The following is a conversation between myself in 2022, and a newer version of myself earlier this year.
 

On AI Governance and Public Policy

2022 Me: I think we will have to tread extremely lightly with, or, if possible, avoid completely. One particular concern is the idea of gaining public support. Many countries have an interest in pleasing their constituents, so if executed well, this could be extremely beneficial. However, it runs high risk of doing far more damage. One major concern is the different mindset needed to conceptualize the problem. Alerting people to the dangers of Nuclear War is easier: nukes have been detonated, the visual image of incineration is easy to imagine and can be described in detail, and they or their parents have likely lived through nuclear drills in school. This is closer to trying to explain someone the dangers of nuclear war before Hiroshima, before the Manhattan Project, and before even tnt was developed. They have to conceptualize what an explosion even is, not simply imagining an explosion at greater scale. Most people will simply not have the time or the will to try to grasp this problem, so this runs the risk of having people calling for action to a problem they do not understand, which will likely lead to dismissal by AI Researchers, and possibly short-sighted policies that don’t actually tackle the problem, or even make the problem worse by having the guise of accomplishment. To make matters worse, there is the risk of polarization. Almost any concern with political implications that has gained widespread public attention runs a high risk of becoming polarized. We are still dealing with the ramifications of well-intentioned, but misguided, early advocates in the Climate Change movement two decades ago, who set the seeds for making climate policy part of one’s political identity. This could be even more detrimental than a merely uninformed electorate, as it might push people who had no previous opinion on AI to advocate strongly in favor of capabilities acceleration, and to be staunchly against any form of safety policy. Even if executed using the utmost caution, this does not stop other players from using their own power or influence to hijack the movement and lead it astray.

2023 Me: Ah, Me’22,, the things you don’t know! Many of the concerns of Me’22 I think are still valid, but we’re experiencing what chess players might call a “forced move”. People are starting to become alarmed, regardless of what we say or do, so steering that in a direction we want is necessary. The fire alarm is being pushed, regardless, and if we don’t try to show some leadership in that regard, we risk less informed voices and blanket solutions winning-out. The good news is “serious” people are going on “serious” platforms and actually talking about x-risk. Other good news is that, from current polls, people are very receptive to concerns over x-risk and it has not currently fallen into divisive lines (roughly the same % of those concerned fall equally among various different demographics). This is still a difficult minefield to navigate. Polarization could still happen, especially with an Election Year in the US looming. I’ve also been talking to a lot of young people who feel frustrated not having anything actionable to do, and if those in AI Safety don’t show leadership, we might risk (and indeed are already risking), many frustrated youth taking political and social action into their own hands. We need to be aware that EA/LW might have an Ivory Tower problem, and that, even though a pragmatic, strategic, and careful course of action might be better, this might make many feel “shut out” and attempt to steer their own course. Finding a way to make those outside EA/LW/AIS feel included, with steps to help guide and inform them, might be critical to avoiding movement hijacking.

On Capabilities vs. Alignment Research:

2022 Me: While I strongly agree that not increasing capabilities is a high priority right now, I also question if we risk creating a state of inertia. In terms of the realms of safety research, there are very few domains that do not risk increasing capabilities research. And, while capabilities continues to progress every day, we might risk failing to keep up the speed of safety progress simply because every action risks an increase in capabilities. Rather than a “do no harm” principle, I think counterfactuals need to be examined in these situations, where we must consider if there is a greater risk if we *don’t* do research in a certain domain.

2023 Me: Oh, oh, oh! I think Me’22 was actually ahead of the curve on this one. This might still be controversial, but I think many got the “capabilities space” wrong. Many AIS-inspired theories that could increase capabilities are for systems that could be safer, more interpretable, and easier to monitor by default. And by not working on such systems we instead got the much more inscrutable, dangerous models by default, because the more dangerous models are easier. To quote the vape commercials, “safer != safe” but I still quit smoking in favor of electronics because safer is still at least safer. This is probably a moot point now, though, since I think it’s likely too late to create an entirely new paradigm in AI architectures. Hopefully Me’24 will be happy to tell me we found a new, 100% safe and effective new paradigm that everyone’s hopping on. Or maybe he’ll invent it.

The following is a conversation between myself in 2022, and a newer version of me earlier this year.

