They’re working on figuring out what we want the AGI to do
Aka friendliness research. But why does that matter? If the machine has no real effectors and lots of human oversight, then why should there even be concern over friendliness? It wouldn’t matter in that context. Tell a machine to do something, and it finds an evil-stupid way of doing it, and human intervention prevents any harm.
Why is it a going concern at all whether we can assure ahead of time that the actions recommended by a machine are human-friendly unless the machine is enabled to independently take those actions without human intervention? Just don’t do that and it stops being a concern.
Humanity is having trouble coordinating and enforcing even global restrictions in greenhouse gasses. Try ensuring that nobody does anything risky or short-sighted with a technology that has no clearly-cut threshold between a “safe” and “dangerous” level of capability, and which can be beneficial for performing in pretty much any competitive and financially lucrative domain.
Restricting the AI’s capabilities may work for a short while, assuming that only a small group of pioneers manages to develop the initial AIs and they’re responsible with their use of the technology—but as Bruce Schneier says, today’s top-secret programs become tomorrow’s PhD theses and the next day’s common applications. If we want to survive in the long term, we need to figure out how to make the free-acting AIs safe, too—otherwise it’s just a ticking time bomb before the first guys accidentally or intentionally release theirs.
Humanity has done more than zero and less that optimality about things like climate change. Importantly, the situation isbelow the immanent existential threat level.
If you are going to complain that alternative proposals face coordination problems, you need to show that yours dont, or you are committing the fallacy of the dangling comparision. If people aren’t going to refrain from building dangerously powerful superintellugences, assuming is possible, why would they have the sense to fit MIRIs safety features, assuming they are possible? If the law can make people fit safety features, why cant it prevent them building dangerous AIs ITFP?
no clearly-cut threshold between a “safe” and “dangerous” level of capability
I would suggest a combination of generality and agency.
And what problem domain requires both?
If you allow for autonomously acting AIs, then you could have Friendly autonomous AIs tracking down and stopping Unfriendly / unauthorized AIs.
This of course depends on people developing the Friendly AIs first, but ideally it’d be enough for only the first people to get the design right, rather than depending on everyone being responsible.
Importantly, the situation isbelow the immanent existential threat level.
It’s unclear whether AI risk will become obviously imminent, either. Goertzel & Pitt 2012 argue in section 3 of their paper that this is unlikely.
I would suggest a combination of generality and agency. And what problem domain requires both?
Business (which by nature covers just about every domain in which you can make a profit, which is to say just about every domain relevant for human lives), warfare, military intelligence, governance… (see also my response to Mark)
If you allow for autonomously acting AIs, then you could have Friendly autonomous AIs tracking down and stopping Unfriendly / unauthorized AIs.
You could, but if you don’t have autonomously acting agents, you don’t need Gort AIs.
Building an agentive superintelligence that is powerful enough to take down any othe, as as MIRI conceives it, is a very risky proposition, since you need to get the value system exactly right. So its better not to be in a place where you have to do that,
This of course depends on people developing the Friendly AIs first, but ideally it’d be enough for only the first people to get the design right, rather than depending on everyone being responsible.
The first people have to be able as well as willing to get everything right, Safety through restraint is easier and more reliable. -- you can omit a feature more reliably than you can add one.
Business (which by nature covers just about every domain in which you can make a profit, which is to say just about every domain relevant for human lives), warfare, military intelligence, governance…
These organizations have a need for widespread intelligence gathering , and for agentive
AI, but that doesn’t mean they need both in the same package. The military don’t need their entire intelligence database in every drone, and don’t want drones that change their mind about who the bad guys are in mid flight. Businesses don’t want HFT applications that decide capitalism is a bad thing.
We want agents to act on our behalf, which means we want agents that are predictable and controllable to the required extent. Early HFT had problems which led to the addition of limits and controls. Control and predictability are close to safety. There is no drive to power that is also a drive away from safety, because uncontrolled power is of no use.
Based on the behaviour of organisations, there seems to be natural division between high-level, unpredictable decision information systems and lower level, faster acting genitive systems. In other words, they voluntarily do some of what would be required for an incremental safety programme.
I agree that it would be better not to have autonomously acting AIs, but not having any autonomously acting AIs would require a way to prevent anyone deploying them, and so far I haven’t seen a proposal for that that’d seem even remotely feasible.
And if we can’t stop them from being deployed, then deploying Friendly AIs first looks like the scenario that’s more likely to work—which still isn’t to say very likely, but at least it seems to have a chance of working even in principle. I don’t see that an even-in-principle way for “just don’t deploying autonomous AIs” to work.
When you say autonomous AIs, do you mean AIs that are autonomous and superinteligent?
AIs that are initially autonomous and non-superintelligent, then gradually develop towards superintelligence. (With the important caveat that it’s unclear whether an AI needed to be generally superintelligent in order to pose a major risk for society. It’s conceivable that superintelligence in some more narrow domain, like cybersecurity, would be enough—particularly in a sufficiently networked society.)
Do you think they could he deployed by basement hackers, or only by large organisations?
