7 March 2023

What are the minimum conditions for software global catastrophe?

Filed under: AGI, risks — Tags: , — David Wood @ 11:55 am

Should we be seriously concerned that forthcoming new software systems might cause a global catastrophe?

Or are there, instead, good reasons to dismiss any such concern?

(image by Midjourney)

It’s a vitally important public debate. Alas, this debate is bedevilled by false turnings.

For example, dismissers often make claims with this form:

  • The argument for being concerned assumes that such-and-such a precondition holds
  • But that precondition is suspect (or false)
  • Therefore the concern can be dismissed.

Here’s a simple example – which used to be common, though it appears less often these days:

  • The argument for being concerned assumes that Moore’s Law will hold for the next three decades
  • But Moore’s Law is slowing down
  • Therefore the concern can be dismissed.

Another one:

  • The argument for being concerned assumes that deep learning systems understand what they’re talking about
  • But by such-and-such a definition of understanding, these systems lack understanding
  • (They’re “just stochastic parrots”)
  • Therefore the concern can be dismissed.

Or a favourite:

  • You call these systems AI, meaning they’re (supposedly) artificially intelligent
  • But by such-and-such a definition of intelligence, these systems lack intelligence
  • Therefore the concern can be dismissed.

Perhaps the silliest example:

  • Your example of doom involves a software system that is inordinately obsessed with paperclips
  • But any wise philosopher would design an AI that has no such paperclip obsession
  • Therefore the concern can be dismissed.

My conclusion: those of us who are seriously concerned about the prospects of a software-induced global catastrophe should clarify what are the minimum conditions that would give rise to such a catastrophe.

To be clear, these minimum conditions don’t include the inexorability of Moore’s Law. Nor the conformance of software systems to particular academic models of language understanding. Nor that a fast take-off occurs. Nor that the software system becomes sentient.

Here’s my suggestion of these minimum conditions:

  1. A software system that can influence, directly or indirectly (e.g. by psychological pressure) what happens in the real world
  2. That has access, directly or indirectly, to physical mechanisms that can seriously harm humans
  3. That operates in ways which we might fail to understand or anticipate
  4. That can anticipate actions humans might take, and can calculate and execute countermeasures
  5. That can take actions quickly enough (and/or stealthily enough) to avoid being switched off or reconfigured before catastrophic damage is done.

Even more briefly: the software system operates outside our understanding and outside our control, with potential devastating power.

I’ve chosen to use the term “software” rather than “AI” in order to counter a whole posse of dismissers right at the beginning of the discussion. Not even the smuggest of dismissers denies that software exists and can, indeed, cause harm when it contains bugs, is misconfigured, is hacked, or has gaps in its specification.

Critically, note that software systems often do have real-world impact. Consider the Stuxnet computer worm that caused centrifuges to speed up and destroy themselves inside Iran’s nuclear enrichment facilities. Consider the WannaCry malware that disabled critical hospital equipment around the world in 2017.

Present-day chatbots have already influenced millions of people around the world, via the ideas emerging in chat interactions. Just as people can make life-changing decisions after talking with human therapists or counsellors, people are increasingly taking life-changing decisions following their encounters with the likes of ChatGPT.

Software systems are already involved in the design and operation of military weapons. Presently, humans tend to remain “in the loop”, but military leaders are making the case for humans instead being just “on the loop”, in order for their defence systems to be able to move “at the speed of relevance”.

So the possibility of this kind of software shouldn’t be disputed.

It’s not just military weapons where the potential risk exists. Software systems can be involved with biological pathogens, or with the generation of hate-inducing fake news, or with geoengineering. Or with the manipulation of parts of our infrastructure that we currently only understand dimly, but which might turn out to be horribly fragile, when nudged in particular ways.

Someone wanting to dismiss the risk of software-induced global catastrophe therefore needs to make one or more of the following cases:

  1. All such software systems will be carefully constrained – perhaps by tamperproof failsafe mechanisms that are utterly reliable
  2. All such software systems will remain fully within human understanding, and therefore won’t take any actions that surprise us
  3. All such software systems will fail to develop an accurate “theory of mind” and therefore won’t be able to anticipate human countermeasures
  4. All such software systems will decide, by themselves, to avoid humans experiencing significant harm, regardless of which other goals are found to be attractive by the alien mental processes of that system.

If you still wish to dismiss the risk of software global catastrophe, which of these four cases do you wish to advance?

Or do you have something different in mind?

And can you also be sure that all such software systems will operate correctly, without bugs, configuration failures, gaps in their specification, or being hacked?

Case 2, by the way, includes the idea that “we humans will merge with software and will therefore remain in control of that software”. But in that case, how confident are you that:

  • Humans can speed up their understanding as quickly as the improvement rate of software systems that are free from the constraints of the human skull?
  • Any such “superintelligent” humans will take actions that avoid the same kinds of global catastrophe (after all, some of the world’s most dangerous people have intelligence well above the average)?

Case 4 includes the idea that at least some aspects of morality are absolute, and that a sufficiently intelligent piece of software will discover these principles. But in that case, how confident are you that:

  • The software will decide to respect these principles of morality, rather than (like many humans) disregarding them in order to pursue some other objectives?
  • That these fundamental principles of morality will include the preservation and flourishing of eight billion humans (rather than, say, just a small representative subset in a kind of future “zoo”)?

Postscript: My own recommendations for how to address these very serious risks are in The Singularity Principles. Spoiler alert: there are no magic bullets.

26 February 2023

Ostriches and AGI risks: four transformations needed

Filed under: AGI, risks, Singularity, Singularity Principles — Tags: , — David Wood @ 12:48 am

I confess to having been pretty despondent at various times over the last few days.

The context: increased discussions on social media triggered by recent claims about AGI risk – such as I covered in my previous blogpost.

The cause of my despondency: I’ve seen far too many examples of people with scant knowledge expressing themselves with unwarranted pride and self-certainty.

I call these people the AGI ostriches.

It’s impossible for AGI to exist, one of these ostriches squealed. The probability that AGI can exist is zero.

Anyone concerned about AGI risks, another opined, fails to understand anything about AI, and has just got their ideas from Hollywood or 1950s science fiction.

Yet another claimed: Anything that AGI does in the world will be the inscrutable cosmic will of the universe, so we humans shouldn’t try to change its direction.

Just keep your hand by the off switch, thundered another. Any misbehaving AGI can easily be shut down. Problem solved! You didn’t think of that, did you?

Don’t give the robots any legs, shrieked yet another. Problem solved! You didn’t think of that, did you? You fool!

It’s not the ignorance that depressed me. It was the lack of interest shown by the AGI ostriches regarding alternative possibilities.

I had tried to engage some of the ostriches in conversation. Try looking at things this way, I asked. Not interested, came the answer. Discussions on social media never change any minds, so I’m not going to reply to you.

Click on this link to read a helpful analysis, I suggested. No need, came the answer. Nothing you have written could possibly be relevant.

And the ostriches rejoiced in their wilful blinkeredness. There’s no need to look in that direction, they said. Keep wearing the blindfolds!

(The following image is by the Midjourney AI.)

But my purpose in writing this blogpost isn’t to complain about individual ostriches.

Nor is my purpose to lament the near-fatal flaws in human nature, including our many cognitive biases, our emotional self-sabotage, and our perverse ideological loyalties.

Instead, my remarks will proceed in a different direction. What most needs to change isn’t the ostriches.

It’s the community of people who want to raise awareness of the catastrophic risks of AGI.

That includes me.

On reflection, we’re doing four things wrong. Four transformations are needed, urgently.

Without these changes taking place, it won’t be surprising if the ostriches continue to behave so perversely.

(1) Stop tolerating the Singularity Shadow

When they briefly take off their blindfolds, and take a quick peak into the discussions about AGI, ostriches often notice claims that are, in fact, unwarranted.

These claims confuse matters. They are overconfident claims about what can be expected about the advent of AGI, also known as the Technological Singularity. These claims form part of what I call the Singularity Shadow.

There are seven components in the Singularity Shadow:

  • Singularity timescale determinism
  • Singularity outcome determinism
  • Singularity hyping
  • Singularity risk complacency
  • Singularity term overloading
  • Singularity anti-regulation fundamentalism
  • Singularity preoccupation

If you’ve not come across the concept before, here’s a video all about it:

Or you can read this chapter from The Singularity Principles on the concept: “The Singularity Shadow”.

People who (like me) point out the dangers of badly designed AGI often too easily make alliances with people in the Singularity Shadow. After all, both groups of people:

  • Believe that AGI is possible
  • Believe that AGI might happen soon
  • Believe that AGI is likely to be cause an unprecedented transformation in the human condition.

But the Singularity Shadow causes far too much trouble. It is time to stop being tolerant of its various confusions, wishful thinking, and distortions.

To be clear, I’m not criticising the concept of the Singularity. Far from it. Indeed, I consider myself a singularitarian, with the meaning I explain here. I look forward to more and more people similarly adopting this same stance.

It’s the distortions of that stance that now need to be countered. We must put our own house in order. Sharply.

Otherwise the ostriches will continue to be confused.

(2) Clarify the credible risk pathways

The AI paperclip maximiser has had its day. It needs to be retired.

Likewise the cancer-solving AI that solves cancer by, perversely, killing everyone on the planet.

Likewise the AI that “rescues” a woman from a burning building by hurling her out of the 20th floor window.

In the past, these thought experiments all helped the discussion about AGI risks, among people who were able to see the connections between these “abstract” examples and more complicated real-world scenarios.

But as more of the general public shows an interest in the possibilities of advanced AI, we urgently need a better set of examples. Explained, not by mathematics, nor by cartoonish simplifications, but in plain everyday language.

I’ve tried to offer some examples, for example in the section “Examples of dangers with uncontrollable AI” in the chapter “The AI Control Problem” of my book The Singularity Principles.

But it seems these scenarios still fail to convince. The ostriches find themselves bemused. Oh, that wouldn’t happen, they say.

So this needs more work. As soon as possible.

I anticipate starting from themes about which even the most empty-headed ostrich occasionally worries:

  1. The prospects of an arms race involving lethal autonomous weapons systems
  2. The risks from malware that runs beyond the control of the people who originally released it
  3. The dangers of geoengineering systems that seek to manipulate the global climate
  4. The “gain of function” research which can create ultra-dangerous pathogens
  5. The side-effects of massive corporations which give priority to incentives such as “increase click-through”
  6. The escalation in hatred stirred up by automated trolls with more ingenious “fake social media”

On top of these starting points, the scenarios I envision mix in AI systems with increasing power and increasing autonomy – AI systems which are, however, incompletely understood by the people who deploy them, and which might manifest terrible bugs in unexpected circumstances. (After all, AIs include software, and software generally contains bugs.)

