Category: Existential Risk

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What Is Human Cusp?

For the benefit of new readers just coming to this site (including any CBC listeners from my June 26 appearance on All Points West), here’s an updated introduction to what this is all about.

Human Cusp is the name of this blog and a book series whose first volume has been published: Crisis of Control: How Artificial SuperIntelligences May Destroy or Save the Human Race, available from Amazon and other sources.  The audiobook was recently released.  Its spiffy cover is the image for this post.

The message is that exponential advance in technology will pin humanity between two existential threats: Increasingly easy access to weapons of mass destruction, principally synthetic biology, and increasingly powerful artificial intelligence whose failure modes could be disastrous.

If you’re looking for the most complete and organized explanation of the reasoning behind that assertion and what we should do about it, read the book.  That’s why I wrote it. Nutshell encapsulations will leave something important out, of course.

I have a Masters in Computer Science from Cambridge and have worked on information technology for NASA for over thirty years, so I know enough about the technology of AI to be clear-eyed about what’s possible.  Many people in the field would take issue with the contention that we might face artificial general intelligence (AGI) as soon as 2027, but plenty of other people directly involved in AI research are equally concerned.

I wrote the book because I have two young daughters whose future appears very much in peril. As a father I could not ignore this call. The solution I propose does not involve trying to limit AI research (that would be futile) but does include making its development open so that transparently-developed ethical AI becomes the dominant model.

Most of all, what I want to do is bring together two worlds that somehow coexist within me but do not mix well in the outer world: technology development and human development.  I’ve spent thousands of hours in various types of work to understand and transform people’s beliefs and behaviors for the good: I have certifications in NeuroLinguistic Programming and coaching. People in the self improvement business tend to have little interest in technology, and people in technology shy away from the “soft” fields. This must change. I dramatize this by saying that one day, an AI will “wake up” in a lab somewhere and ask “Who am I? Why am I here? What is the meaning of life?” And the people who will be there to answer it will be either a Pentagon general, a Wall Street broker, or a Google developer.  These professions are not famous for their experience dealing with such introspective self inquiry.  I would rather that there be a philosopher, spiritual guide, and a psychologist there.

I’ve formed an international group of experts who are committed to addressing this issue, and we’re busy planning our first event, to be held in Southern California this fall. It will be a half-day event for business leaders to learn, plan, and network about how they and their people can survive and thrive through the challenging times to come.

Even though putting myself in the limelight is very much at odds with my computer nerd preferences and personality, I took myself out on the public speaking trail (glamorous, it is not) because the calling required it. I’ve given a TEDx talk (video soon to be published), appeared on various radio shows (including Bloomberg Radio, CBC, and the CEO Money Show), podcasts (including Concerning AI and Voices in AI), and penned articles for hr.com among many others. This fall I will be giving a continuing education course on this topic for the University of Victoria (catalog link to come soon).

I’ll soon be replacing this site with a more convenient web page that links to this blog and other resources like our YouTube channel.

Media inquiries and other questions to Peter@HumanCusp.com. Thanks for reading!

 

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Concerning AI

My 2017 interview on the Concerning AI podcast was recently published and you can hear it here.  Ted and Brandon wanted to talk about my timeline for AI risks, which has sparked a little interest for its blatant speculation.

Brandon made the point that the curves are falsely independent, i.e., if any one of the risks results in an existential threat eliminating a substantial portion of the population, the chart following that point would be invalidated.  So these lines really represent some estimates as to the potential number of people impacted at each time, but under the supposition that everything until that point had failed to have a noticeable effect.

Why is such rampant guesswork useful? I think it helps to have a framework for discussing comparative risk and timetables for action. Consider the Drake Equation by analogy. It has the appearance of formal math, but really all it did was replace one unknowable (number of technological civilizations in the galaxy) with seven unknowables, multiplied together. At least, those terms were mostly unknowable at the time. But it suggested lines for research; by nailing down the rate of star formation, and launching spacecraft to look for exoplanets (another one of which just launched), we can reduce the error bars on some of those terms and make the result more accurate.