Hard to say. The way AI has developed so far, it looks like the capability might be restricted to large organizations with lots of hardware resources at first, but time will likely drive down the hardware requirements.
Do you think an organisation like the military or business has a motivation to deploy them?
Yes.
Do you agree that there are dangers to an FAI project that goes wrong?
Yes.
Do you have a plan B to cope with a FAI that goes rogue?
Such a plan would seem to require lots of additional information about both the specifics of the FAI plan, and also the state of the world at that time, so not really.
Do you think that having a AI potentially running the world is an attractive idea to a lot of people?
Depends on how we’re defining “lots”, but I think that the notion of a benevolent dictator has often been popular in many circles, who’ve also acknowledged its largest problems to be that 1) power tends to corrupt 2) even if you got a benevolent dictator, you also needed a way to ensure that all of their successors were benevolent. Both problems could be overcome with an AI, so on that basis at least I would expect lots of people to find it attractive. I’d also expect it to be considered more attractive in e.g. China, where people seem to be more skeptical towards democracy than they are in the West.
Additionally, if the AI wouldn’t be the equivalent of a benevolent dictator, but rather had a more hands-off role that kept humans in power and only acted to e.g. prevent disease, violent crime, and accidents, then that could be attractive to a lot of people who preferred democracy.
When you say autonomous AIs, do you mean AIs that are autonomous and superinteligent?
AIs that are initially autonomous and non-superintelligent, then gradually develop towards superintelligence
If you believe in the conjunction of claims that people are motivated to create autonomous, not just agentive, AIs, and that pretty well any AI can evolve into dangerous superintelligence, then the situation is dire, because you cannot guarantee to get in first with an AI policeman as a solution to AI threat.
The situation is better, but only slightly better with legal restraint as a solution to AI threat, because you can lower the probability of disaster by banning autonomous AI...but you can only lower it, not eliminate it, because no ban is 100% effective.
And how serious are you about the threat level? Compare with micro biological research. It could be the case that someone will accidentally create an organism that spells doom for the human race, it cannot be ruled out, but no one is panicing now because there is no specific reason to rule it in, no specific pathway to it. It is a remote possibility, not a serious one.
Someone who sincerely believed that rapid self improvement towards autonomous AI could happen at any time, because there are no specific precondition or precursors for it, is someone who effectively believes it could happen now. But someone who genuinely believes an AI apocalypse could happen now is someone who would e revealing their belief in their behaviour by heading for the hills, or smashing every computer they see.
(With the important caveat that it’s unclear whether an AI needed to be generally superintelligent in order to pose a major risk for society.
Narrow superintelligences may well be less dangerous than general superintelligences, and if you are able to restrict the generality of an AI, that could be a path to incremental safety.
But if the path to some kind of spontaneous superintelligence in an autonomous AI is also a path to spontaneous generality, that is hopeless. -- if the one can happen for no particular reason, so can the other. But is the situation really bad, or are these scenarios remote possibilities, like genetically engineered super plagues?
Do you think they could he deployed by basement hackers, or only by large organisations?
Hard to say. The way AI has developed so far, it looks like the capability might be restricted to large organizations with lots of hardware resources at first, but time will likely drive down the hardware requirements.
But by the time the hardware requirements have been driven down for entry level AI, the large organizations will already have more powerful systems, and they will dominate for better or worse. If benevolent, they will supress dangerous AIs coming out of basements, if dangerous they will suppress
rivals. The only problematic scenario is where the hackers get in first, since they are less likely to partition agency from intelligence, as I have argued a large organisation would.
But the one thing we know for sure about AI is that it is hard.The scenario where a small team hits on the One Weird Trick to
achieve ASI is the most worrying, but also the least
likely.
Do you think an organisation like the military or business has a motivation to deploy [autonomous AI]?
Yes.
Which would be what?
Do you agree that there are dangers to an FAI project that goes wrong?
Yes.
Do you have a plan B to cope with a FAI that goes rogue?
Such a plan would seem to require lots of additional information about both the specifics of the FAI plan, and also the state of the world at that time, so not really.
But building an FAI capable of policing other AIs is potentially dangerous, since it would need to be both a general intelligence and super intelligence.
Do you think that having a AI potentially running the world is an attractive idea to a lot of people?
Depends on how we’re defining “lots”,
For the purposes of the current argument, a democratic majority.
but I think that the notion of a benevolent dictator has often been popular in many circles, who’ve also acknowledged its largest problems to be that 1) power tends to corrupt 2) even if you got a benevolent dictator, you also needed a way to ensure that all of their successors were benevolent. Both problems could be overcome with an AI,
There are actually three problems with benevolent dictators. As well. as power corrupting, and successorship, there is the problem of ensuring or detecting benevolence in the first place.
You have conceded that Gort AI is potentially dangerous. The danger is that it is fragile in a specific way: a near miss to a benevolent value system is a dangerous one,
so on that basis at least I would expect lots of people to find it attractive. I’d also expect it to be considered more attractive in e.g. China, where people seem to be more skeptical towards democracy than they are in the West.
