Mm.
This is true only if the AI’s social interactions are all with some human. If, instead, the AI spawns copies of itself to interact with (perhaps simply because it wants interaction, and it can get more interaction that way than waiting for a human to get off its butt) it might derive a number of social mechanisms in isolation without human observation.
I see no reason for it to do that before simple input-output experiments, but let’s suppose I grant you this approach. The AI simulates an entire community of mini-AI and is now a master of game theory.
It still doesn’t know the first thing about humans. Even if it now understands the concept that hiding information gives an advantage for achieving goals—this is too abstract. It wouldn’t know what sort of information it should hide from us. It wouldn’t know to what degree we analyze interactions rationally, and to what degree our behavior is random. It wouldn’t know what we can or can’t monitor it doing. All these things would require live experimentation.
It would stumble. And when it does that, we will crack it open, run the stack trace, find the game theory it was trying to run on us, pale collectively, and figure out that this AI approach creates manipulative, deceptive AIs.
Goodbye to that design, but not to Earth, I think!
It is not clear to me that talking to a human is simpler than interacting with a copy of itself. I agree that if talking to a human is simpler, it would probably do that first.
I agree that what it would learn by this process is general game theory, and not specific facts about humans. It is not clear to me that sufficient game-theoretical knowledge, coupled with the minimal set of information about humans required to have a conversation with one at all, is insufficient to effectively deceive a human.
It is not clear to me that, even if it does “stumble,” humans will respond as you describe.
It is not clear to me that a system capable of having a meaningful conversation with a human will necessarily have a stack trace that is subject to the kind of analysis you imply here. It is not even clear to me that the capacity for such a stack trace is likely, depending on what architectures turn out to work best for implementing AI.
But, sure, I could be wrong about all of that. And if I’m wrong, and you’re right, then a system like you describe will be reliably incapable of fooling a human observer.
If I was using an AI that was designed to answer some class of questions (with independently-verifiable answers) truthfully, and I noticed it responding to questions of that class with demonstrable falsehoods, I would at the very least file a strongly-worded bug report, triple-check whatever work I’d previously done involving answers it provided, and cease using it in the future. I don’t think such a response would be exceptional in it’s decisiveness; other users would likely go further, seek out venues to complain openly. Consider the uproar over Gmail’s ‘new look.’
You may be right that ceasing to use the tool in that situation would be standard behavior. It seems unlikely to me, but I have no compelling data to offer to change your estimate.
I think the weakest link here is human response to the AI revealing it can be deceptive. There is absolutely no guarantee that people would act correctly under these circumstances. Human negligence for a long enough time would eventually give the AI a consistent ability to manipulate humans.
I also agree that simulating relationships makes sense as it can happen in “AI time” without having to wait for human response.
The other reservations seem less of an issue to me...
That game theory knowledge coupled with the most basic knowledge about humans is insufficient to cleverly manipulate them is clear to me. I don’t see how these things can be combined in this way, or why the AI would choose to be particularly careful (it doesn’t know what it should be careful about). I’d love to see a plausible line of thought by which the AI would try and succeed in deceiving humans at the get-go point without exposing its intentions.
A stack trace reader or an equivalent monitoring system is something you implement externally without telling the AI about it. Sure, if it’s powerful enough it will mislead or disable it; but while it has no knowledge of it, and no knowledge on what sort of operations it should mask, it has no means of doing so.
(If it encrypts everything it does, somehow fearing any monitoring, that is in itself cause for concern).
To put this into an analogy: You can feed a surveillance camera a repeating loop, but not if you don’t know that the camera exists. If you suspect it exists, you still don’t know where; so you don’t know which approach to take so as to remain undetected.
Yes, I agree that there’s no guarantee that humans would behave as you describe. Indeed, I don’t find it likely. But, sure, they might.
===
I agree that a stack trace can exist outside the AI’s zone of control. What I was expressing skepticism about was that a system with even approximately human-level intelligence necessarily supports a stack trace that supports the kind of analysis you envision performing in the first place, without reference to intentional countermeasures.
By way of analogy: I can perform a structural integrity analysis on a bar of metal to determine whether it can support a given weight, but performing an equivalent analysis on a complicated structure comprising millions of bars of metal connected in a variety of arrangements via a variety of connectors using the same techniques is not necessarily possible.