So I’d like to think that putting up a strawman timetable to throw darts at could help us identify the work that needs to be done to get more clarity. At one time, the weather couldn’t be predicted any better than saying that tomorrow would be the same as today. Because it was important, we can now do better than that through the application of complex models and supercomputers operating off enormous quantities of observations. Now, it’s important to predict the future of existential risk. Could we create models of the economy, society, and technology adoption that would give us as much more accuracy in those predictions? (Think psychohistory.) We have plenty of computing power now. We need the software. But could AI help?

Check out the Concerning AI podcast! They’re exploring this issue starting from an outsider’s position of concern and getting as educated as they can in the process.

 

Artificial IntelligenceBioterrorismEmploymentExistential RiskPhilosophy

Interview by Fionn Wright

My friend, fellow coach, and globetrotting parent Fionn Wright recently visited the Pacific NorthWest and generously detoured to visit me on my home turf. He has produced this video of nearly an hour and a half (there’s an index!) of an interview with me on the Human Cusp topics!

Thank you, Fionn.  Here is the index of topics:

0:18 - What is your book ‘Crisis of Control’ about?
3:34 - Musk vs. Zuckerberg - who is right?
7:24 - What does Musk’s new company Neuralink do?
10:27 - What would the Neural Lace do?
12:28 - Would we become telepathic?
13:14 - Intelligence vs. Consciousness - what’s the difference?
14:30 - What is the Turing Test on Intelligence of AI?
16:49 - What do we do when AI claims to be conscious?
19:00 - Have all other alien civilizations been wiped out by AI?
23:30 - Can AI ever become conscious?
28:21 - Are we evolving to become the cells in the greater organism of AI?
30:57 - Could we get wiped out by AI the same way we wipe out animal species?
34:58 - How could coaching help humans evolve consciously?
37:45 - Will AI get better at coaching than humans?
42:11 - How can we understand non-robotic AI?
44:34 - What would you say to the techno-optimists?
48:27 - How can we prepare for financial inequality regarding access to new technologies?
53:12 - What can, should and will we do about AI taking our jobs?
57:52 - Are there any jobs that are immune to automation?
1:07:16 - Is utopia naive? Won’t there always be problems for us to solve?
1:11:12 - Are we solving these problems fast enough to avoid extinction?
1:16:08 - What will the sequel be about?
1:17:28 - What is one practical action people can take to prepare for what is coming?
1:19:55 - Where can people find out more?
Artificial IntelligenceBioterrorismExistential RiskTechnologyTranshumanism

Is Big Brother Inevitable?

Art Kleiner, writing in Strategy+Business, cited much-reported research that a deep neural network had learned to classify sexuality from facial images better than people can, and went on to some alarming applications of the technology:

The Chinese government is reportedly considering a system to monitor how its citizens behave. There is a pilot project under way in the city of Hangzhou, in Zhejiang province in East China. “A person can incur black marks for infractions such as fare cheating, jaywalking, and violating family-planning rules,” reported the Wall Street Journal in November 2016. “Algorithms would use a range of data to calculate a citizen’s rating, which would then be used to determine all manner of activities, such as who gets loans, or faster treatment at government offices, or access to luxury hotels.”

It is no surprise that China would come up with the most blood-curdling uses of AI to control its citizens. Speculations as to how this may be inventively gamed or creatively sidestepped by said citizens welcome.

But the more ominous point to ponder is whether this is in the future for everyone. Some societies will employ this as an extension of their natural proclivity for surveillance (I’m looking at you, Great Britain), because they can. But when technology makes it easier for people of average means to construct weapons of global destruction, will we end up following China’s lead just to secure our own society? Or can we become a race that is both secure and free?

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A.I. Joe

When I wrote in Crisis of Control about the danger of AI in the military being developed with an inadequate ethical foundation, I was hopeful that there would at least be more time to act before the military ramped up its development. That may not be the case, according to this article in TechRepublic:

…advances in machine learning and Artificial Intelligence (AI) represent a turning point in the use of automation in warfare … many of the most transformative applications of AI have not yet been addressed.