Additionally, if the AI wouldn’t be the equivalent of a benevolent dictator, but rather had a more hands-off role that kept humans in power and only acted to e.g. prevent disease, violent crime, and accidents, then that could be attractive to a lot of people who preferred democracy
That also depends on both getting it right, and convincing people you have got it right
If you believe in the conjunction of claims that people are motivated to create autonomous, not just agentive, AIs, and that pretty well any AI can evolve into dangerous superintelligence, then the situation is dire, because you cannot guarantee to get in first with an AI policeman as a solution to AI threat.
The situation is better, but only slightly better with legal restraint as a solution to AI threat,
Indeed.
And how serious are you about the threat level? Compare with micro biological research. It could be the case that someone will accidentally create an organism that spells doom for the human race, it cannot be ruled out, but no one is panicing now because there is no specific reason to rule it in, no specific pathway to it. It is a remote possibility, not a serious one.
Someone who sincerely believed that rapid self improvement towards autonomous AI could happen at any time, because there are no specific precondition or precursors for it, is someone who effectively believes it could happen now. But someone who genuinely believes an AI apocalypse could happen now is someone who would e revealing their belief in their behaviour by heading for the hills, or smashing every computer they see.
I don’t think that rapid self-improvement towards a powerful AI could happen at any time. It’ll require AGI, and we’re still a long way from that.
Narrow superintelligences may well be less dangerous than general superintelligences, and if you are able to restrict the generality of an AI, that could be a path to incremental safety.
It could, yes.
But by the time the hardware requirements have been driven down for entry level AI, the large organizations will already have more powerful systems, and they will dominate for better or worse.
Assuming they can keep their AGI systems in control.
Do you think an organisation like the military or business has a motivation to deploy [autonomous AI]?
Yes.
Which would be what?
See my response here and also section 2 in this post.
But building an FAI capable of policing other AIs is potentially dangerous, since it would need to be both a general intelligence and super intelligence. [...] You have conceded that Gort AI is potentially dangerous. The danger is that it is fragile in a specific way: a near miss to a benevolent value system is a dangerous one,
I think you very much misunderstand my suggestion. I’m saying that there is no reason to presume AI will be given the keys to the kingdom from day one, not advocating for some sort of regulatory regime.
So what do you see as the mechanism that will prevent anyone from handing the AI those keys, given the tremendous economic pressure towards doing exactly that?
As with a boxed
AGI, there are many factors that would tempt the owners of
an Oracle AI to transform it to an autonomously acting agent.
Such an AGI would be far more effective in furthering its
goals, but also far more dangerous.
Current narrow-AI technology includes HFT algorithms,
which make trading decisions within fractions of a second, far
too fast to keep humans in the loop. HFT seeks to make a very
short-term profit, but even traders looking for a longer-term
investment benefit from being faster than their competitors.
Market prices are also very effective at incorporating various
sources of knowledge [135]. As a consequence, a trading
algorithmʼs performance might be improved both by making
it faster and by making it more capable of integrating various
sources of knowledge. Most advances toward general AGI
will likely be quickly taken advantage of in the financial
markets, with little opportunity for a human to vet all the
decisions. Oracle AIs are unlikely to remain as pure oracles
for long.
Similarly, Wallach [283] discuss the topic of autonomous
robotic weaponry and note that the US military is seeking to
eventually transition to a state where the human operators of
robot weapons are ‘on the loop’ rather than ‘in the loop’. In
other words, whereas a human was previously required to
explicitly give the order before a robot was allowed to initiate
possibly lethal activity, in the future humans are meant to
merely supervise the robotʼs actions and interfere if something
goes wrong.
Human Rights Watch [90] reports on a number of
military systems which are becoming increasingly autonomous,
with the human oversight for automatic weapons
defense systems—designed to detect and shoot down
incoming missiles and rockets—already being limited to
accepting or overriding the computerʼs plan of action in a
matter of seconds. Although these systems are better
described as automatic, carrying out pre-programmed
sequences of actions in a structured environment, than
autonomous, they are a good demonstration of a situation
where rapid decisions are needed and the extent of human
oversight is limited. A number of militaries are considering
the future use of more autonomous weapons.
In general, any broad domain involving high stakes,
adversarial decision making and a need to act rapidly is likely
to become increasingly dominated by autonomous systems.
The extent to which the systems will need general intelligence
will depend on the domain, but domains such as corporate
management, fraud detection and warfare could plausibly
make use of all the intelligence they can get. If oneʼs
opponents in the domain are also using increasingly
autonomous AI/AGI, there will be an arms race where one
might have little choice but to give increasing amounts of
control to AI/AGI systems.
Miller [189] also points out that if a person was close to
death, due to natural causes, being on the losing side of a war,
or any other reason, they might turn even a potentially
dangerous AGI system free. This would be a rational course
of action as long as they primarily valued their own survival
and thought that even a small chance of the AGI saving their
life was better than a near-certain death.