If there’s not already a prize competition to encourage clearer communication of such risk scenarios, in ways that uphold credibility as well as comprehensibility, there should be!

(3) Clarify credible solution pathways

Even more important than clarifying the AGI risk scenarios is to clarify some credible pathways to managing these risks.

Without seeing such solutions, ostriches go into an internal negative feedback loop. They think to themselves as follows:

  • Any possible solution to AGI risks seems unlikely to be successful
  • Any possible solution to AGI risks seems likely to have bad consequences in its own right
  • These thoughts are too horrible to contemplate
  • Therefore we had better believe the AGI risks aren’t actually real
  • Therefore anyone who makes AGI risks seem real needs to be silenced, ridiculed, or mocked.

Just as we need better communication of AGI risk scenarios, we need better communication of positive examples that are relevant to potential solutions:

  • Examples of when society collaborated to overcome huge problems which initially seemed impossible
  • Successful actions against the tolerance of drunk drivers, against dangerous features in car design, against the industrial pollutants which caused acid rain, and against the chemicals which depleted the ozone layer
  • Successful actions by governments to limit the powers of corporate monopolies
  • The de-escalation by Ronald Reagan and Mikhail Gorbachev of the terrifying nuclear arms race between the USA and the USSR.

But we also need to make it clearer how AGI risks can be addressed in practice. This includes a better understanding of:

  • Options for AIs that are explainable and interpretable – with the aid of trusted tools built from narrow AI
  • How AI systems can be designed to be free from the unexpected “emergence” of new properties or subgoals
  • How trusted monitoring can be built into key parts of our infrastructure, to provide early warnings of potential AI-induced catastrophic failures
  • How powerful simulation environments can be created to explore potential catastrophic AI failure modes (and solutions to these issues) in the safety of a virtual model
  • How international agreements can be built up, initially from a “coalition of the willing”, to impose powerful penalties in cases when AI is developed or deployed in ways that violate agreed standards
  • How research into AGI safety can be managed much more effectively, worldwide, than is presently the case.

Again, as needed, significant prizes should be established to accelerate breakthroughs in all these areas.

(4) Divide and conquer

The final transformation needed is to divide up the overall huge problem of AGI safety into more manageable chunks.

What I’ve covered above already suggests a number of vitally important sub-projects.

Specifically, it is surely worth having separate teams tasked with investigating, with the utmost seriousness, a range of potential solutions for the complications that advanced AI brings to each of the following:

  1. The prospects of an arms race involving lethal autonomous weapons systems
  2. The risks from malware that runs beyond the control of the people who originally released it
  3. The dangers of geoengineering systems that seek to manipulate the global climate
  4. The “gain of function” research which can create ultra-dangerous pathogens
  5. The side-effects of massive corporations which give priority to incentives such as “increase click-through”
  6. The escalation in hatred stirred up by automated trolls with more ingenious “fake social media”

(Yes, these are the same six scenarios for catastrophic AI risk that I listed in section (2) earlier.)

Rather than trying to “boil the entire AGI ocean”, these projects each appear to require slightly less boiling.

Once candidate solutions have been developed for one or more of these risk scenarios, the outputs from the different teams can be compared with each other.

What else should be added to the lists above?

23 February 2023

Nuclear-level catastrophe: four responses

36% of respondents agree that it is plausible that AI could produce catastrophic outcomes in this century, on the level of all-out nuclear war.

That’s 36% of a rather special group of people. People who replied to this survey needed to meet the criterion of being a named author on at least two papers published in the last three years in accredited journals in the field of Computational Linguistics (CL) – the field sometimes also known as NLP (Natural Language Processing).

The survey took place in May and June 2022. 327 complete responses were received, by people matching the criteria.

A full report on this survey (31 pages) is available here (PDF).

Here’s a screenshot from page 10 of the report, illustrating the answers to questions about Artificial General Intelligence (AGI):

You can see the responses to question 3-4. 36% of the respondents either “agreed” or “weakly agreed” with the statement that

It is plausible that decisions made by AI or machine learning systems could cause a catastrophe this century that is at least as bad as an all-out nuclear war.

That statistic is a useful backdrop to discussions stirred up in the last few days by a video interview given by polymath autodidact and long-time AGI risk researcher Eliezer Yudkowsky:

The publishers of that video chose the eye-catching title “we’re all gonna die”.

If you don’t want to spend 90 minutes watching that video – or if you are personally alienated by Eliezer’s communication style – here’s a useful twitter thread summary by Liron Shapira:

In contrast to the question posed in the NLP survey I mentioned earlier, Eliezer isn’t thinking about “outcomes of AGI in this century“. His timescales are much shorter. His “ballpark estimate” for the time before AGI arrives is “3-15 years”.

How are people reacting to this sombre prediction?

More generally, what responses are there to the statistic that, as quoted above,

36% of respondents agree that it is plausible that AI could produce catastrophic outcomes in this century, on the level of all-out nuclear war.

I’ve seen a lot of different reactions. They break down into four groups: denial, sabotage, trust, and hustle.

1. Denial

One example of denial is this claim: We’re nowhere near an understanding the magic of human minds. Therefore there’s no chance that engineers are going to duplicate that magic in artificial systems.

I have two counters:

  1. The risks of AGI arise, not because the AI may somehow become sentient, and take on the unpleasant aspects of alpha male human nature. Rather, the risks arise from systems that operate beyond our understanding and outside our control, and which may end up pursuing objectives different from the ones we thought (or wished) we had programmed into them
  2. Many systems have been created over the decades without the underlying science being fully understood. Steam engines predated the laws of thermodynamics. More recently, LLMs (Large Language Model AIs) have demonstrated aspects of intelligence that the designers of these systems had not anticipated. In the same way, AIs with some extra features may unexpectedly tip over into greater general intelligence.

Another example of denial: Some very smart people say they don’t believe that AGI poses risks. Therefore we don’t need to pay any more attention to this stupid idea.

My counters:

  1. The mere fact that someone very smart asserts an idea – likely outside of their own field of special expertise – does not confirm the idea is correct
  2. None of these purported objections to the possibility of AGI risk holds water (for a longer discussion, see my book The Singularity Principles).

Digging further into various online discussion threads, I caught the impression that what was motivating some of the denial was often a terrible fear. The people loudly proclaiming their denial were trying to cope with depression. The thought of potential human extinction within just 3-15 years was simply too dreadful for them to contemplate.

It’s similar to how people sometimes cope with the death of someone dear to them. There’s a chance my dear friend has now been reunited in an afterlife with their beloved grandparents, they whisper to themselves. Or, It’s sweet and honourable to die for your country: this death was a glorious sacrifice. And then woe betide any uppity humanist who dares to suggests there is no afterlife, or that patriotism is the last refuge of a scoundrel!

Likewise, woe betide any uppity AI risk researcher who dares to suggest that AGI might not be so benign after all! Deny! Deny!! Deny!!!

(For more on this line of thinking, see my short chapter “The Denial of the Singularity” in The Singularity Principles.)

A different motivation for denial is the belief that any sufficient “cure” to the risk of AGI catastrophe would be worse than the risk it was trying to address. This line of thinking goes as follows:

  • A solution to AGI risk will involve pervasive monitoring and widespread restrictions
  • That monitoring and restrictions will only be possible if an autocratic world government is put in place
  • Any autocratic world government would be absolutely terrible
  • Therefore, the risk of AGI can’t be that bad after all.

I’ll come back later to the flaws in that particular argument. (In the meantime, see if you can spot what’s wrong.)

2. Sabotage

In the video interview, Eliezer made one suggestion for avoiding AGI catastrophe: Destroy all the GPU server farms.

These vast collections of GPUs (a special kind of computing chip) are what enables the training of many types of AI. If these chips were all put out of action, it would delay the arrival of AGI, giving humanity more time to work out a better solution to coexisting with AGI.

Another suggestion Eliezer makes is that the superbright people who are currently working flat out to increase the capabilities of their AI systems should be paid large amounts of money to do nothing. They could lounge about on a beach all day, and still earn more money than they are currently receiving from OpenAI, DeepMind, or whoever is employing them. Once again, that would slow down the emergence of AGI, and buy humanity more time.

I’ve seen other similar suggestions online, which I won’t repeat here, since they come close to acts of terrorism.

All these suggestions have in common: let’s find ways to stop the development of AI in its tracks, all across the world. Companies should be stopped in their tracks. Shadowy military research groups should be stopped in their tracks. Open source hackers should be stopped in their tracks. North Korean ransomware hackers must be stopped in their tracks.

This isn’t just a suggestion that specific AI developments should be halted, namely those with an explicit target of creating AGI. Instead, it recognises that the creation of AGI might occur via unexpected routes. Improving the performance of various narrow AI systems, including fact-checking, or emotion recognition, or online request interchange marketplaces – any of these might push the collection of AI modules over the critical threshold. Mixing metaphors, AI could go nuclear.

Shutting down all these research activities seems a very tall order. Especially since many of the people who are currently working flat out to increase AI capabilities are motivated, not by money, but by the vision that better AI could do a tremendous amount of good in the world: curing cancer, solving nuclear fusion, improving agriculture by leaps and bounds, and so on. They’re not going to be easy to persuade to change course. For them, there’s a lot more at stake than money.

I have more to say about the question “To AGI or not AGI” in this chapter. In short, I’m deeply sceptical.

In response, a would-be saboteur may admit that their chances of success are low. But what do you suggest instead, they will ask.

Read on.

3. Trust

Let’s start again from the statistic that 36% of the NLP survey respondents agreed, with varying degrees of confidence, that advanced AI could trigger a catastrophe as bad as an all-out nuclear war some time this century.

It’s a pity that the question wasn’t asked with shorter timescales. Comparing the chances of an AI-induced global catastrophe in the next 15 years with one in the next 85 years:

  • The longer timescale makes it more likely that AGI will be developed
  • The shorter timescale makes it more likely that AGI safety research will still be at a primitive (deeply ineffective) level.

Even since the date of the survey – May and June 2022 – many forecasters have shortened their estimates of the likely timeline to the arrival of AGI.