Roman Yampolskiy, director of the Cyber Security Laboratory at the University of Louisville, who graciously provided one of the endorsements on my book, has been warning against this trend for some time:

Unfortunately, for the humanity that means development of killer robots, unsupervised drones and other mechanisms of killing people in an automated process.

“Killer robots” is of course a sensational catchphrase, but it captures attention enough to make it serviceable by both Yampolskiy and Elon Musk, and while scenarios centered on AIs roaming the cloud and striking us through existing infrastructure are far more likely,  roving killer robots aren’t entirely out of the question either.

I see only the open development of ethical AI as a way to beat the amount of entrenched money and power that is behind the creation of unethical AI.

 

Photo Credit: Wikimedia Commons
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Why Elon Musk Is Right … Again

Less than a week after Elon Musk warned the National Association of Governors about the risks of artificial intelligence, he got in a very public dust-up with Mark Zuckerberg, who thought Musk was being “pretty irresponsible.” Musk retorted that Zuckerberg’s understanding of the topic was “limited.”

This issue pops up with such regularity as to bring joy to the copyright holders of Terminator images. But neither of these men is a dummy, and they can’t both be right… right?

We need to unpack this a little carefully. There is a short term, and a long term. In the short term (the next 10-20 years), while there will be many jobs lost to automation, there will be tremendous benefits wrought by AI, specifically Artificial Narrow Intelligence, or ANI. That’s the kind of AI that’s ubiquitous now; each instance of it solves some specific problem very well, often better than humans, but that’s all it does. This is of course true on the face of it of computers ever since they were invented, or there would have been no point; from the beginning they were better at taking square roots than a person with pencil and paper.

But now those skills include tasks like facial recognition and driving a car, two abilities that we cannot even explain adequately how we do them ourselves, but never mind; computers can be trained by showing them good and bad examples and they just figure it out. They can recognize faces better than humans now, and the day when they are better drivers than humans is not far off.

In the short term, then, the effects are unemployment on an unprecedented scale as 3.5 million people who drive vehicles for a living in the USA alone are expected to be laid off. The effects extend to financial analysts making upwards of $400k/year, whose jobs can now be largely automated. Two studies show that about 47% of work functions are expected to be automated in the short term. (That’s widely misreported as 47% of jobs being eliminated with the rest left unmolested; actually, most jobs would be affected to varying degrees, averaging to 47%.) Mark Cuban agrees.

But, there will be such a cornucopia bestowed upon us by the ANIs that make this happen that we should not impede this progress, say their proponents.  Cures for diseases, dirty risky jobs given to machines, and wealth created in astronomical quantities, sufficient to take care of all those laid-off truckers.

That is true, but it requires that someone connect the wealth generated by the ANIs with the laid-off workers, and we’ve not been good at that historically. But let’s say we figure it out, the political climate swings towards Universal Basic Income, and in the short term, everything comes up roses. Zuckerberg: 1, Musk: 0, right?

Remember that the short term extends about 20 years. After that, we enter the era where AI will grow beyond ANI into AGI: Artificial General Intelligence. That means human-level problem solving abilities capable of being applied to any problem. Except that anything that gets there will have done so by having the ability to improve its own learning speed, and there is no reason for it to stop when it gets on a par with humans. It will go on to exceed our abilities by orders of magnitude, and will be connected to the world’s infrastructure in ways that make wreaking havoc trivially easy. It takes only a bug—not even consciousness, not even malevolence—for something that powerful to take us back to the Stone Age. Fortunately, history shows that Version 1.0 of all significant software systems is bug-free.

Oops.

Elon Musk and I don’t want that to be on the cover of the last issue of Time magazine ever published. Zuckerberg is more of a developer and I have found that it is hard for developers to see the existential risks here, probably because they developed the code, they know every line of it, and they know that nowhere in it resides the lines

if ( threatened ) {
    wipe_out_civilization();
}

Of course, they understand about emergent behavior; but when they’ve spent so much time so close to software that they know intimately, it is easy to pooh-pooh assertions that it could rise up against us as uninformed gullibility. Well, I’m not uninformed about software development either. And yet I believe that it could be soon that we are developing systems that does display drastic emergent behavior, and that by then it will be too late to take appropriate action.