But, sure, it might be.
======
I’d love to see a plausible line of thought by which the AI would try and succeed in deceiving humans at the get-go point without exposing its intentions.
Well, one place to start is with an understanding of the difference between “the minimal set of information about humans required to have a conversation with one at all” (my phrase) and “the most basic knowledge about humans” (your phrase). What do you imagine the latter to encompass, and how do you imagine the AI obtained this knowledge?
What I was expressing skepticism about was that a system with even approximately human-level intelligence necessarily supports a stack trace that supports the kind of analysis you envision performing in the first place, without reference to intentional countermeasures.
Ah, that does clarify it. I agree, analyzing the AI’s thought process would likely be difficult, maybe impossible! I guess I was being a bit hyperbolic in my earlier “crack it open” remarks (though depending on how seriously you take it, such analysis might still take place, hard and prolonged though it may be).
One can have “detectors” in place set to find specific behaviors, but these would have assumptions that could easily fail.
Detectors that would still be useful would be macro ones—where it tries to access and how—but these would provide only limited insight into the AI’s thought process.
[...]the difference between “the minimal set of information about humans required to have a conversation with one at all” (my phrase) and “the most basic knowledge about humans” (your phrase). What do you imagine the latter to encompass, and how do you imagine the AI obtained this knowledge?
I actually perceive your phrase to be a subset of my own; I am making the (reasonable, I think) assumption that humans will attempt to communicate with the budding AI. Say, in a lab environment. It would acquire its initial data from this interaction.
I think both these sets of knowledge depend a lot on how the AI is built. For instance, a “babbling” AI—one that is given an innate capability of stringing words together onto a screen, and the drive to do so—would initially say a lot of gibberish and would (presumably) get more coherent as it gets a better grip on its environment. In such a scenario, the minimal set of information about humans required to have a conversation is zero; it would be having conversations before it even knows what it is saying.
(This could actually make detection of deception harder down the line, because such attempts can be written off as “quirks” or AI mistakes)
Now, I’ll take your phrase and twist it just a bit: The minimal set of knowledge the AI needs in order to try deceiving humans. That would be the knowledge that humans can be modeled as having beliefs (which drive behavior) and these can be altered by the AI’s actions, at least to some degree. Now, assuming this information isn’t hard-coded, it doesn’t seem likely that is all an AI would know about us; it should be able to see some patterns at least to our communications with it. However, I don’t see how such information would be useful for deception purposes before extensive experimentation.
(Is the fact that the operator communicates with me between 9am and 5pm an intrinsic property of the operator? For all I know, that is a law of nature...)
depending on how seriously you take it, such analysis might still take place, hard and prolonged though it may be).
Yup, agreed that it might. And agreed that it might succeed, if it does take place.
One can have “detectors” in place set to find specific behaviors, but these would have assumptions that could easily fail. Detectors that would still be useful would be macro ones—where it tries to access and how—but these would provide only limited insight into the AI’s thought process.
Agreed on all counts.
Re: what the AI knows… I’m not sure how to move forward here. Perhaps what’s necessary is a step backwards.
If I’ve understood you correctly, you consider “having a conversation” to encompass exchanges such as: A: “What day is it?” B: “Na ni noo na”
If that’s true, then sure, I agree that the minimal set of information about humans required to do that is zero; hell, I can do that with the rain. And I agree that a system that’s capable of doing that (e.g., the rain) is sufficiently unlikely to be capable of effective deception that the hypothesis isn’t even worthy of consideration. I also suggest that we stop using the phrase “having a conversation” at all, because it does not convey anything meaningful.
Having said that… for my own part, I initially understood you to be talking about a system capable of exchanges like:
A: “What day is it?” B: “Day seventeen.” A: “Why do you say that?” B: “Because I’ve learned that ‘a day’ refers to a particular cycle of activity in the lab, and I have observed seventeen such cycles.”
A system capable of doing that, I maintain, already knows enough about humans that I expect it to be capable of deception. (The specific questions and answers don’t matter to my point, I can choose others if you prefer.)
My point was that the AI is likely to start performing social experiments well before it is capable of even that conversation you depicted. It wouldn’t know how much it doesn’t know about humans.