So, for the sake of the argument, let’s suppose that the risk of an AI-induced global catastrophe happening by 2038 (15 years from now) is 1/10.

There are two ways to react to this:

  • 1/10 is fine odds. I feel lucky. What’s more, there are plenty of reasons we ought to feel lucky about
  • 1/10 is terrible odds. That’s far too high a risk to accept. We need to hustle to find ways to change these odds in our favour.

I’ll come to the hustle response in a moment. But let’s first consider the trust response.

A good example is in this comment from SingularityNET founder and CEO Ben Goertzel:

Eliezer is a very serious thinker on these matters and was the core source of most of the ideas in Nick Bostrom’s influential book Superintelligence. But ever since I met him, and first debated these issues with him,  back in 2000 I have felt he had a somewhat narrow view of humanity and the universe in general.   

There are currents of love and wisdom in our world that he is not considering and seems to be mostly unaware of, and that we can tap into by creating self reflective compassionate AGIs and doing good loving works together with them.

In short, rather than fearing humanity, we should learn to trust humanity. Rather than fearing what AGI will do, we should trust that AGI can do wonderful things.

You can find a much longer version of Ben’s views in the review he wrote back in 2015 of Superintelligence. It’s well worth reading.

What are the grounds for hope? Humanity has come through major challenges in the past. Even though the scale of the challenge is more daunting on this occasion, there are also more people contributing ideas and inspiration than before. AI is more accessible than nuclear weapons, which increases the danger level, but AI could also be deployed as part of the solution, rather than just being a threat.

Another idea is that if an AI looks around for data teaching it which values to respect and uphold, it will find plenty of positive examples in great human literature. OK, that literature also includes lots of treachery, and different moral codes often conflict, but a wise AGI should be able to see through all these conclusions to discern the importance of defending human flourishing. OK, much of AI training at the moment focuses on deception, manipulation, enticement, and surveillance, but, again, we can hope that a wise AGI will set aside those nastier aspects of human behaviour. Rather than aping trolls or clickbait, we can hope that AGI will echo the better angels of human nature.

It’s also possible that, just as DeepMind’s AlphaGo Zero worked out by itself, without any human input, superior strategies at the board games Go and Chess, a future AI might work out, by itself, the principles of universal morality. (That’s assuming such principles exist.)

We would still have to hope, in such a case, that the AI that worked out the principles of universal morality would decide to follow these principles, rather than having some alternative (alien) ways of thinking.

But surely hope is better than despair?

To quote Ben Goertzel again:

Despondence is unwarranted and unproductive. We need to focus on optimistically maximizing odds of a wildly beneficial Singularity together.   

My view is the same as expressed by Berkeley professor of AI Stuart Russell, in part of a lengthy exchange with Steven Pinker on the subject of AGI risks:

The meta argument is that if we don’t talk about the failure modes, we won’t be able to address them…

Just like in nuclear safety, it’s not against the rules to raise possible failure modes like, what if this molten sodium that you’re proposing should flow around all these pipes? What if it ever came into contact with the water that’s on the turbine side of the system? Wouldn’t you have a massive explosion which could rip off the containment and so on? That’s not exactly what happened in Chernobyl, but not so dissimilar…

The idea that we could solve that problem without even mentioning it, without even talking about it and without even pointing out why it’s difficult and why it’s important, that’s not the culture of safety. That’s sort of more like the culture of the communist party committee in Chernobyl, that simply continued to assert that nothing bad was happening.

(By the way, my sympathies in that long discussion, when it comes to AGI risk, are approximately 100.0% with Russell and approximately 0.0% with Pinker.)

4. Hustle

The story so far:

  • The risks are real (though estimates of their probability vary)
  • Some possible “solutions” to the risks might produce results that are, by some calculations, worse than letting AGI take its own course
  • If we want to improve our odds of survival – and, indeed, for humanity to reach something like a sustainable superabundance with the assistance of advanced AIs – we need to be able to take a clear, candid view of the risks facing us
  • Being naĂŻve about the dangers we face is unlikely to be the best way forward
  • Since time may be short, the time to press for better answers is now
  • We shouldn’t despair. We should hustle.

Some ways in which research could generate useful new insight relatively quickly:

  • When the NLP survey respondents expressed their views, what reasons did they have for disagreeing with the statement? And what reasons did they have for agreeing with it? And how do these reasons stand up, in the cold light of a clear analysis? (In other words, rather than a one-time survey, an iterative Delphi survey should lead to deeper understanding.)
  • Why have the various AI safety initiatives formed in the wake of the Puerto Rico and Asilomar conferences of 2015 and 2017 fallen so far short of expectations?
  • Which descriptions of potential catastrophic AI failure modes are most likely to change the minds of those critics who currently like to shrug off failure scenarios as “unrealistic” or “Hollywood fantasy”?

Constructively, I invite conversation on the strengths and weaknesses of the 21 Singularity Principles that I have suggested as contributing to improving the chances of beneficial AGI outcomes.

For example:

  • Can we identify “middle ways” that include important elements of global monitoring and auditing of AI systems, without collapsing into autocratic global government?
  • Can we improve the interpretability and explainability of advanced AI systems (perhaps with the help of trusted narrow AI tools), to diminish the risks of these systems unexpectedly behaving in ways their designers failed to anticipate?
  • Can we deepen our understanding of the ways new capabilities “emerge” in advanced AI systems, with a particular focus on preventing the emergence of alternative goals?

I also believe we should explore more fully the possibility that an AGI will converge on a set of universal values, independent of whatever training we provide it – and, moreover, the possibility that these values will include upholding human flourishing.

And despite me saying just now that these values would be “independent of whatever training we provide”, is there, nevertheless, a way for us to tilt the landscape so that the AGI is more likely to reach and respect these conclusions?


To join me in “camp hustle”, visit Future Surge, which is the activist wing of London Futurists.

If you’re interested in the ideas of my book The Singularity Principles, here’s a podcast episode in which Calum Chace and I discuss some of these ideas more fully.

In a subsequent episode of our podcast, Calum and I took another look at the same topics, this time with Millennium Project Executive Director Jerome Glenn: “Governing the transition to AGI”.

19 December 2022


Filed under: AGI, politics, Singularity Principles — Tags: , , — David Wood @ 2:06 am

I’ve been rethinking some aspects of AI control and AI alignment.

In the six months since publishing my book The Singularity Principles: Anticipating and Managing Cataclysmically Disruptive Technologies, I’ve been involved in scores of conversations about the themes it raises. These conversations have often brought my attention to fresh ideas and different perspectives.

These six months have also seen the appearance of numerous new AI models with capabilities that often catch observers by surprise. The general public is showing a new willingness (at least some of the time) to consider the far-reaching implications of these AI models and their more powerful successors.

People from various parts of my past life have been contacting me. The kinds of things they used to hear me forecasting – the kinds of things they thought, at the time, were unlikely to ever happen – are becoming more credible, more exciting, and, yes, more frightening.

They ask me: What is to be done? And, pointedly, Why aren’t you doing more to stop the truly bad outcomes that now seem ominously likely?

The main answer I give is: read my book. Indeed, you can find all the content online, spread out over a family of webpages.

Indeed, my request is that people should read my book all the way through. That’s because later chapters of that book anticipate questions that tend to come to readers’ minds during earlier chapters, and try to provide answers.

Six months later, although I would give some different (newer) examples were I to rewrite that book today, I stand by the analysis I offered and the principles I championed.

However, I’m inclined to revise my thinking on a number of points. Please find these updates below.

An option to control superintelligent AI

I remain doubtful about the prospects for humans to retain control of any AGI (Artificial General Intelligence) that we create.

That is, the arguments I gave in my chapter “The AI Control Problem” still look strong to me.

But one line of thinking may have some extra mileage. That’s the idea of keeping AGI entirely as an advisor to humans, rather than giving it any autonomy to act directly in the world.

Such an AI would provide us with many recommendations, but it wouldn’t operate any sort of equipment.

More to the point: such an AI would have no desire to operate any sort of equipment. It would have no desires whatsoever, nor any motivations. It would simply be a tool. Or, to be more precise, it would simply be a remarkable tool.

In The Singularity Principles I gave a number of arguments why that idea is unsustainable:

  • Some decisions require faster responses than slow-brained humans can provide; that is, AIs with direct access to real-world levers and switches will be more effective than those that are merely advisory
  • Smart AIs will inevitably develop “subsidiary goals” (intermediate goals) such as having greater computational power, even when there is no explicit programming for such goals
  • As soon as a smart AI acquires any such subsidiary goal, it will find ways to escape any confinement imposed by human overseers.

But I now think this should be explored more carefully. Might a useful distinction be made between:

  1. AIs that do have direct access to real-world levers and switches – with the programming of such AIs being carefully restricted to narrow lines of thinking
  2. AIs with more powerful (general) capabilities, that operate purely in advisory capacities.

In that case, the damage that could be caused by failures of the first type of AI, whilst significant, would not involve threats to the entirety of human civilisation. And failures of the second type of AI would be restricted by the actions of humans as intermediaries.

This approach would require confidence that:

  1. The capabilities of AIs of the first type will remain narrow, despite competitive pressures to give these systems at least some extra rationality
  2. The design of AIs of the second type will prevent the emergence of any dangerous “subsidiary goals”.

As a special case of the second point, the design of these AIs will need to avoid any risk of the systems developing sentience or intrinsic motivation.

These are tough challenges – especially since we still have only a vague understanding of how desires and/or sentience can emerge as smaller systems combine and evolve into larger ones.

But since we are short of other options, it’s definitely something to be considered more fully.

An option for automatically aligned superintelligence

If controlling an AGI turns out to be impossible – as seems likely – what about the option that an AGI will have goals and principles that are fundamentally aligned with human wellbeing?

In such a case, it will not matter if an AGI is beyond human control. The actions it takes will ensure that humans have a very positive future.

The creation of such an AI – sometimes called a “friendly AI” – remains my best hope for humanity’s future.

However, there are severe difficulties in agreeing and encoding “goals and principles that are fundamentally aligned with human wellbeing”. I reviewed these difficulties in my chapter “The AI Alignment Problem”.

But what if such goals and principles are somehow part of an objective reality, awaiting discovery, rather than needing to be invented? What if something like the theory of “moral realism” is true?

In this idea, a principle like “treat humans well” would follow from some sort of a priori logical analysis, a bit like the laws of mathematics (such as the fact, discovered by one of the followers of Pythagoras, that the square root of two is an irrational number).