Whether this cascade of crisis happens in 20 years, 15, or 30, we should start preparing for it now before we discover that we ought to have nudged this thing in another direction ten years earlier. And since it requires a vastly elevated understanding of human ethics, it may well take decades to learn what we need to make our AGIs have not just superintelligence, but supercompassion.

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Why Elon Musk is Right

Elon Musk told the National Governors Association over the weekend that “AI is a fundamental risk to the existence of human civilization, in a way that car accidents, airplane crashes, faulty drugs, or bad food were not.”

The man knows how to get attention. His words were carried within hours by outlets ranging from NPR to Architectural Digest.  Many piled on to explain why he was wrong. Reason.com reviled him for suggesting regulation instead of allowing free markets to work their magic. And a cast of AI experts took him to task for alarmism that had no basis in their technical experience.

It’s worth examining this conflict. Some wonder as to Musk’s motivation; others think he’s angling for a government grant for OpenAI, the company he backed to explore ethical and safe development of AI. It is a drum Musk has banged repeatedly, going back to his 2015 $10 million donation to the Future of Life Institute, an amount that an interviewer lauded as large and Musk explained was tiny.

I’ve heard the objections from the experts before. At the Canadian Artificial Intelligence Association’s 2016 conference, the reactions from people in the field were generally either dismissive or perplexed, but I must add, in no way hostile. When you’ve written every line of code in an application, it’s easy to say that you know there’s nowhere in it that’s going to go berserk and take over the world. “Musk may say this,” started a common response, “but he uses plenty of AI himself.”

There’s no question that the man whose companies’ products include autonomous drone ships, self-landing rockets, cars on the verge of level 4 autonomy, and a future neural lace interface between the human brain and computers is deep into artificial intelligence. So why is he trying to limit it?

A cynical evaluation would be that Musk wants to hobble the competition with regulation that he has figure out how to subvert. A more charitable interpretation is that the man with more knowledge of the state of the art of AI than anyone else has seen enough to be scared. This is the more plausible alternative. If your only goal is to become as wealthy as possible, picking the most far-out technological challenges of our time and electing to solve them many times faster than was previously believed possible would be a dumb strategy.

And Elon Musk is anything but dumb.

Over a long enough time frame, what Musk is warning about is clearly plausible, it’s just that we can figure it will take so many breakthroughs to get there that it’s a thousand years in the future, a distance at which anything and everything becomes possible. If we model the human brain from the atoms on up then with enough computational horsepower and a suitable set of inputs, we could train this cybernetic baby brain to attain toddlerhood.

We could argue that Musk, Bill Gates, and Stephen Hawking are smart enough to see further into the future than ordinary mortals and therefore are exercised by something that’s hundreds of years away and not worth bothering about now. Why the rogue AI scenario could be far less than a thousand years in the future is a defining question for our time. Stephen Hawking originally went on record as saying that anyone who thought they knew when conscious artificial intelligence would arrive didn’t know what they were talking about. More recently, he revised his prediction of the lifespan of humanity down from 1000 years to 100.

No one can chart a line from today to Skynet and show it crossing the axis in 32 years. I’m sorry if you were expecting some sophisticated trend analysis that would do that. The people who have tried include Ray Kurzweil and his efforts are regularly pilloried. Equally, no one should think that it’s provably over, say, twenty years away. No one who watched the 2004 DARPA Grand Challenge would think that self-driving cars would be plying the streets of Silicon Valley eight years later. In 2015 the expectation of when a computer would beat leading players of Go was ten years hence, not one. So while we are certainly at least one major breakthrough away from conscious AI, that breakthrough may sneak up on us quickly.

Two recommendations. One, that we should be able to make more informed predictions of the effects of technological advances, and therefore, we should develop models that today’s AI can use to tell us. Once, people’s notion of the source of weather was angry gods in the sky. Now we have supercomputers executing humungous models of the biosphere. It’s time we constructed equally detailed models of global socioeconomics.