Some AGI designers might also choose to create less
constrained and more free-acting AGIs for aesthetic or moral
reasons, preferring advanced minds to have more freedom.
I thought my excerpt answered that, but maybe that was illusion of transparency speaking. In particular, this paragraph:
In general, any broad domain involving high stakes, adversarial decision making and a need to act rapidly is likely to become increasingly dominated by autonomous systems. The extent to which the systems will need general intelligence will depend on the domain, but domains such as corporate management, fraud detection and warfare could plausibly make use of all the intelligence they can get. If oneʼs opponents in the domain are also using increasingly autonomous AI/AGI, there will be an arms race where one might have little choice but to give increasing amounts of control to AI/AGI systems.
To rephrase: the main trend is history has been to automate everything that can be automated, both to reduce costs and because machines can do things better than humans do. This isn’t going to stop: I’ve already seen articles calling for both company middle managers, as well as government bureaucrats, to be replaced with AIs. If you have any kind of a business, you could potentially make it run better by putting a sufficiently sophisticated AI in charge—because it can think faster and smarter, deal with more information at once, and not have the issue of self-interest leading to office politics leading to many employees acting suboptimally from the company’s point of view, that you’d get if you had a thousand human employees rather than a single AI.
This trend has been going on throughout history, doesn’t show any signs of stopping, and inherently involves giving the AI systems whatever agency they need in order to run the company better.
And if your competitors are having AIs run their company and you don’t, you’re likely to be outcompeted, so you’ll want to make sure your AIs are smarter and more capable of acting autonomously than the competitors. These pressures aren’t just going to vanish at the point when AIs start approaching human capability.
The same considerations also apply to other domains than business—like governance—but the business and military domains are the most likely to have intense arms race dynamics going on.
Yes, illusion of transparency at work here. That paragraph has always been so clearly wrong to me that I wrote it off as the usual academic prose fluff, and didn’t realize it was in fact the argument being made. Here is the issue I take with that:
You can find instances where industry is clamoring to use AI to reduce costs / improve productivity. For example, Uber and self-driving cars. However in these cases there are a combination of two factors at work: (1) the examples are necessarily specialized narrow AI, not general decision making; and/or (2) the costs of poor decision making are externalized. Let’s look at these points in more detail:
Anytime a human is being used as a meat robot, e.g. an Uber driver, a machine can do the job better and more efficiently with quantifiable tradeoffs due to the machine’s own quirks. However one must not forget that this is the case because the context has already been specialized! One can replace a minimum wage burger flipper with a machine because the job is part of a three-ring binder enterprise that has already been exhaustively thought out to such a degree that every component task can be taught to a minimum wage, distracted teenage worker. If the mechanical burger flipper fails, you go back to paying a $10/hr meat robot to do the trick. But what happens when the corporate strategy robot fails and the new product is a flop? You lose hundreds of millions of invested dollars. And worse, you don’t know until it is all over and played out. Not comparable at all.
Uber might want a fleet of self-driving cars. But that’s because the costs of being wrong are externalized. Get in an accident? It’s your driver’s problem, not Uber. Self-driving car get in an accident? It’s the owner of the car’s problem which, surprise, is not Uber. The applications of AGI have risks that are not so easily externalized, however.
I can see how one might think that unchecked AGI would improve the efficiency of corporate management, fraud detection, and warfare. However that’s confirmation bias. I assure you that the corporate strategists, fraud specialists, and generals get paid the big bucks to think about risk and the ways in which things can go wrong. I can give examples of what could go wrong when an alien AGI psychology tries to interact with irrational humans, but it’s much simpler to remember that even presumably superhuman AGIs have error rates, and these error rates will be higher than humans for a good duration of time while the technology is still developing. And what happens when an AGI makes a mistake?
A corporate strategist AGI makes a mistake, and the directors of the corporation who have a fiduciary responsibility to shareholders are held personally accountable. Indemnity insurance refuses to pay out as upper management purposefully took themselves out of the loop, an action that is considered irresponsible in hindsight.
A fraud specialist AGI makes a mistake, and its company turns a blind eye to hundreds of millions of dollars of fraud that a human would have seen. Business goes belly-up.
An war-making AGI makes a mistake, and you are now dead.
I hope that you’ll forgive me, but I must call on anecdotal evidence here. I am the co-founder of a startup that has raised >$75MM. I understand very well how investors, upper management, and corporate strategists manage risk. I also have observed how extremely terrified of additional risk they are. The supposition that they would be willing to put a high-risk proto-AGI in the driver’s seat is naïve to say the least. These are the people that are held accountable and suffer the largest losses when things go wrong, and they are terrified of that outcome.
What is likely to happen, on the other hand, is a hybridization of machine and human. AGI cognitive assistance will permeate these industries, but their job is to give recommendations, not steer things directly. And it’s not at all so clear to me that this approach, “Oracle AI” as it is called on LW, is so dangerous.
Thank you for the patient explanation! This is an interesting argument that I’ll have to think about some more, but I’ve already adjusted my view of how I expect things to go based on it.