Accordingly, a sufficiently smart AGI would, all being well, reach its own conclusion that humans ought to be well treated.

Nevertheless, even in this case, significant risks would remain:

  • The principle might be true, but an AGI might not be motivated to discover it
  • The principle might be true, but an AGI, despite its brilliance, may fail to discover it
  • The principle might be true, and an AGI might recognise it, but it may take its own decision to ignore it – like the way that we humans often act in defiance of what we believe at the time to be overarching moral principles

The design criteria and initial conditions that we humans provide for an AGI may well influence the outcome of these risk factors.

I plan to return to these weighty matters in a future blog post!

Two different sorts of control

I’ve come to realise that there are not one but two questions of control of AI:

  1. Can we humans retain control of an AGI that we create?
  2. Can society as a whole control the actions of companies (or organisations) that may create an AGI?

Whilst both these control problems are profoundly hard, the second is less hard.

Moreover, it’s the second problem which is the truly urgent one.

This second control problem involves preventing teams inside corporations (and other organisations) from rushing ahead without due regard to questions of the potential outcomes of their work.

It’s the second control problem that the 21 principles which I highlight in my book are primarily intended to address.

When people say “it’s impossible to solve the AI control problem”, I think they may be correct regarding the first problem, but I passionately believe they’re wrong concerning the second problem.

The importance of psychology

When I review what people say about the progress and risks of AI, I am frequently struck by the fact that apparently intelligent people are strongly attached to views that are full of holes.

When I try to point out the flaws in their thinking, they hardly seem to pause in their stride. They portray a stubborn confidence that they are sure they are correct.

What’s at play here is more than logic. It’s surely a manifestation of humanity’s often defective psychology.

My book includes a short chapter “The denial of the Singularity” which touched on various matters of psychology. If I were to rewrite my book today, I believe that chapter would become larger, and that psychological themes would be spread more widely throughout the book.

Of course, noticing psychological defects is only the start of making progress. Circumventing or transcending these defects is an altogether harder question. But it’s one that needs a lot more attention.

The option of merging with AI

How can we have a better, more productive conversation about anticipating and managing AGI?

How can we avoid being derailed by ineffective arguments, hostile rhetoric, stubborn prejudices, hobby-horse obsessions, outdated ideologies, and (see the previous section) flawed psychology?

How might our not-much-better-than-monkey brains cope with the magnitude of these questions?

One possible answer is that technology can help us (so long as we use it wisely).

For example, the chapter “Uplifting politics”, from near the end of my book, listed ten ways for “technology improving politics”.

More broadly, we humans have the option to selectively deploy some aspects of technology to improve our capabilities in handling other aspects of technology.

We must recognise that technology is no panacea. But it can definitely make a big difference.

Especially if we restrict ourselves to putting heavy reliance only on those technologies – narrow technologies – whose mode of operation we fully understand, and where risks of malfunction can be limited.

This forms part of a general idea that “we humans don’t need to worry about being left behind by robots, or about being subjugated by robots, since we will be the robots”.

As I put it in the chapter “No easy solutions” in my book,

If humans merge with AI, humans could remain in control of AIs, even as these AIs rapidly become more powerful. With such a merger in place, human intelligence will automatically be magnified, as AI improves in capability. Therefore, we humans wouldn’t need to worry about being left behind.

Now I’ve often expressed strong criticisms of this notion of merger. I still believe these criticisms are sound.

But what these criticisms show is that any such merger cannot be the entirety of our response to the prospect of the emergence of AGI. They can only be part of the solution. That’s especially true because humans-augmented-by-technology are still very likely to lag behind pure technology systems, until such time as human minds might be removed from biological skulls and placed into new silicon hosts. That’s something that I’m not expecting to happen before the arrival of AGI, so it will be too late to solve (by itself) the problems of AI alignment and control.

(And since you ask, I probably won’t be in any hurry, even after the arrival of AGI, for my mind to be removed from my biological skull. I guess I might rethink that reticence in due course. But that’s rethinking for another day.)

The importance of politics

Any serious discussion about managing cataclysmically disruptive technologies (such as advanced AIs) pretty soon rubs up against the questions of politics.

That’s not just small-p “politics” – questions of how to collaborate with potential partners where there are many points of disagreement and even dislike.

It’s large-P “Politics” – interacting with presidents, prime ministers, cabinets, parliaments, and so on.

Questions of large-P politics occur throughout The Singularity Principles. My thoughts now, six months afterwards, is that even more focus should be placed on the subject of improving politics:

  • Helping politics to escape the clutches of demagogues and autocrats
  • Helping politics to avoid stultifying embraces between politicians and their “cronies” in established industries
  • Ensuring that the best insights and ideas of the whole electorate can rise to wide attention, without being quashed or distorted by powerful incumbents
  • Bringing everyone involved in politics rapidly up-to-date with the real issues regarding cataclysmically disruptive technologies
  • Distinguishing effective regulations and incentives from those that are counter-productive.

As 2022 has progressed, I’ve seen plenty new evidence of deep problems within political systems around the world. These problems were analysed with sharp insight in the book The Revenge of Power by MoisĂ©s NaĂ­m that I recently identified as “the best book that I read in 2022”.

Happily, as well as evidence of deep problems in our politics worldwide, there are also encouraging signs, as well as sensible plans for improvement. You can find some of these plans inside the book by NaĂ­m, and, yes, I offer suggestions in my own book too.

To accelerate improvements in politics was one of the reasons I created Future Surge a few months back. That’s an initiative on which I expect to spend a lot more of my time in 2023.

Note: the image underlying the picture at the top of this article was created by DALL.E 2 from the prompt “A brain with a human face on it rethinks, vivid stormy sky overhead, photorealistic style”.

15 May 2022

A year-by-year timeline to 2045

The ground rules for the worldbuilding competition were attractive:

  • The year is 2045.
  • AGI has existed for at least 5 years.
  • Technology is advancing rapidly and AI is transforming the world sector by sector.
  • The US, EU and China have managed a steady, if uneasy, power equilibrium.
  • India, Africa and South America are quickly on the ride as major players.
  • Despite ongoing challenges, there have been no major wars or other global catastrophes.
  • The world is not dystopian and the future is looking bright.

Entrants were asked to submit four pieces of work. One was a new media piece. I submitted this video:

Another required piece was:

timeline with entries for each year between 2022 and 2045 giving at least two events (e.g. “X invented”) and one data point (e.g. “GDP rises by 25%”) for each year.

The timeline I created dovetailed with the framework from the above video. Since I enjoyed creating it, I’m sharing my submission here, in the hope that it may inspire readers.

(Note: the content was submitted on 11th April 2022.)


US mid-term elections result in log-jammed US governance, widespread frustration, and a groundswell desire for more constructive approaches to politics.

The collapse of a major crypto “stablecoin” results in much wider adverse repercussions than was generally expected, and a new social appreciation of the dangers of flawed financial systems.

Data point: Number of people killed in violent incidents (including homicides and armed conflicts) around the world: 590,000


Fake news that is spread by social media driven by a new variant of AI provokes riots in which more than 10,000 people die, leading to much greater interest a set of “Singularity Principles” that had previously been proposed to steer the development of potentially world-transforming technologies.

G7 transforms into the D16, consisting of the world’s 16 leading democracies, proclaiming a profound shared commitment to champion norms of: openness; free and fair elections; the rule of law; independent media, judiciary, and academia; power being distributed rather than concentrated; and respect for autonomous decisions of groups of people.

Data point: Proportion of world population living in countries that are “full democracies” as assessed by the Economist: 6.4%


South Korea starts a trial of a nationwide UBI scheme, in the first of what will become in later years a long line of increasingly robust “universal citizens’ dividends” schemes around the world.

A previously unknown offshoot of ISIS releases a bioengineered virus. Fortunately, vaccines are quickly developed and deployed against it. In parallel, a bitter cyber war takes place between Iran and Israel. These incidents lead to international commitments to prevent future recurrences.

Data point: Proportion of people of working age in US who are not working and who are not looking for a job: 38%


Extreme weather – floods and storms – kills 10s of 1000s in both North America and Europe. A major trial of geo-engineering is rushed through, with reflection of solar radiation in the stratosphere – causing global political disagreement and then a renewed determination for tangible shared action on climate change.

The US President appoints a Secretary for the Future as a top-level cabinet position. More US states adopt rank choice voting, allowing third parties to grow in prominence.

Data point: Proportion of earth’s habitable land used to rear animals for human food: 38%


A song created entirely by an AI tops the hit parade, and initiates a radical new musical genre.

Groundswell opposition to autocratic rule in Russia leads to the fall from power of the president and a new dedication to democracy throughout countries formerly perceived as being within Russia’s sphere of direct influence.

Data point: Net greenhouse gas emissions (including those from land-use changes): 59 billion tons of CO2 equivalent – an unwelcome record.


Metformin approved for use as an anti-aging medicine in a D16 country. Another D16 country recommends nationwide regular usage of a new nootropic drug.

Exchanges of small numbers of missiles between North and South Korea leads to regime change inside North Korea and a rapprochement between the long-bitter enemies.

Data point: Proportion of world population living in countries that are “full democracies” as assessed by the Economist: 9.2%


An innovative nuclear fusion system, with its design assisted by AI, runs for more than one hour and generates significantly more energy out than what had been put in.

As a result of disagreements about the future of an independent Taiwan, an intense destructive cyber battle takes place. At the end, the nations of the world commit more seriously than before to avoiding any future cyber battles.

Data point: Proportion of world population experiencing mental illness or dissatisfied with the quality of their mental health: 41%


A trial of an anti-aging intervention in middle-aged dogs is confirmed to have increased remaining life expectancy by 25% without causing any adverse side effects. Public interest in similar interventions in humans skyrockets.

The UK rejoins a reconfigured EU, as an indication of support for sovereignty that is pooled rather than narrow.

Data point: Proportion of world population with formal cryonics arrangements: 1 in 100,000


Russia is admitted into the D40 – a newly expanded version of the D16. The D40 officially adopts “Index of Human Flourishing” as more important metric than GDP, and agrees a revised version of the Universal Declaration of Human Rights, brought up to date with transhuman issues.

First permanent implant in a human of an artificial heart with a new design that draws all required power from the biology of the body rather than any attached battery, and whose pace of operation is under the control of the brain.

Data point: Net greenhouse gas emissions (including those from land-use changes): 47 billion tons of CO2 equivalent – a significant improvement


An AI discovers and explains a profound new way of looking at mathematics, DeepMath, leading in turn to dramatically successful new theories of fundamental physics.