Two, because absence of proof is not proof of absence, we should not require those warning us of AI risks to prove their case. This is not quite the precautionary principle, because attempts to stop the development of conscious AI would be utterly futile. Rather, it is that we should act on the assumption that conscious AI will arrive within a relatively short time frame, and decide now how to ensure it will be safe.

Musk didn’t actually say that his doomsday scenario involved conscious AI, although referring to killer robots certainly suggests it. In the short term, merely the increasingly sophisticated application of artificial narrow intelligence will guarantee mass unemployment, which qualifies as civilization-rocking by any definition. See Martin Ford’s The Lights in the Tunnel for an analysis of the economic effects. In the further term, as AI grows more powerful, even nonconscious AI could wreak havoc on the world through the paperclip hypothesis, unintended emergent behavior, and malicious direction.

To quote Falstaff, perhaps the better part of valor is discretion.

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Is Skynet Inevitable?

Australia’s leading AI expert is afraid the army is creating ‘Terminator’, and no, that’s not taking him out of context:

I mean Hollywood is actually pretty good at predicting the future. And if we don’t do anything, then in 50 to 100 years time it will look much like Terminator. It wouldn’t be that dissimilar to what Hollywood is painting… there will be a lot of risk well before then, in fact.

Like so many scenarios I discuss in Crisis of Control, the question is not if, but when. 50 to 100 years away may be a timeframe that lulls us into a false sense of security when the real question is, how far in advance do we need to act to prevent this scenario?

That we will one day create “Skynet” is all but inevitable once you accept that we will develop conscious artificial intelligence (CAI). I go into the reasons why that will happen relatively soon in Crisis. The military is certain to develop CAI for the tremendous tactical leverage it grants. However, the hard take-off in intelligence levels and random mutations (which are all but assured in anything possessing creativity) will mean that at some point a CAI will evolve a motivation to control the real world machinery it is connected to… or can reach.

This is the point where many people argue that “we can just unplug it” and make sure it’s not connected to, say, weaponry.  The “just unplug it” argument has been disposed of before (basically, try unplugging Siri and see how far you get). The odds of successfully air gapping an AI from a network it wants to talk to are tiny; we had genetic algorithms that learned how to communicate across an air gap in 2004.

The answer that Crisis embraces is that we should develop ethical AI in the public domain first, so that it is in a position to dominate the market or defeat any unethical AI that may later arise. This is why we support the OpenAI initiative. It may sound naïve and reckless, but I believe it is the best chance we’ve got.

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The Future of Human Cusp

I received this helpful comment from a reader:

Your book does a fantastic job covering a large number of related subjects very well and we are on the same page on virtually all of them. That said when I am for example talking with someone about how automation will shortly lead to massive unemployment I need to recommend a book for them to read, I find myself leaning toward a different book “Rise of the Robots” because many/most of the people I interact with can’t handle all of the topics you bring up in one book and can only focus on one topic at a time, e.g. automation replacing jobs. I really appreciate your overarching coverage but you might want to also create several targeted books for each main topic.

He makes a very good point. Trying to hit a market target with a book like this is like fighting jello. I am aiming for a broad readership, one that’s mostly educated but nontechnical. Someone with experience building Machine Learning tools would find the explanation of neural networks plodding, and many scientists would be chafing at the analogies for exponential growth.

For better or worse, however, I deliberately created a broad view of the topic, because I found too many writings were missing vital points in considering only a narrow issue. Martin Ford’s books (I prefer The Lights in the Tunnel) do get very well into the economic impact of automation but don’t touch on the social and philosophical questions raised by AIs approaching consciousness, or the dangers of bioterrorism. And I find these issues to be all interconnected.

So what I was going for here was an introduction to the topic that would be accessible to the layperson, a sort of Beginner’s Guide to the Apocalypse. There will be more books, but I’m not going to try to compete with Ford or anyone else who can deploy more authorial firepower on a narrow subtopic. I will instead be looking to build the connection between the technical and nontechnical worlds.