And I agree that humans might be able to detect attempts at deception in a system at that stage of its development. I’m not vastly confident of it, though.
I have likewise adjusted down my confidence that this would be as easy or as inevitable as I previously anticipated. Thus I would no longer say I am “vastly confident” in it, either.
Still good to have this buffer between making an AI and total global catastrophe, though!
Mm. This is true only if the AI’s social interactions are all with some human.
If, instead, the AI spawns copies of itself to interact with (perhaps simply because it wants interaction, and it can get more interaction that way than waiting for a human to get off its butt) it might derive a number of social mechanisms in isolation without human observation.
I see no reason for it to do that before simple input-output experiments, but let’s suppose I grant you this approach. The AI simulates an entire community of mini-AI and is now a master of game theory.
It still doesn’t know the first thing about humans. Even if it now understands the concept that hiding information gives an advantage for achieving goals—this is too abstract. It wouldn’t know what sort of information it should hide from us. It wouldn’t know to what degree we analyze interactions rationally, and to what degree our behavior is random. It wouldn’t know what we can or can’t monitor it doing. All these things would require live experimentation.
It would stumble. And when it does that, we will crack it open, run the stack trace, find the game theory it was trying to run on us, pale collectively, and figure out that this AI approach creates manipulative, deceptive AIs.
Goodbye to that design, but not to Earth, I think!
It is not clear to me that talking to a human is simpler than interacting with a copy of itself.
I agree that if talking to a human is simpler, it would probably do that first.
I agree that what it would learn by this process is general game theory, and not specific facts about humans.
It is not clear to me that sufficient game-theoretical knowledge, coupled with the minimal set of information about humans required to have a conversation with one at all, is insufficient to effectively deceive a human.
It is not clear to me that, even if it does “stumble,” humans will respond as you describe.
It is not clear to me that a system capable of having a meaningful conversation with a human will necessarily have a stack trace that is subject to the kind of analysis you imply here. It is not even clear to me that the capacity for such a stack trace is likely, depending on what architectures turn out to work best for implementing AI.
But, sure, I could be wrong about all of that. And if I’m wrong, and you’re right, then a system like you describe will be reliably incapable of fooling a human observer.
If I was using an AI that was designed to answer some class of questions (with independently-verifiable answers) truthfully, and I noticed it responding to questions of that class with demonstrable falsehoods, I would at the very least file a strongly-worded bug report, triple-check whatever work I’d previously done involving answers it provided, and cease using it in the future. I don’t think such a response would be exceptional in it’s decisiveness; other users would likely go further, seek out venues to complain openly. Consider the uproar over Gmail’s ‘new look.’
You may be right that ceasing to use the tool in that situation would be standard behavior. It seems unlikely to me, but I have no compelling data to offer to change your estimate.
I think the weakest link here is human response to the AI revealing it can be deceptive. There is absolutely no guarantee that people would act correctly under these circumstances. Human negligence for a long enough time would eventually give the AI a consistent ability to manipulate humans.
I also agree that simulating relationships makes sense as it can happen in “AI time” without having to wait for human response.
The other reservations seem less of an issue to me...
That game theory knowledge coupled with the most basic knowledge about humans is insufficient to cleverly manipulate them is clear to me. I don’t see how these things can be combined in this way, or why the AI would choose to be particularly careful (it doesn’t know what it should be careful about). I’d love to see a plausible line of thought by which the AI would try and succeed in deceiving humans at the get-go point without exposing its intentions.
A stack trace reader or an equivalent monitoring system is something you implement externally without telling the AI about it. Sure, if it’s powerful enough it will mislead or disable it; but while it has no knowledge of it, and no knowledge on what sort of operations it should mask, it has no means of doing so. (If it encrypts everything it does, somehow fearing any monitoring, that is in itself cause for concern).
To put this into an analogy: You can feed a surveillance camera a repeating loop, but not if you don’t know that the camera exists. If you suspect it exists, you still don’t know where; so you don’t know which approach to take so as to remain undetected.
Yes, I agree that there’s no guarantee that humans would behave as you describe.
Indeed, I don’t find it likely.
But, sure, they might.