Widespread use of dynamically re-programmed nanobots to treat medical conditions that would previously have been fatal.

Data point: Proportion of world population regularly taking powerful anti-aging medications: 23%


First person reaches the age of 125. Her birthday celebrations are briefly disrupted by a small group of self-described “naturality advocates” who chant “120 is enough for anyone”, but that group has little public support.

D40 countries put in place a widespread “trustable monitoring system” to cut down on existential risks (such as spread of WMDs) whilst maintaining citizens’ trust.

Data point: Proportion of world population living in countries that are “full democracies” as assessed by the Economist: 35.7% 


For the first time since the 1850s, the US President comes from a party other than Republican and Democratic.

An AI system is able to convincingly pass the Turing test, impressing even the previous staunchest critics with its apparent grasp of general knowledge and common sense. The answers it gives to questions of moral dilemmas also impress previous sceptics.

Data point: Proportion of people of working age in US who are not working and who are not looking for a job: 58%


The D90 (expanded from the D40) agrees to vigorously impose Singularity Principles rules to avoid inadvertent creation of dangerous AGI.

Atomically precise synthetic nanoscale assembly factories have come of age, in line with the decades-old vision of nanotechnology visionary Eric Drexler, and are proving to have just as consequential an impact on human society as AI.

Data point: Net greenhouse gas *removals*: 10 billion tons of CO2 equivalent – a dramatic improvement


A novel written entirely by an AI reaches the top of the New York Times bestseller list, and is widely celebrated as being the finest piece of literature ever produced.

Successful measures to remove greenhouse gases from the atmosphere, coupled with wide deployment of clean energy sources, lead to a declaration of “victory over runaway climate change”.

Data point: Proportion of earth’s habitable land used to rear animals for human food: 4%


A film created entirely by an AI, without any real human actors, wins Oscar awards.

The last major sceptical holdout, a philosophy professor from an Ivy League university, accepts that AGI now exists. The pope gives his blessing too.

Data point: Proportion of world population with cryonics arrangements: 24%


The last instances of the industrial scale slaughter of animals for human consumption, on account of the worldwide adoption of cultivated (lab-grown) meat.

AGI convincingly explains that it is not sentient, and that it has a very different fundamental structure from that of biological consciousness.

Data point: Proportion of world population who are literate: 99.3%


Rejuvenation therapies are in wide use around the world. “Eighty is the new fifty”. First person reaches the age of 130.

Improvements made by AGI upon itself effectively raise its IQ one hundred fold, taking it far beyond the comprehension of human observers. However, the AGI provides explanatory educational material that allows people to understand vast new sets of ideas.

Data point: Proportion of world population who consider themselves opposed to AGI: 0.1%


An extensive set of “vital training” sessions has been established by the AGI, with all citizens over the age of ten participating for a minimum of seven hours per day on 72 days each year, to ensure that humans develop and maintain key survival skills.

Menopause reversal is common place. Women who had long ago given up any ideas of bearing another child happily embrace motherhood again.

Data point: Proportion of world population regularly taking powerful anti-aging medications: 99.2%


The use of “mind phones” is widespread: new brain-computer interfaces that allow communication between people by mental thought alone.

People regularly opt to have several of their original biological organs replaced by synthetic alternatives that are more efficient, more durable, and more reliable.

Data point: Proportion of people of working age in US who are not working and who are not looking for a job: 96%


Shared immersive virtual reality experiences include hyper-realistic simulations of long-dead individuals – including musicians, politicians, royalty, saints, and founders of religions.

The number of miles of journey undertaken by small “flying cars” exceeds that of ground-based powered transport.

Data point: Proportion of world population living in countries that are “full democracies” as assessed by the Economist: 100.0%


First successful revival of mammal from cryopreservation.

AGI presents a proof of the possibility of time travel, but the resources required for safe transit of humans through time would require the equivalent of building a Dyson sphere around the sun.

Data point: Proportion of world population experiencing mental illness or dissatisfied with the quality of their mental health: 0.4%


First person reaches the age of 135, and declares herself to be healthier than at any time in the preceding four decades.

As a result of virtual reality encounters of avatars of founders of religion, a number of new systems of philosophical and mystical thinking grow in popularity.

Data point: Proportion of world’s energy provided by earth-based nuclear fusion: 75%


First human baby born from an ectogenetic pregnancy.

Family holidays on the Moon are an increasingly common occurrence.

Data point: Average amount of their waking time that people spend in a metaverse: 38%


First revival of human from cryopreservation – someone who had been cryopreserved ten years previously.

Subtle messages decoded by AGI from far distant stars in the galaxy confirm that other intelligent civilisations exist, and are on their way to reveal themselves to humanity.

Data point: Number of people killed in violent incidents around the world: 59


My thanks go to the competition organisers, the Future of Life Institute, for providing the inspiration for the creation of the above timeline.

Readers are likely to have questions in their minds as they browse the timeline above. More details of the reasoning behind the scenarios involved are contained in three follow-up posts:

31 July 2020

The future of AI: 12 possible breakthroughs, and beyond

Filed under: AGI, books, disruption — Tags: , , , , — David Wood @ 1:30 pm

The AI of 5-10 years time could be very different from today’s AI. The most successful AI systems of that time will not simply be extensions of today’s deep neural networks. Instead, they are likely to include significant conceptual breakthroughs or other game-changing innovations.

That was the argument I made in a presentation on Thursday to the Global Data Sciences and Artificial Intelligence meetup. The chair of that meetup, Pramod Kunji, kindly recorded the presentation.

You can see my opening remarks in this video:

A copy of my slides can be accessed on Slideshare.

The ideas in this presentation raise many important questions, for which there are, as yet, only incomplete answers.

Indeed, the future of AI is a massive topic, touching nearly every area of human life. The greater the possibility that AI will experience cascading improvements in capability, the greater the urgency of exploring these scenarios in advance. In other words, the greater the need to set aside hype and predetermined ideas, in order to assess matters objectively and with an independent mind.

For that reason, I’ve joined with Rohit Talwar of Fast Future and Ben Goertzel of SingularityNET in a project to commission and edit chapters in a forthcoming book, “The Future of AI: Pathways to Artificial General Intelligence”.


We’re asking AI researchers, practitioners, analysts, commentators, policy makers, investors, futurists, economists, and writers from around the world, to submit chapters of up to 1,000 words, by the deadline of 15th September, that address one or more of the following themes:

  • Capability, Applications, and Impacts
    • How might the capabilities of AI systems evolve in the years ahead?
    • What can we anticipate about the potential evolution from today’s AI to AGI and beyond, in which software systems will match or exceed human cognitive abilities in every domain of thought?
    • What possible scenarios for the emergence of significantly more powerful AI deserve the most attention?
    • What new economic concepts, business models, and intellectual property ownership frameworks might be enabled and required as a result of advances that help us transition from today’s AI to AGI?
  • Pathways to AGI
    • What incremental steps might help drive practical commercial and humanitarian AI applications in the direction of AGI?
    • What practical ideas and experiences can be derived from real-world applications of technologies like transfer learning, unsupervised and reinforcement learning, and lifelong learning?
    • What are the opportunities and potential for “narrow AGI” applications that bring increasing levels of AGI to bear within specific vertical markets and application areas?
  • Societal Readiness
    • How can we raise society-wide awareness and understanding of the underlying technologies and their capabilities?
    • How can governments, businesses, educators, civil society organizations, and individuals prepare for the range of possible impacts and implications?
    • What other actions might be taken by individuals, by local groups, by individual countries, by non-governmental organizations (NGOs), by businesses, and by international institutions, to help ensure positive outcomes with advanced AI? How might we reach agreement on what constitutes a positive societal outcome in the context of AI and AGI?
  • Governance
    • How might societal ethical frameworks need to evolve to cope with the new challenges and opportunities that AGI is likely to bring?
    • What preparations can be made, at the present time, for the introduction and updating of legal and political systems to govern the development and deployment of AGI?

For more details of this new book, the process by which chapters will be selected, and processing fees that may apply, click here.

I’m very much looking forward to the insights that will arise – and to the critical new questions that will no doubt arise along the way.


29 September 2018

Preview: Assessing the risks from super intelligent AI

Filed under: AGI, presentation — Tags: , , , , , — David Wood @ 1:14 am

The following video gives a short preview of the Funzing talk on “Assessing the risks from super-intelligent AI” that I’ll be giving shortly:

Note: the music in this video is “Berlin Approval” from Jukedeck, a company that is “building tools that use cutting-edge musical artificial intelligence to assist creativity”. Create your own at http://jukedeck.com.

Transcript of the video:

Welcome. My name is David Wood, and I’d like to tell you about a talk I give for Funzing.

This talk looks at the potential rapid increase in the ability of Artificial Intelligence, also known as AI.

AI is everywhere nowadays, and it is, rightly, getting a lot of attention. But the AI of a few short years in the future could be MUCH more powerful than today’s AI. Is that going to be a good thing, or a bad thing?

Some people, like the entrepreneur Elon Musk, or the physicist Stephen Hawking, say we should be very worried about the growth of super artificial intelligence. It could be the worst thing that ever happened to humanity, they say. Without anyone intending it, we could all become the victims of some horrible bugs or design flaws in super artificial intelligence. You may have heard of the “blue screen of death”, when Windows crashes. Well, we could all be headed to some kind of “blue screen of megadeath”.

Other people, like the Facebook founder Mark Zuckerberg, say that it’s “irresponsible” to worry about the growth of super AI. Let’s hurry up and build better AI, they say, so we can use that super AI to solve major outstanding human problems like cancer, climate change, and economic inequality.

A third group of people say that discussing the rise of super AI is a distraction and it’s premature to do so now. It’s nothing we need to think about any time soon, they say. Instead, there are more pressing short-term issues that deserve our attention, like hidden biases in today’s AI algorithms, or the need to retrain people to change their jobs more quickly in the wake of the rise of automation.

In my talk, I’ll be helping you to understand the strengths and weaknesses of all three of these points of view. I’ll give reasons why, in as little as ten years, we could, perhaps, reach a super AI that goes way beyond human capability in every aspect. I’ll describe five ways in which that super AI could go disastrously wrong, due to lack of sufficient forethought and coordination about safety. And I’ll be reviewing some practical initiatives for how we can increase the chance of the growth of super AI being a very positive development for humanity, rather than a very negative one.