Two questions:
First, isn’t algorithmic trading a counterexample to your argument? It’s true that it’s a narrow domain, but it’s also one where AI systems are trusted with enormous sums of money, and have the potential to make enormous losses. E.g. one company apparently lost $440 million in less than an hour due to a glitch in their software. Wikipedia on the consequences:
Knight Capital took a pre-tax loss of $440 million. This caused Knight Capital’s stock price to collapse, sending shares lower by over 70% from before the announcement. The nature of the Knight Capital’s unusual trading activity was described as a “technology breakdown”.[14][15]
On Sunday, August 5 the company managed to raise around $400 million from half a dozen investors led by Jefferies in an attempt to stay in business after the trading error. Jefferies’ CEO, Richard Handler and Executive Committee Chair Brian Friedman structured and led the rescue and Jefferies purchased $125 million of the $400 million investment and became Knight’s largest shareholder. [2]. The financing would be in the form of convertible securities, bonds that turn into equity in the company at a fixed price in the future.[16]
The incident was embarrassing for Knight CEO Thomas Joyce, who was an outspoken critic of Nasdaq’s handling of Facebook’s IPO.[17] On the same day the company’s stock plunged 33 percent, to $3.39; by the next day 75 percent of Knight’s equity value had been erased.[18]
Also, you give several examples of AGIs potentially making large mistakes with large consequences, but couldn’t e.g. a human strategist make a similarly big mistake as well?
You suggest that the corporate leadership could be held more responsible for a mistake by an AGI than if a human employer made the mistake, and I agree that this is definitely plausible. But I’m not sure whether it’s inevitable. If the AGI was initially treated the way a junior human employee would, i.e. initially kept subject to more supervision and given more limited responsibilities, and then had its responsibilities scaled up as people came to trust it more and it learned from its mistakes, would that necessarily be considered irresponsible by the shareholders and insurers? (There’s also the issue of privately held companies with no need to keep external shareholders satisfied.)
one where AI systems are trusted with enormous sums of money
Kinda. They are carefully watched and have separate risk management systems which impose constraints and limits on what they can do.
E.g. one company apparently lost $440 million in less than an hour due to a glitch in their software.
Yes, but that has nothing to do with AI: “To err is human, but to really screw up you need a computer”. Besides, there are equivalent human errors (fat fingers, add a few zeros to a trade inadvertently) with equivalent magnitude of losses.
have separate risk management systems which impose constraints and limits on what they can do.
If those risk management systems are themselves software, that doesn’t really change the overall picture.
Yes, but that has nothing to do with AI:
If we’re talking about “would companies place AI systems in a role where those systems could cost the company lots of money if they malfunctioned”, then examples of AI systems having been placed in roles where they cost the company a lot of money have everything to do with the discussion.
In the usual way. Contemporary trading systems are not black boxes full of elven magic. They are models, that is, a bunch of code and some data. If the model doesn’t do what you want it to do, you stick your hands in there and twiddle the doohickeys until it stops outputting twaddle.
Besides, in most trading systems the sophisticated part (“AI”) is an oracle. Typically it outputs predictions (e.g. of prices of financial assets) and its utility function is some loss function on the difference between the prediction and the actual. It has no concept of trades, or dollars, or position limits.
Translating these predictions into trades is usually quite straightforward.
I suspect that this dates back to a time when MIRI believed the answer to AI safety was to both build an agentive, maximal supeintelligence and align its values with ours, and put it in charge of all the other AIs.
The first idea has been effectively shelved, since MIRI had produced about zero lines of code,..but the idea that AI safety is value alignment continues with considerable momentum. And value alignment only makes sense if you are building an agentive AI (and have given up on corrigibility).
Which unfortunately presumes that an AGI would be tasked with doing something and given free reign to do so, a truly naïve and unlikely outcome.
How does it presume that?
Aka friendliness research. But why does that matter? If the machine has no real effectors and lots of human oversight, then why should there even be concern over friendliness? It wouldn’t matter in that context. Tell a machine to do something, and it finds an evil-stupid way of doing it, and human intervention prevents any harm.
Why is it a going concern at all whether we can assure ahead of time that the actions recommended by a machine are human-friendly unless the machine is enabled to independently take those actions without human intervention? Just don’t do that and it stops being a concern.
Humanity is having trouble coordinating and enforcing even global restrictions in greenhouse gasses. Try ensuring that nobody does anything risky or short-sighted with a technology that has no clearly-cut threshold between a “safe” and “dangerous” level of capability, and which can be beneficial for performing in pretty much any competitive and financially lucrative domain.
Restricting the AI’s capabilities may work for a short while, assuming that only a small group of pioneers manages to develop the initial AIs and they’re responsible with their use of the technology—but as Bruce Schneier says, today’s top-secret programs become tomorrow’s PhD theses and the next day’s common applications. If we want to survive in the long term, we need to figure out how to make the free-acting AIs safe, too—otherwise it’s just a ticking time bomb before the first guys accidentally or intentionally release theirs.
Humanity has done more than zero and less that optimality about things like climate change. Importantly, the situation isbelow the immanent existential threat level.