On the Nature of Intelligence and its "True Name":

2022 Me:  This has become less obvious to me as I’ve tried to gain a better understanding of what general intelligence is. Until recently, I always made the assumption that intelligence and agency were the same thing. But General Intelligence, or G, might not be agentic. Agents that behave like RLs may only be narrow forms of intelligence, without generalizability. G might be something closer to a simulator. From my very naive perception of neuroscience, it could be that we (our intelligence) is not agentic, but just simulates agents. In this situation, the prefrontal cortex not only runs simulations to predict its next sensory input, but might also run simulations to predict inputs from other parts of the brain. In this scenario, “desire” or “goals”, might be simulations to better predict narrowly-intelligent agentic optimizers. Though the simulator might be myopic, I think this prediction model allows for non-myopic behavior, in a similar way GPT has non-myopic behavior, despite only trying to predict the next token (it has an understanding of where a future word “should” be within the context of a sentence, paragraph, or story). I think this model of G allows for the appearance of intelligent goal-seeking behavior, long-term planning, and self-awareness. I have yet to find another model for G that allows for all three. The True Name of G might be Algorithm Optimized To Reduce Predictive Loss.

2023 Me: interesting, me’22, but let me ask you something: you seem to think this majestic ‘G’ is something humans have, but other species do not, and then name the True Name of ‘G’ to be Algorithm Optimized To Reduce Predictive Loss. Do you *really* think other animals don’t do this? How long is a cat going to survive if it can’t predict where it’s going to land? Or where the mouse’s path trajectory is heading? Did you think it was all somehow hardcoded in? But cats can jump up on tables, and those weren’t in the ancestry environment, there’s clearly some kind of generalized form of prediction occurring. Try formulating that answer again, but taboo “intelligence”, “G”, “agent”, “desire”, and “goal”. I think the coherence of it breaks down.

Now, what does me’23 think? Well, I’m going to take a leaf from my own book, and try to explain what I think without the words mentioned above. There are predictive mechanisms in the Universe that can run models of what things in the Universe might do in future states. Some of these predictive mechanism are more computationally efficient than others. Some will be more effective than others. A more effective and efficient predictive mechanism, with a large input of information about the Universe, could be a very powerful tool. If taken to the theoretical (not physical) extreme, that predictive mechanism would hold models of all possible future states. It could then, by accident or intention, guide outcomes toward certain future states over others.

2022 Me: according to this model, humans dream because the simulator is now making predictions without sensory input, gradually creating a bigger and bigger gap from reality. Evidence to support this is from sensory-deprivation tanks, where humans, despite being awake, have dream-like states. I also find it interesting that people who exhibit Schizophrenia, which involves hallucinations (like dreams do), can tickle themselves. Most people can be tickled by others, but not themselves. But normal people on LSD can do this, and also can have hallucinations. My hairbrained theory is that something is going wrong when initializing new tokens for the simulator, which results in hallucinations from the lack of correction from sensory input, and a less strong sense of self because of a lack of correction from RL agents in other parts of the brain.

2023 Me: I don’t want to endorse crackpot theories from Me’22, so I’m just going to speak from feelings and fuzzy intuitions here. I will say hallucinations from chatbots are interesting. When getting one to hallucinate, it seems to be kind of “making up reality as it goes along”. You say it’s a Unicorn, and it will start coming up with explanations for why it’s a Unicorn. You say it told you something you never told it, and it will start acting as though it did. I have to admit it does have a strange resemblance to dreams. I find myself in New York, but remember that I had been in Thailand that morning, and I hallucinate a memory of boarding a plane. I wonder where I got the plane ticket, and I hallucinate another memory of buying one. These are not well-reasoned arguments, though, so I hope Me’24 won’t beat me up too much about them.

2022 Me: I have been searching for how to test this theory. One interest of mine has been mirrors. 

2023 Me: Don’t listen to Me’22 on this one. He thought he understood something, but he didn’t. Yes, the mirror thing is interesting in animals, but it’s probably a whole different thing, not the same thing.

A man asks one of the members of the tribe to find him some kindling so that he may start a fire. A few hours pass, and the second man returns, walking with a large elephant.

“I asked for kindling.” Says the first.

“Yes.” Says the second.

“Where is it?” Asks the first, trying to ignore the large pachyderm in the room.

The second gestures at the elephant, grinning.

“That’s an elephant.”

“I see that you are uninformed. You see, elephants are quite combustible, despite their appearance. Once heat reaches the right temperature, its skin, muscles, all of it will burn. Right down to its bones.”