People who have seen my talk before have said that it’s easy to understand, it’s engaging, it’s fascinating, and it provides “much to think about”.

What makes my approach different to others who speak on this subject is the wide perspective I can apply. This comes from the twenty five years in which I was at the heart of the mobile computing and smartphone industries, during which time I saw at close hand the issues with developing and controlling very complicated system software. I also bring ten years of experience more recently, as chair of London Futurists, in running meetings at which the growth of AI has often been discussed by world-leading thinkers.

I consider myself a real-world futurist: I take the human and political dimensions of technology very seriously. I also consider myself to be a radical futurist, since I believe that the not-so-distant future could be very different from the present. And we need to think hard about it beforehand, to decide if we like that outcome or not.

The topic of super AI is too big and important to leave to technologists, or to business people. There are a lot of misunderstandings around, and my talk will help you see the key issues and opportunities more clearly than before. I look forward to seeing you there! Thanks for listening.

20 July 2018

Christopher Columbus and the surprising future of AI

Filed under: AGI, predictability, Singularity — Tags: , , , , — David Wood @ 5:49 pm

There are plenty of critics who are sceptical about the future of AI. The topic has been over-hyped, say these critics. According to these critics, we don’t need to be worried about the longer-term repercussions of AI with superhuman capabilities. We’re many decades – perhaps centuries – from anything approaching AGI (artificial general intelligence) with skills in common sense reasoning matching (or surpassing) that of humans. As for AI destroying jobs, that, too, is a false alarm – or so the critics insist. AI will create at least as many jobs as it destroys.

In my previous blog post, Serious question over PwC’s report on the impact of AI on jobs, I offered some counters to these critics. To my mind, this is no time for complacency: AI could accelerate in its capabilities, and take us by surprise. The kinds of breakthroughs that, in a previous era, might have been expected to take many decades, could actually take place in just a few short years. Rather than burying our head in the sands, denying the possibility of any such acceleration, we need to pay more attention to the trends of technological change and the potential for disruptive new innovations.

The Christopher Columbus angle

Overnight, I’ve been reminded of an argument that I’ve used previously – towards the end of a rather long blogpost. It’s the argument that critics of the future of AI are similar to the critics of Christopher Columbus – the people who said, before his 1492 voyage across the Atlantic in search of a westerly route to Asia, that the effort was bound to be a bad investment.

Bear with me while I retell this analogy.

For years, Columbus tried to drum up support for what most people considered to be a hare-brained scheme. Most observers concluded that Columbus had fallen victim to a significant mistake – he estimated that the distance from the Canary Islands (off the coast of Morocco) to Japan was around 3,700 km, whereas the generally accepted figure was closer to 20,000 km. Indeed, the true size of the sphere of the Earth had been known since the 3rd century BC, due to a calculation by Eratosthenes, based on observations of shadows at different locations.

Accordingly, when Columbus presented his bold proposal to courts around Europe, the learned members of the courts time and again rejected the idea. The effort would be hugely larger than Columbus supposed, they said. It would be a fruitless endeavour.

Columbus, an autodidact, wasn’t completely crazy. He had done a lot of his own research. However, he was misled by a number of factors:

  • Confusion between various ancient units of distance (the “Arabic mile” and the “Roman mile”)
  • How many degrees of latitude the Eurasian landmass occupied (225 degrees versus 150 degrees)
  • A speculative 1474 map, by the Florentine astronomer Toscanelli, which showed a mythical island “Antilla” located to the east of Japan (named as “Cippangu” in the map).

You can read the details in the Wikipedia article on Columbus, which provides numerous additional reference points. The article also contains a copy of Toscanelli’s map, with the true location of the continents of North and South America superimposed for reference.

No wonder Columbus thought his plan might work after all. Nevertheless, the 1490s equivalents of today’s VCs kept saying “No” to his pitches. Finally, spurred on by competition with the neighbouring Portuguese (who had, just a few years previously, successfully navigated to the Indian ocean around the tip of Africa), the Spanish king and queen agreed to take the risk of supporting his adventure. After stopping in the Canaries to restock, the Nina, the Pinta, and the Santa Maria set off westward. Five weeks later, the crew spotted land, in what we now call the Bahamas. And the rest is history.

But it wasn’t the history expected by Columbus, or by his backers, or by his critics. No-one had foreseen that a huge continent existed in the oceans in between Europe and Japan. None of the ancient writers – either secular or religious – had spoken of such a continent. Nevertheless, once Columbus had found it, the history of the world proceeded in a very different direction – including mass deaths from infectious diseases transmitted from the European sailors, genocide and cultural apocalypse, and enormous trade in both goods and slaves. In due course, it would the the ingenuity and initiatives of people subsequently resident in the Americas that propelled humans beyond the Earth’s atmosphere all the way to the moon.

What does this have to do with the future of AI?

Rational critics may have ample justification in thinking that true AGI is located many decades in the future. But this fact does not deter a multitude of modern-day AGI explorers from setting out, Columbus-like, in search of some dramatic breakthroughs. And who knows what intermediate forms of AI might be discovered, unexpectedly?

Just as the contemporaries of Columbus erred in presuming they already knew all the large features of the earth’s continents (after all: if America really existed, surely God would have written about it in the Bible…), modern-day critics of AI can err in presuming they already know all the large features of the landscape of possible artificial minds.

When contemplating the space of all possible minds, some humility is in order. We cannot foretell in advance what configurations of intelligence are possible. We don’t know what may happen, if separate modules of reasoning are combined in innovative ways. After all, there are many aspects of the human mind which are still in doubt.

When critics say that it is unlikely that present-day AI mechanisms will take us all the way to AGI, they are very likely correct. But it would be a horrendous error to draw the conclusion that meaningful new continents of AI capability are inevitably still the equivalent of 20,000 km into the distance. The fact is, we simply don’t know. And for that reason, we should keep an open mind.

One day soon, indeed, we might read news of some new “AUI” having been discovered – some Artificial Unexpected Intelligence, which changes history. It won’t be AGI, but it could have all kinds of unexpected consequences.

Beyond the Columbus analogy

Every analogy has its drawbacks. Here are three ways in which the discovery of an AUI could be different from the discovery by Columbus of America:

  1. In the 1490s, there was only one Christopher Columbus. Nowadays, there are scores (perhaps hundreds) of schemes underway to try to devise new models of AI. Many of these are proceeding with significant financial backing.
  2. Whereas the journey across the Atlantic (and, eventually, the Pacific) could be measured by a single variable (latitude), the journey across the vast multidimensional landscape of artificial minds is much less predictable. That’s another reason to keep an open mind.
  3. Discovering an AUI could drastically transform the future of exploration in the landscape of artificial minds. Assisted by AUI, we might get to AGI much quicker than without it. Indeed, in some scenarios, it might take only a few months after we reach AUI for us (now going much faster than before) to reach AGI. Or days. Or hours.


If you’re in or near Birmingham on 11th September, I’ll be giving a Funzing talk on how to assess the nature of the risks and opportunities from superhuman AI. For more details, see here.


7 December 2017

The super-opportunities and super-risks of super-AI

Filed under: AGI, Events, risks, Uncategorized — Tags: , , — David Wood @ 7:29 pm

2017 has seen more discussion of AI than any preceding year.

There has even been a number of meetings – 15, to be precise – in the UK Houses of Parliament, of the APPG AI – an “All-Party Parliamentary Group on Artificial Intelligence”.

According to its website, the APPG AI “was set up in January 2017 with the aim to explore the impact and implications of Artificial Intelligence”.

In the intervening 11 months, the group has held 7 evidence meetings, 4 advisory group meetings, 2 dinners, and 2 receptions. 45 different MPs, along with 7 members of the House of Lords and 5 parliamentary researchers, have been engaged in APPG AI discussions at various times.


Yesterday evening, at a reception in Parliament’s Cholmondeley Room & Terrace, the APPG AI issued a 12 page report with recommendations in six different policy areas:

  1. Data
  2. Infrastructure
  3. Skills
  4. Innovation & entrepreneurship
  5. Trade
  6. Accountability

The headline “key recommendation” is as follows:

The APPG AI recommends the appointment of a Minister for AI in the Cabinet Office

The Minister would have a number of different responsibilities:

  1. To bring forward the roadmap which will turn AI from a Grand Challenge to a tool for untapping UK’s economic and social potential across the country.
  2. To lead the steering and coordination of: a new Government Office for AI, a new industry-led AI Council, a new Centre for Data Ethics and Innovation, a new GovTech Catalyst, a new Future Sectors Team, and a new Tech Nation (an expansion of Tech City UK).
  3. To oversee and champion the implementation and deployment of AI across government and the UK.
  4. To keep public faith high in these emerging technologies.
  5. To ensure UK’s global competitiveness as a leader in developing AI technologies and capitalising on their benefits.

Overall I welcome this report. It’s a definite step in the right direction. Via a programme of further evidence meetings and workshops planned throughout 2018, I expect real progress can be made.

Nevertheless, it’s my strong belief that most of the public discussion on AI – including the discussions at the APPG AI – fail to appreciate the magnitude of the potential changes that lie ahead. There’s insufficient awareness of:

  • The scale of the opportunities that AI is likely to bring – opportunities that might better be called “super-opportunities”
  • The scale of the risks that AI is likely to bring – “super-risks”
  • The speed at which it is possible (though by no means guaranteed) that AI could transform itself via AGI (Artificial General Intelligence) to ASI (Artificial Super Intelligence).

These are topics that I cover in some of my own presentations and workshops. The events organisation Funzing have asked me to run a number of seminars with the title “Assessing the risks from superintelligent AI: Elon Musk vs. Mark Zuckerberg

DW Dec Funzing Singularity v2

The reference to Elon Musk and Mark Zuckerberg reflects the fact that these two titans of the IT industry have spoken publicly about the advent of superintelligence, taking opposing views on the balance of opportunity vs. risk.

In my seminar, I take the time to explain their differing points of view. Other thinkers on the subject of AI that I cover include Alan Turing, IJ Good, Ray Kurzweil, Andrew Ng, Eliezer Yudkowsky, Stuart Russell, Nick Bostrom, Isaac Asimov, and Jaan Tallinn. The talk is structured into six sections:

  1. Introducing the contrasting ideas of Elon Musk and Mark Zuckerberg
  2. A deeper dive into the concepts of “superintelligence” and “singularity”
  3. From today’s AI to superintelligence
  4. Five ways that powerful AI could go wrong
  5. Another look at accelerating timescales
  6. Possible responses and next steps

At the time of writing, I’ve delivered this Funzing seminar twice. Here’s a sampling of the online reviews:

Really enjoyed the talk, David is a good presenter and the presentation was very well documented and entertaining.