If you are going to complain that alternative proposals face coordination problems, you need to show that yours dont, or you are committing the fallacy of the dangling comparision. If people aren’t going to refrain from building dangerously powerful superintellugences, assuming is possible, why would they have the sense to fit MIRIs safety features, assuming they are possible? If the law can make people fit safety features, why cant it prevent them building dangerous AIs ITFP?
I would suggest a combination of generality and agency. And what problem domain requires both?
If you allow for autonomously acting AIs, then you could have Friendly autonomous AIs tracking down and stopping Unfriendly / unauthorized AIs.
This of course depends on people developing the Friendly AIs first, but ideally it’d be enough for only the first people to get the design right, rather than depending on everyone being responsible.
It’s unclear whether AI risk will become obviously imminent, either. Goertzel & Pitt 2012 argue in section 3 of their paper that this is unlikely.
Business (which by nature covers just about every domain in which you can make a profit, which is to say just about every domain relevant for human lives), warfare, military intelligence, governance… (see also my response to Mark)
Somehow that reminds me of Sentinels from X-Men: Days of Future Past.
You could, but if you don’t have autonomously acting agents, you don’t need Gort AIs. Building an agentive superintelligence that is powerful enough to take down any othe, as as MIRI conceives it, is a very risky proposition, since you need to get the value system exactly right. So its better not to be in a place where you have to do that,
The first people have to be able as well as willing to get everything right, Safety through restraint is easier and more reliable. -- you can omit a feature more reliably than you can add one.
These organizations have a need for widespread intelligence gathering , and for agentive AI, but that doesn’t mean they need both in the same package. The military don’t need their entire intelligence database in every drone, and don’t want drones that change their mind about who the bad guys are in mid flight. Businesses don’t want HFT applications that decide capitalism is a bad thing.
We want agents to act on our behalf, which means we want agents that are predictable and controllable to the required extent. Early HFT had problems which led to the addition of limits and controls. Control and predictability are close to safety. There is no drive to power that is also a drive away from safety, because uncontrolled power is of no use.
Based on the behaviour of organisations, there seems to be natural division between high-level, unpredictable decision information systems and lower level, faster acting genitive systems. In other words, they voluntarily do some of what would be required for an incremental safety programme.
I agree that it would be better not to have autonomously acting AIs, but not having any autonomously acting AIs would require a way to prevent anyone deploying them, and so far I haven’t seen a proposal for that that’d seem even remotely feasible.
And if we can’t stop them from being deployed, then deploying Friendly AIs first looks like the scenario that’s more likely to work—which still isn’t to say very likely, but at least it seems to have a chance of working even in principle. I don’t see that an even-in-principle way for “just don’t deploying autonomous AIs” to work.
When you say autonomous AIs, do you mean AIs that are autonomous and superinteligent?
Do you think they could he deployed by basement hackers, or only by large organisations?
Do you think an organisation like the military or business has a motivation to deploy them?
Do you agree that there are dangers to an FAI project that goes wrong?
Do you have a plan B to cope with a FAI that goes rogue?
Do you think that having a AI potentially running the world is an attractive idea to a lot of people?
AIs that are initially autonomous and non-superintelligent, then gradually develop towards superintelligence. (With the important caveat that it’s unclear whether an AI needed to be generally superintelligent in order to pose a major risk for society. It’s conceivable that superintelligence in some more narrow domain, like cybersecurity, would be enough—particularly in a sufficiently networked society.)
Hard to say. The way AI has developed so far, it looks like the capability might be restricted to large organizations with lots of hardware resources at first, but time will likely drive down the hardware requirements.
Yes.
Yes.
Such a plan would seem to require lots of additional information about both the specifics of the FAI plan, and also the state of the world at that time, so not really.
Depends on how we’re defining “lots”, but I think that the notion of a benevolent dictator has often been popular in many circles, who’ve also acknowledged its largest problems to be that 1) power tends to corrupt 2) even if you got a benevolent dictator, you also needed a way to ensure that all of their successors were benevolent. Both problems could be overcome with an AI, so on that basis at least I would expect lots of people to find it attractive. I’d also expect it to be considered more attractive in e.g. China, where people seem to be more skeptical towards democracy than they are in the West.
Additionally, if the AI wouldn’t be the equivalent of a benevolent dictator, but rather had a more hands-off role that kept humans in power and only acted to e.g. prevent disease, violent crime, and accidents, then that could be attractive to a lot of people who preferred democracy.
If you believe in the conjunction of claims that people are motivated to create autonomous, not just agentive, AIs, and that pretty well any AI can evolve into dangerous superintelligence, then the situation is dire, because you cannot guarantee to get in first with an AI policeman as a solution to AI threat.
The situation is better, but only slightly better with legal restraint as a solution to AI threat, because you can lower the probability of disaster by banning autonomous AI...but you can only lower it, not eliminate it, because no ban is 100% effective.
And how serious are you about the threat level? Compare with micro biological research. It could be the case that someone will accidentally create an organism that spells doom for the human race, it cannot be ruled out, but no one is panicing now because there is no specific reason to rule it in, no specific pathway to it. It is a remote possibility, not a serious one.
