is to evade detection: if one has some artificial intelligence technology, one might be able, for instance, to engage in certain kinds of financial crimes in a way that can be randomized in a particular way that avoids standard methods of crime detection. Or criminals could use computer programs to notice patterns in security systems that a human couldn’t notice, and find weaknesses that a human would find very hard to identify… And then finally a more common use might be of AI to just crack passwords and codes, and access accounts and data that people previously could leave secure. So these are just three examples of how AI would be a serious threat to security of people in general if it were in the hands of the wrong people.”

“I think it would be a tragedy if we let fear of remote possibilities of AI systems committing crimes, if that fear stopped us from investigating artificial intelligence as a positive technology that might help us solve some of the problems our world is facing now. I’m an optimist in that I think that AI as a technology can very well be used for good, and if we’re careful, can be of much more benefit than disadvantage.”

“I think that as long as legislators and law enforcement agencies understand what the possibilities are, and understand that the threat is humans committing crimes with AI rather than robots committing crimes, then I think we can head off any potential worries with the appropriate kinds of regulations and updating of our laws.”

What’s really interesting about the dress colour illusion

dress-color-illusionA piece in today’s Guardian (“The Science Behind the Dress Colour Illusion“) quotes me as a primary source, but the exigencies of copy deadlines mean that in a few places my intended meaning was lost.  Here are my (unedited) notes on the matter, which should clarify my comments in the Guardian article that might have left more than a few people scratching their heads: Continue reading

What is colour?

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Fellow Sackler member Jim Parkinson brought to my attention the fact that this year’s Flame Challenge – explaining science to 11-year-olds in less than 300 words – is on the topic “What is Color?”.  I decided to take up the challenge; here’s my entry (299 words!):

The question “what is color?” is tricky.  Understood one way, it hardly needs answering for people with normal vision, who have no problem learning how to use the word “color” and what the names for different colors are: color is just part of the way that things look.   But that answer would be of little use to a blind person, since for them objects don’t “look” any way at all.  Science should try to explain things for everyone, so here’s an explanation of color that works for all people, sighted or blind.
Light is a collection of extremely small particles called photons. A photon might begin its journey at a lamp, bounce off an object (such as a book), and end its journey by being absorbed by one of the cells that line the back wall inside your eye.  Photons wiggle while moving – some wiggle slowly, some quickly.
The color of an object is the mixture of wiggle speeds of photons the object gives off in normal light. 
 
Sighted people can see an object’s color because the way a photon affects their eye cells depends on its wiggle speed.  For example, if your eye absorbs a slow wiggling photon, you see red; a fast wiggling photon, you see blue. Mixtures of wiggle speeds have a mixture of effects on your eye cells, letting you see a mixture of colors.  Something colored white gives off photons of all wiggle speeds.
 
If you shine red light on a white ball it looks red, but its actual color is still white because if it were in normal light it would give off photons of all wiggle speeds.  Similarly, a blue book in the dark is still blue because it would still give off fast wiggling photons were it in normal light. 

Comments welcome.

Barry Smith: “The Mysteries of the Brain”

Steve Torrance says:

I just heard an interview with Barry Smith on Start the Week (Radio 4).

Barry has a series on BBC World Service – see http://tinyurl.com/37k928d

The Mysteries of the Brain
How do our brains work in everyday life?

The experiences that we take for granted – talking to a friend, listening
to a piece of music, lifting a cup of coffee, tasting a peach – depend for
their existence on the intricate and silent workings of several cooperative
regions of the brain.

Why do some people see numbers as coloured? Do we have five or twenty-five
senses? How much of the brain do we need to understand language? Can we
cure chronic pain or depression at the flick of an electrical switch? Do we
decide how to act before we know about it?

For this four-part series, Professor Barry Smith from the Institute of
Philosophy, explores the way neuroscience is addressing the ultimate
scientific challenge: namely, how our brain makes us the conscious
creatures we are – capable of language, thinking and feeling.

The BBC Start the Week programme is repeated tonight, and will soon be
available online:
http://www.bbc.co.uk/programmes/b006r9xr

Cheers

Steve