Brilliant eye opening talk which I feel very effectively conveyed the gravity of these important issues. Felt completely engaged throughout and would highly recommend. David was an excellent speaker.

Very informative and versatile content. Also easy to follow if you didn’t know much about AI yet, and still very insightful. Excellent Q&A. And the PowerPoint presentation was of great quality and attention was spent on detail putting together visuals and explanations. I’d be interested in seeing this speaker do more of these and have the opportunity to go even more in depth on specific aspects of AI (e.g., specific impact on economy, health care, wellbeing, job market etc). 5 stars 🙂

Best Funzing talk I have been to so far. The lecture was very insightful. I was constantly tuned in.

Brilliant weighing up of the dangers and opportunities of AI – I’m buzzing.

If you’d like to attend one of these seminars, three more dates are in my Funzing diary:

Click on the links for more details, and to book a ticket while they are still available 🙂

11 April 2015

Opening Pandora’s box

Should some conversations be suppressed?

Are there ideas which could prove so incendiary, and so provocative, that it would be better to shut them down?

Should some concepts be permanently locked into a Pandora’s box, lest they fly off and cause too much chaos in the world?

As an example, consider this oft-told story from the 1850s, about the dangers of spreading the idea of that humans had evolved from apes:

It is said that when the theory of evolution was first announced it was received by the wife of the Canon of Worcester Cathedral with the remark, “Descended from the apes! My dear, we will hope it is not true. But if it is, let us pray that it may not become generally known.”

More recently, there’s been a growing worry about spreading the idea that AGI (Artificial General Intelligence) could become an apocalyptic menace. The worry is that any discussion of that idea could lead to public hostility against the whole field of AGI. Governments might be panicked into shutting down these lines of research. And self-appointed militant defenders of the status quo might take up arms against AGI researchers. Perhaps, therefore, we should avoid any public mention of potential downsides of AGI. Perhaps we should pray that these downsides don’t become generally known.

tumblr_static_transcendence_rift_logoThe theme of armed resistance against AGI researchers features in several Hollywood blockbusters. In Transcendence, a radical anti-tech group named “RIFT” track down and shoot the AGI researcher played by actor Johnny Depp. RIFT proclaims “revolutionary independence from technology”.

As blogger Calum Chace has noted, just because something happens in a Hollywood movie, it doesn’t mean it can’t happen in real life too.

In real life, “Unabomber” Ted Kaczinski was so fearful about the future destructive potential of technology that he sent 16 bombs to targets such as universities and airlines over the period 1978 to 1995, killing three people and injuring 23. Kaczinski spelt out his views in a 35,000 word essay Industrial Society and Its Future.

Kaczinki’s essay stated that “the Industrial Revolution and its consequences have been a disaster for the human race”, defended his series of bombings as an extreme but necessary step to attract attention to how modern technology was eroding human freedom, and called for a “revolution against technology”.

Anticipating the next Unabombers

unabomber_ely_coverThe Unabomber may have been an extreme case, but he’s by no means alone. Journalist Jamie Bartlett takes up the story in a chilling Daily Telegraph article “As technology swamps our lives, the next Unabombers are waiting for their moment”,

In 2011 a new Mexican group called the Individualists Tending toward the Wild were founded with the objective “to injure or kill scientists and researchers (by the means of whatever violent act) who ensure the Technoindustrial System continues its course”. In 2011, they detonated a bomb at a prominent nano-technology research centre in Monterrey.

Individualists Tending toward the Wild have published their own manifesto, which includes the following warning:

We employ direct attacks to damage both physically and psychologically, NOT ONLY experts in nanotechnology, but also scholars in biotechnology, physics, neuroscience, genetic engineering, communication science, computing, robotics, etc. because we reject technology and civilisation, we reject the reality that they are imposing with ALL their advanced science.

Before going any further, let’s agree that we don’t want to inflame the passions of would-be Unabombers, RIFTs, or ITWs. But that shouldn’t lead to whole conversations being shut down. It’s the same with criticism of religion. We know that, when we criticise various religious doctrines, it may inflame jihadist zeal. How dare you offend our holy book, and dishonour our exalted prophet, the jihadists thunder, when they cannot bear to hear our criticisms. But that shouldn’t lead us to cowed silence – especially when we’re aware of ways in which religious doctrines are damaging individuals and societies (by opposition to vaccinations or blood transfusions, or by denying female education).

Instead of silence (avoiding the topic altogether), what these worries should lead us to is a more responsible, inclusive, measured conversation. That applies for the drawbacks of religion. And it applies, too, for the potential drawbacks of AGI.

Engaging conversation

The conversation I envisage will still have its share of poetic effect – with risks and opportunities temporarily painted more colourfully than a fully sober evaluation warrants. If we want to engage people in conversation, we sometimes need to make dramatic gestures. To squeeze a message into a 140 character-long tweet, we sometimes have to trim the corners of proper spelling and punctuation. Similarly, to make people stop in their tracks, and start to pay attention to a topic that deserves fuller study, some artistic license may be appropriate. But only if that artistry is quickly backed up with a fuller, more dispassionate, balanced analysis.

What I’ve described here is a two-phase model for spreading ideas about disruptive technologies such as AGI:

  1. Key topics can be introduced, in vivid ways, using larger-than-life characters in absorbing narratives, whether in Hollywood or in novels
  2. The topics can then be rounded out, in multiple shades of grey, via film and book reviews, blog posts, magazine articles, and so on.

Since I perceive both the potential upsides and the potential downsides of AGI as being enormous, I want to enlarge the pool of people who are thinking hard about these topics. I certainly don’t want the resulting discussion to slide off to an extreme point of view which would cause the whole field of AGI to be suspended, or which would encourage active sabotage and armed resistance against it. But nor do I want the discussion to wither away, in a way that would increase the likelihood of adverse unintended outcomes from aberrant AGI.

Welcoming Pandora’s Brain

cropped-cover-2That’s why I welcome the recent publication of the novel “Pandora’s Brain”, by the above-mentioned blogger Calum Chace. Pandora’s Brain is a science and philosophy thriller that transforms a series of philosophical concepts into vivid life-and-death conundrums that befall the characters in the story. Here’s how another science novellist, William Hertling, describes the book:

Pandora’s Brain is a tour de force that neatly explains the key concepts behind the likely future of artificial intelligence in the context of a thriller novel. Ambitious and well executed, it will appeal to a broad range of readers.

In the same way that Suarez’s Daemon and Naam’s Nexus leaped onto the scene, redefining what it meant to write about technology, Pandora’s Brain will do the same for artificial intelligence.

Mind uploading? Check. Human equivalent AI? Check. Hard takeoff singularity? Check. Strap in, this is one heck of a ride.

Mainly set in the present day, the plot unfolds in an environment that seems reassuringly familiar, but which is overshadowed by a combination of both menace and promise. Carefully crafted, and absorbing from its very start, the book held my rapt attention throughout a series of surprise twists, as various personalities react in different ways to a growing awareness of that menace and promise.

In short, I found Pandora’s Brain to be a captivating tale of developments in artificial intelligence that could, conceivably, be just around the corner. The imminent possibility of these breakthroughs cause characters in the book to re-evaluate many of their cherished beliefs, and will lead most readers to several “OMG” realisations about their own philosophies of life. Apple carts that are upended in the processes are unlikely ever to be righted again. Once the ideas have escaped from the pages of this Pandora’s box of a book, there’s no going back to a state of innocence.

But as I said, not everyone is enthralled by the prospect of wider attention to the “menace” side of AGI. Each new novel or film in this space has the potential of stirring up a negative backlash against AGI researchers, potentially preventing them from doing the work that would deliver the powerful “promise” side of AGI.

The dual potential of AGI

FLIThe tremendous dual potential of AGI was emphasised in an open letter published in January by the Future of Life Institute:

There is now a broad consensus that AI research is progressing steadily, and that its impact on society is likely to increase. The potential benefits are huge, since everything that civilization has to offer is a product of human intelligence; we cannot predict what we might achieve when this intelligence is magnified by the tools AI may provide, but the eradication of disease and poverty are not unfathomable. Because of the great potential of AI, it is important to research how to reap its benefits while avoiding potential pitfalls.

“The eradication of disease and poverty” – these would be wonderful outcomes from the project to create AGI. But the lead authors of that open letter, including physicist Stephen Hawking and AI professor Stuart Russell, sounded their own warning note:

Success in creating AI would be the biggest event in human history. Unfortunately, it might also be the last, unless we learn how to avoid the risks. In the near term, world militaries are considering autonomous-weapon systems that can choose and eliminate targets; the UN and Human Rights Watch have advocated a treaty banning such weapons. In the medium term, as emphasised by Erik Brynjolfsson and Andrew McAfee in The Second Machine Age, AI may transform our economy to bring both great wealth and great dislocation…

One can imagine such technology outsmarting financial markets, out-inventing human researchers, out-manipulating human leaders, and developing weapons we cannot even understand. Whereas the short-term impact of AI depends on who controls it, the long-term impact depends on whether it can be controlled at all.

They followed up with this zinger:

So, facing possible futures of incalculable benefits and risks, the experts are surely doing everything possible to ensure the best outcome, right? Wrong… Although we are facing potentially the best or worst thing to happen to humanity in history, little serious research is devoted to these issues outside non-profit institutes… All of us should ask ourselves what we can do now to improve the chances of reaping the benefits and avoiding the risks.


Critics give a number of reasons why they see these fears as overblown. To start with, they argue that the people raising the alarm – Stephen Hawking, serial entrepreneur Elon Musk, Oxford University philosophy professor Nick Bostrom, and so on – lack their own expertise in AGI. They may be experts in black hole physics (Hawking), or in electric cars (Musk), or in academic philosophy (Bostrom), but that gives them no special insights into the likely course of development of AGI. Therefore we shouldn’t pay particular attention to what they say.

A second criticism is that it’s premature to worry about the advent of AGI. AGI is still situated far into the future. In this view, as stated by Demis Hassabis, founder of DeepMind,

We’re many, many decades away from anything, any kind of technology that we need to worry about.