Someone who sincerely believed that rapid self improvement towards autonomous AI could happen at any time, because there are no specific precondition or precursors for it, is someone who effectively believes it could happen now. But someone who genuinely believes an AI apocalypse could happen now is someone who would e revealing their belief in their behaviour by heading for the hills, or smashing every computer they see.
Narrow superintelligences may well be less dangerous than general superintelligences, and if you are able to restrict the generality of an AI, that could be a path to incremental safety.
But if the path to some kind of spontaneous superintelligence in an autonomous AI is also a path to spontaneous generality, that is hopeless. -- if the one can happen for no particular reason, so can the other. But is the situation really bad, or are these scenarios remote possibilities, like genetically engineered super plagues?
But by the time the hardware requirements have been driven down for entry level AI, the large organizations will already have more powerful systems, and they will dominate for better or worse. If benevolent, they will supress dangerous AIs coming out of basements, if dangerous they will suppress rivals. The only problematic scenario is where the hackers get in first, since they are less likely to partition agency from intelligence, as I have argued a large organisation would.
But the one thing we know for sure about AI is that it is hard.The scenario where a small team hits on the One Weird Trick to achieve ASI is the most worrying, but also the least likely.
Which would be what?
But building an FAI capable of policing other AIs is potentially dangerous, since it would need to be both a general intelligence and super intelligence.
For the purposes of the current argument, a democratic majority.
There are actually three problems with benevolent dictators. As well. as power corrupting, and successorship, there is the problem of ensuring or detecting benevolence in the first place.
You have conceded that Gort AI is potentially dangerous. The danger is that it is fragile in a specific way: a near miss to a benevolent value system is a dangerous one,
That also depends on both getting it right, and convincing people you have got it right
Indeed.
I don’t think that rapid self-improvement towards a powerful AI could happen at any time. It’ll require AGI, and we’re still a long way from that.
It could, yes.
Assuming they can keep their AGI systems in control.
See my response here and also section 2 in this post.
Very much so.
I think you very much misunderstand my suggestion. I’m saying that there is no reason to presume AI will be given the keys to the kingdom from day one, not advocating for some sort of regulatory regime.
So what do you see as the mechanism that will prevent anyone from handing the AI those keys, given the tremendous economic pressure towards doing exactly that?
As we discussed in Responses to AGI Risk:
What “tremendous economic pressure”? The argument doesn’t hold weight absent that unsubstantiated justification.
I thought my excerpt answered that, but maybe that was illusion of transparency speaking. In particular, this paragraph:
To rephrase: the main trend is history has been to automate everything that can be automated, both to reduce costs and because machines can do things better than humans do. This isn’t going to stop: I’ve already seen articles calling for both company middle managers, as well as government bureaucrats, to be replaced with AIs. If you have any kind of a business, you could potentially make it run better by putting a sufficiently sophisticated AI in charge—because it can think faster and smarter, deal with more information at once, and not have the issue of self-interest leading to office politics leading to many employees acting suboptimally from the company’s point of view, that you’d get if you had a thousand human employees rather than a single AI.
This trend has been going on throughout history, doesn’t show any signs of stopping, and inherently involves giving the AI systems whatever agency they need in order to run the company better.
And if your competitors are having AIs run their company and you don’t, you’re likely to be outcompeted, so you’ll want to make sure your AIs are smarter and more capable of acting autonomously than the competitors. These pressures aren’t just going to vanish at the point when AIs start approaching human capability.
The same considerations also apply to other domains than business—like governance—but the business and military domains are the most likely to have intense arms race dynamics going on.
Yes, illusion of transparency at work here. That paragraph has always been so clearly wrong to me that I wrote it off as the usual academic prose fluff, and didn’t realize it was in fact the argument being made. Here is the issue I take with that:
You can find instances where industry is clamoring to use AI to reduce costs / improve productivity. For example, Uber and self-driving cars. However in these cases there are a combination of two factors at work: (1) the examples are necessarily specialized narrow AI, not general decision making; and/or (2) the costs of poor decision making are externalized. Let’s look at these points in more detail:
Anytime a human is being used as a meat robot, e.g. an Uber driver, a machine can do the job better and more efficiently with quantifiable tradeoffs due to the machine’s own quirks. However one must not forget that this is the case because the context has already been specialized! One can replace a minimum wage burger flipper with a machine because the job is part of a three-ring binder enterprise that has already been exhaustively thought out to such a degree that every component task can be taught to a minimum wage, distracted teenage worker. If the mechanical burger flipper fails, you go back to paying a $10/hr meat robot to do the trick. But what happens when the corporate strategy robot fails and the new product is a flop? You lose hundreds of millions of invested dollars. And worse, you don’t know until it is all over and played out. Not comparable at all.
Uber might want a fleet of self-driving cars. But that’s because the costs of being wrong are externalized. Get in an accident? It’s your driver’s problem, not Uber. Self-driving car get in an accident? It’s the owner of the car’s problem which, surprise, is not Uber. The applications of AGI have risks that are not so easily externalized, however.