=== I agree that a stack trace can exist outside the AI’s zone of control. What I was expressing skepticism about was that a system with even approximately human-level intelligence necessarily supports a stack trace that supports the kind of analysis you envision performing in the first place, without reference to intentional countermeasures.
By way of analogy: I can perform a structural integrity analysis on a bar of metal to determine whether it can support a given weight, but performing an equivalent analysis on a complicated structure comprising millions of bars of metal connected in a variety of arrangements via a variety of connectors using the same techniques is not necessarily possible.
But, sure, it might be.
======
Well, one place to start is with an understanding of the difference between “the minimal set of information about humans required to have a conversation with one at all” (my phrase) and “the most basic knowledge about humans” (your phrase). What do you imagine the latter to encompass, and how do you imagine the AI obtained this knowledge?
Ah, that does clarify it. I agree, analyzing the AI’s thought process would likely be difficult, maybe impossible! I guess I was being a bit hyperbolic in my earlier “crack it open” remarks (though depending on how seriously you take it, such analysis might still take place, hard and prolonged though it may be).
One can have “detectors” in place set to find specific behaviors, but these would have assumptions that could easily fail. Detectors that would still be useful would be macro ones—where it tries to access and how—but these would provide only limited insight into the AI’s thought process.
I actually perceive your phrase to be a subset of my own; I am making the (reasonable, I think) assumption that humans will attempt to communicate with the budding AI. Say, in a lab environment. It would acquire its initial data from this interaction.
I think both these sets of knowledge depend a lot on how the AI is built. For instance, a “babbling” AI—one that is given an innate capability of stringing words together onto a screen, and the drive to do so—would initially say a lot of gibberish and would (presumably) get more coherent as it gets a better grip on its environment. In such a scenario, the minimal set of information about humans required to have a conversation is zero; it would be having conversations before it even knows what it is saying. (This could actually make detection of deception harder down the line, because such attempts can be written off as “quirks” or AI mistakes)
Now, I’ll take your phrase and twist it just a bit: The minimal set of knowledge the AI needs in order to try deceiving humans. That would be the knowledge that humans can be modeled as having beliefs (which drive behavior) and these can be altered by the AI’s actions, at least to some degree. Now, assuming this information isn’t hard-coded, it doesn’t seem likely that is all an AI would know about us; it should be able to see some patterns at least to our communications with it. However, I don’t see how such information would be useful for deception purposes before extensive experimentation.
(Is the fact that the operator communicates with me between 9am and 5pm an intrinsic property of the operator? For all I know, that is a law of nature...)
Yup, agreed that it might.
And agreed that it might succeed, if it does take place.
Agreed on all counts.
Re: what the AI knows… I’m not sure how to move forward here. Perhaps what’s necessary is a step backwards.
If I’ve understood you correctly, you consider “having a conversation” to encompass exchanges such as:
A: “What day is it?”
B: “Na ni noo na”
If that’s true, then sure, I agree that the minimal set of information about humans required to do that is zero; hell, I can do that with the rain.
And I agree that a system that’s capable of doing that (e.g., the rain) is sufficiently unlikely to be capable of effective deception that the hypothesis isn’t even worthy of consideration.
I also suggest that we stop using the phrase “having a conversation” at all, because it does not convey anything meaningful.
Having said that… for my own part, I initially understood you to be talking about a system capable of exchanges like: A: “What day is it?”
B: “Day seventeen.”
A: “Why do you say that?”
B: “Because I’ve learned that ‘a day’ refers to a particular cycle of activity in the lab, and I have observed seventeen such cycles.”
A system capable of doing that, I maintain, already knows enough about humans that I expect it to be capable of deception. (The specific questions and answers don’t matter to my point, I can choose others if you prefer.)
My point was that the AI is likely to start performing social experiments well before it is capable of even that conversation you depicted. It wouldn’t know how much it doesn’t know about humans.
(nods) Likely.
And I agree that humans might be able to detect attempts at deception in a system at that stage of its development. I’m not vastly confident of it, though.
I have likewise adjusted down my confidence that this would be as easy or as inevitable as I previously anticipated. Thus I would no longer say I am “vastly confident” in it, either.
Still good to have this buffer between making an AI and total global catastrophe, though!
Sure… a process with an N% chance of global catastrophic failure is definitely better than a process with N+delta% chance.