The third criticism is that it will be relatively simple to stop AGI causing any harm to humans. AGI will be a tool to humans, under human control, rather than having its own autonomy. This view is represented by this tweet by science populariser Neil deGrasse Tyson:

Seems to me, as long as we don’t program emotions into Robots, there’s no reason to fear them taking over the world.

I hear all these criticisms, but they’re by no means the end of the discussion. They’re no reason to terminate the discussion about AGI risks. That’s the argument I’m going to make in the remainder of this blogpost.

By the way, you’ll find all these of these criticisms mirrored in the course of the novel Pandora’s Brain. That’s another reason I recommend that people should read that book. It manages to bring a great deal of serious arguments to the table, in the course of entertaining (and sometimes frightening) the reader.

Answering the criticisms: personnel

Elon Musk, one of the people who have raised the alarm about AGI risks, lacks any PhD in Artificial Intelligence to his name. It’s the same with Stephen Hawking and with Nick Bostrom. On the other hand, others who are raising the alarm do have relevant qualifications.

AI a modern approachConsider as just one example Stuart Russell, who is a computer-science professor at the University of California, Berkeley and co-author of the 1152-page best-selling text-book “Artificial Intelligence: A Modern Approach”. This book is described as follows:

Artificial Intelligence: A Modern Approach, 3rd edition offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Number one in its field, this textbook is ideal for one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence.

Moreover, other people raising the alarm include some the giants of the modern software industry:

Wozniak put his worries as follows – in an interview for the Australian Financial Review:

“Computers are going to take over from humans, no question,” Mr Wozniak said.

He said he had long dismissed the ideas of writers like Raymond Kurzweil, who have warned that rapid increases in technology will mean machine intelligence will outstrip human understanding or capability within the next 30 years. However Mr Wozniak said he had come to recognise that the predictions were coming true, and that computing that perfectly mimicked or attained human consciousness would become a dangerous reality.

“Like people including Stephen Hawking and Elon Musk have predicted, I agree that the future is scary and very bad for people. If we build these devices to take care of everything for us, eventually they’ll think faster than us and they’ll get rid of the slow humans to run companies more efficiently,” Mr Wozniak said.

“Will we be the gods? Will we be the family pets? Or will we be ants that get stepped on? I don’t know about that…

And here’s what Bill Gates said on the matter, in an “Ask Me Anything” session on Reddit:

I am in the camp that is concerned about super intelligence. First the machines will do a lot of jobs for us and not be super intelligent. That should be positive if we manage it well. A few decades after that though the intelligence is strong enough to be a concern. I agree with Elon Musk and some others on this and don’t understand why some people are not concerned.

Returning to Elon Musk, even his critics must concede he has shown remarkable ability to make new contributions in areas of technology outside his original specialities. Witness his track record with PayPal (a disruption in finance), SpaceX (a disruption in rockets), and Tesla Motors (a disruption in electric batteries and electric cars). And that’s even before considering his contributions at SolarCity and Hyperloop.

Incidentally, Musk puts his money where his mouth is. He has donated $10 million to the Future of Life Institute to run a global research program aimed at keeping AI beneficial to humanity.

I sum this up as follows: the people raising the alarm in recent months about the risks of AGI have impressive credentials. On occasion, their sound-bites may cut corners in logic, but they collectively back up these sound-bites with lengthy books and articles that deserve serious consideration.

Answering the criticisms: timescales

I have three answers to the comment about timescales. The first is to point out that Demis Hassabis himself sees no reason for any complacency, on account of the potential for AGI to require “many decades” before it becomes a threat. Here’s the fuller version of the quote given earlier:

We’re many, many decades away from anything, any kind of technology that we need to worry about. But it’s good to start the conversation now and be aware of as with any new powerful technology it can be used for good or bad.

(Emphasis added.)

Second, the community of people working on AGI has mixed views on timescales. The Future of Life Institute ran a panel discussion in Puerto Rico in January that addressed (among many other topics) “Creating human-level AI: how and when”. Dileep George of Vicarious gave the following answer about timescales in his slides (PDF):

Will we solve the fundamental research problems in N years?

N <= 5: No way
5 < N <= 10: Small possibility
10 < N <= 20: > 50%.

In other words, in his view, there’s a greater than 50% chance that artificial general human-level intelligence will be solved within 20 years.

SuperintelligenceThe answers from the other panellists aren’t publicly recorded (the event was held under Chatham House rules). However, Nick Bostrom has conducted several surveys among different communities of AI researchers. The results are included in his book Superintelligence: Paths, Dangers, Strategies. The communities surveyed included:

  • Participants at an international conference: Philosophy & Theory of AI
  • Participants at another international conference: Artificial General Intelligence
  • The Greek Association for Artificial Intelligence
  • The top 100 cited authors in AI.

In each case, participants were asked for the dates when they were 90% sure human-level AGI would be achieved, 50% sure, and 10% sure. The average answers were:

  • 90% likely human-level AGI is achieved: 2075
  • 50% likely: 2040
  • 10% likely: 2022.

If we respect what this survey says, there’s at least a 10% chance of breakthrough developments within the next ten years. Therefore it’s no real surprise that Hassabis says

It’s good to start the conversation now and be aware of as with any new powerful technology it can be used for good or bad.

Third, I’ll give my own reasons for why progress in AGI might speed up:

  • Computer hardware is likely to continue to improve – perhaps utilising breakthroughs in quantum computing
  • Clever software improvements can increase algorithm performance even more than hardware improvements
  • Studies of the human brain, which are yielding knowledge faster than ever before, can be translated into “neuromorphic computing”
  • More people are entering and studying AI than ever before, in part due to MOOCs, such as that from Stanford University
  • There are more software components, databases, tools, and methods available for innovative recombination
  • AI methods are being accelerated for use in games, financial trading, malware detection (and in malware itself), and in many other industries
  • There could be one or more “Sputnik moments” causing society to buckle up its motivation to more fully support AGI research (especially when AGI starts producing big benefits in healthcare diagnosis).

Answering the critics: control

I’ve left the hardest question to last. Could there be relatively straightforward ways to keep AGI under control? For example, would it suffice to avoid giving AGI intentions, or emotions, or autonomy?

For example, physics professor and science populariser Michio Kaku speculates as follows:

No one knows when a robot will approach human intelligence, but I suspect it will be late in the 21st century. Will they be dangerous? Possibly. So I suggest we put a chip in their brain to shut them off if they have murderous thoughts.

And as mentioned earlier, Neil deGrasse Tyson proposes,

As long as we don’t program emotions into Robots, there’s no reason to fear them taking over the world.

Nick Bostrom devoted a considerable portion of his book to this “Control problem”. Here are some reasons I think we need to continue to be extremely careful:

  • Emotions and intentions might arise unexpectedly, as unplanned side-effects of other aspects of intelligence that are built into software
  • All complex software tends to have bugs; it may fail to operate in the way that we instruct it
  • The AGI software will encounter many situations outside of those we explicitly anticipated; the response of the software in these novel situations may be to do “what we asked it to do” but not what we would have wished it to do
  • Complex software may be vulnerable to having its functionality altered, either by external hacking, or by well-intentioned but ill-executed self-modification
  • Software may find ways to keep its inner plans hidden – it may have “murderous thoughts” which it prevents external observers from noticing
  • More generally, black-box evolution methods may result in software that works very well in a large number of circumstances, but which will go disastrously wrong in new circumstances, all without the actual algorithms being externally understood
  • Powerful software can have unplanned adverse effects, even without any consciousness or emotion being present; consider battlefield drones, infrastructure management software, financial investment software, and nuclear missile detection software
  • Software may be designed to be able to manipulate humans, initially for purposes akin to advertising, or to keep law and order, but these powers may evolve in ways that have worse side effects.

A new Columbus?

christopher-columbus-shipsA number of the above thoughts started forming in my mind as I attended the Singularity University Summit in Seville, Spain, a few weeks ago. Seville, I discovered during my visit, was where Christopher Columbus persuaded King Ferdinand and Queen Isabella of Spain to fund his proposed voyage westwards in search of a new route to the Indies. It turns out that Columbus succeeded in finding the new continent of America only because he was hopelessly wrong in his calculation of the size of the earth.

From the time of the ancient Greeks, learned observers had known that the earth was a sphere of roughly 40 thousand kilometres in circumference. Due to a combination of mistakes, Columbus calculated that the Canary Islands (which he had often visited) were located only about 4,440 km from Japan; in reality, they are about 19,000 km apart.

Most of the countries where Columbus pitched the idea of his westward journey turned him down – believing instead the figures for the larger circumference of the earth. Perhaps spurred on by competition with the neighbouring Portuguese (who had, just a few years previously, successfully navigated to the Indian ocean around the tip of Africa), the Spanish king and queen agreed to support his adventure. Fortunately for Columbus, a large continent existed en route to Asia, allowing him landfall. And the rest is history. That history included the near genocide of the native inhabitants by conquerors from Europe. Transmission of European diseases compounded the misery.

It may be the same with AGI. Rational observers may have ample justification in thinking that true AGI is located many decades in the future. But this fact does not deter a multitude of modern-day AGI explorers from setting out, Columbus-like, in search of some dramatic breakthroughs. And who knows what intermediate forms of AI might be discovered, unexpectedly?

It all adds to the argument for keeping our wits fully about us. We should use every means at our disposal to think through options in advance. This includes well-grounded fictional explorations, such as Pandora’s Brain, as well as the novels by William Hertling. And it also includes the kinds of research being undertaken by the Future of Life Institute and associated non-profit organisations, such as CSER in Cambridge, FHI in Oxford, and MIRI (the Machine Intelligence Research Institute).

Let’s keep this conversation open – it’s far too important to try to shut it down.

Footnote: Vacancies at the Centre for the Study of Existential Risk

I see that the Cambridge University CSER (Centre for the Study of Existential Risk) have four vacancies for Research Associates. From the job posting:

Up to four full-time postdoctoral research associates to work on the project Towards a Science of Extreme Technological Risk (ETR) within the Centre for the Study of Existential Risk (CSER).

CSER’s research focuses on the identification, management and mitigation of possible extreme risks associated with future technological advances. We are currently based within the University’s Centre for Research in the Arts, Social Sciences and Humanities (CRASSH). Our goal is to bring together some of the best minds from academia, industry and the policy world to tackle the challenges of ensuring that powerful new technologies are safe and beneficial. We focus especially on under-studied high-impact risks – risks that might result in a global catastrophe, or even threaten human extinction, even if only with low probability.

The closing date for applications is 24th April. If you’re interested, don’t delay!

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