I can see how one might think that unchecked AGI would improve the efficiency of corporate management, fraud detection, and warfare. However that’s confirmation bias. I assure you that the corporate strategists, fraud specialists, and generals get paid the big bucks to think about risk and the ways in which things can go wrong. I can give examples of what could go wrong when an alien AGI psychology tries to interact with irrational humans, but it’s much simpler to remember that even presumably superhuman AGIs have error rates, and these error rates will be higher than humans for a good duration of time while the technology is still developing. And what happens when an AGI makes a mistake?
A corporate strategist AGI makes a mistake, and the directors of the corporation who have a fiduciary responsibility to shareholders are held personally accountable. Indemnity insurance refuses to pay out as upper management purposefully took themselves out of the loop, an action that is considered irresponsible in hindsight.
A fraud specialist AGI makes a mistake, and its company turns a blind eye to hundreds of millions of dollars of fraud that a human would have seen. Business goes belly-up.
An war-making AGI makes a mistake, and you are now dead.
I hope that you’ll forgive me, but I must call on anecdotal evidence here. I am the co-founder of a startup that has raised >$75MM. I understand very well how investors, upper management, and corporate strategists manage risk. I also have observed how extremely terrified of additional risk they are. The supposition that they would be willing to put a high-risk proto-AGI in the driver’s seat is naïve to say the least. These are the people that are held accountable and suffer the largest losses when things go wrong, and they are terrified of that outcome.
What is likely to happen, on the other hand, is a hybridization of machine and human. AGI cognitive assistance will permeate these industries, but their job is to give recommendations, not steer things directly. And it’s not at all so clear to me that this approach, “Oracle AI” as it is called on LW, is so dangerous.
Thank you for the patient explanation! This is an interesting argument that I’ll have to think about some more, but I’ve already adjusted my view of how I expect things to go based on it.
Two questions:
First, isn’t algorithmic trading a counterexample to your argument? It’s true that it’s a narrow domain, but it’s also one where AI systems are trusted with enormous sums of money, and have the potential to make enormous losses. E.g. one company apparently lost $440 million in less than an hour due to a glitch in their software. Wikipedia on the consequences:
Also, you give several examples of AGIs potentially making large mistakes with large consequences, but couldn’t e.g. a human strategist make a similarly big mistake as well?
You suggest that the corporate leadership could be held more responsible for a mistake by an AGI than if a human employer made the mistake, and I agree that this is definitely plausible. But I’m not sure whether it’s inevitable. If the AGI was initially treated the way a junior human employee would, i.e. initially kept subject to more supervision and given more limited responsibilities, and then had its responsibilities scaled up as people came to trust it more and it learned from its mistakes, would that necessarily be considered irresponsible by the shareholders and insurers? (There’s also the issue of privately held companies with no need to keep external shareholders satisfied.)
Kinda. They are carefully watched and have separate risk management systems which impose constraints and limits on what they can do.
Yes, but that has nothing to do with AI: “To err is human, but to really screw up you need a computer”. Besides, there are equivalent human errors (fat fingers, add a few zeros to a trade inadvertently) with equivalent magnitude of losses.
If those risk management systems are themselves software, that doesn’t really change the overall picture.
If we’re talking about “would companies place AI systems in a role where those systems could cost the company lots of money if they malfunctioned”, then examples of AI systems having been placed in roles where they cost the company a lot of money have everything to do with the discussion.
It does because the issue is complexity and opaqueness. A simple gatekeeper filter along the lines of
is not an “AI system”.
In which case the AI splits the transaction into 2 transactions, each just below a gazillion.
I’m talking about contemporary-level-of-technology trading systems, not about future malicious AIs.
So? An opaque neural net would quickly learn how to get around trade size restrictions if given the proper motivations.
At which point the humans running this NN will notice that it likes to go around risk control measures and will… persuade it that it’s a bad idea.
It’s not like no one is looking at the trades it’s doing.
How? By instituting more complex control measures? Then you’re back to the problem Kaj mentioned above.
In the usual way. Contemporary trading systems are not black boxes full of elven magic. They are models, that is, a bunch of code and some data. If the model doesn’t do what you want it to do, you stick your hands in there and twiddle the doohickeys until it stops outputting twaddle.
Besides, in most trading systems the sophisticated part (“AI”) is an oracle. Typically it outputs predictions (e.g. of prices of financial assets) and its utility function is some loss function on the difference between the prediction and the actual. It has no concept of trades, or dollars, or position limits.
Translating these predictions into trades is usually quite straightforward.
I suspect that this dates back to a time when MIRI believed the answer to AI safety was to both build an agentive, maximal supeintelligence and align its values with ours, and put it in charge of all the other AIs.
The first idea has been effectively shelved, since MIRI had produced about zero lines of code,..but the idea that AI safety is value alignment continues with considerable momentum. And value alignment only makes sense if you are building an agentive AI (and have given up on corrigibility).