“What is the ignition temperature for an elephant”

“I don't know, perhaps 300-400°C”

The first held up two stones.

“This is all I have to start a fire.” He says, “It will only create a few sparks at best… I’m not even sure how I can get it to consistently do that much, given how hard this will be for people thousands of years from now to replicate.”

“That is the challenge.” The second nodded solemnly, “I’m glad you understand the scope of this. We will have to search for ways to generate sparks at 400° so that we can solve the Elephant Kindling Problem.”

“I think I know why you chose the elephant. I think you didn’t initially understand that almost everything is combustible, but only notice things are combustible once you pay enough attention to them. You looked around the Savana, and didn't understand that dry leaves would be far more combustible, and your eyes immediately went to the elephant. Because elephants are interesting. They’re big and have trunks. Working on an Elephant Problem just felt way more interesting than a Dry Leaves Problem, so you zeroed all of your attention on elephants, using the excuse that elephants are technically combustible, failing to see the elegant beauty in the efficient combustibility of leaves and their low ignition temperature.”

“Leaves might be combustible. But think of how fast they burn out. And how many you would have to gather to start a fire. An elephant is very big. It might take longer to get it properly lit, but once you do, you will have several tons of kindling! You could start any number of fires with it!”

“Would you have really made these conclusions if you had searched all the possible combustible materials in the Savana, instead of immediately focusing on elephants?”

“Listen, we can’t waste too much time on search. There are thousands of things in the Savana! If we tested the combustibility and ignition temperature of every single one of them, we’d never get around to starting any fires. Are elephants the most combustible things in the Universe? Probably not. But should I waste time testing every possible material instead of focusing on how to get one material to burn? We have finite time, and finite resources to search for combustible materials. It’s better to pick one and figure out how to do it well.”

“I still think you only chose elephants because they’re big and interesting.”

“I imagine that ‘big’ and ‘useful as kindling material’ are not orthogonal. We shouldn’t get distracted by the small, easy problems, such as how to burn leaves. These are low hanging fruit that anyone can pick. But my surveys of the tribe have found that figuring out the combustibility of elephants remains extremely neglected.”

“What about the guy who brought me a giraffe yesterday?”

“A giraffe is not an elephant! I doubt anything useful will ever come from giraffe combustibility. Their necks are so long that they will not even fit inside our caves!”

“What I am saying is that others have brought in big, interesting-looking animals, and tried to figure out how to turn them into kindling. Sure, no one else is working on the Elephant Kindling Problem. But that’s also what the guy with the giraffe said, and the zebra, and the python.”

“Excuse me,” Said a third, poking his head into the cave, “But the Python Kindling Problem is very different from the Elephant one. Elephants are too girthy to be useful. But with a python, you can roll it into a coil, which will make it extremely efficient kindling material.”

The second scratched his chin for a moment, looking a bit troubled.

“What if we combined the two?” He asked. “If we wound the python around a leg of the elephant, the heat could be transferred somewhat efficiently.”

“No, no, no.", argued the third, "I agree combining these two problems might be useful. But it would be far better to just cut the trunk off the elephant, and intertwine it with the python. This could be very useful, since elephant hide is very thick and might burn slower. This gives us the pros of a fast-burning amount of kindling, mixed with a more sustained blaze from the elephant.”

“Might I interject.” Said a fourth voice, who had been watching quietly from the corner, but now stepped forward, “I have been hard at work on the Giraffe Kindling problem, but think that we are actually working on similar things. The main issue has always been the necks. They simply won’t fit inside the cave. We need a solution that works in all edge cases, after all. If it’s raining, we can’t start a fire outside. But if we use the python and the elephant trunk to tie the neck of the giraffe against the rest of its body, we could fit the whole thing in!”

“I think this will be a very fruitful collaboration.” Said the second, “While at first it seemed as though we were all working on different problems, it turns out by combining them, we have found an elegant solution.”

“But we still can’t generate sparks hot enough to combust any of them!” Shouted the first, “All you’ve done is made this even more complicated and messy!”

“I am aware it might seem that way to a novice.” Said the second, “But we have all gained great knowledge in our own domains. And now it is time for our fields to evolve into a true science. We are not amateurs anymore, simply playing around with fire. We are now establishing expertise, creating sub-domains, arriving at a general consensus of the problem and its underlying structure! To an outsider, it will probably look daunting. But so does every scientific field once it matures. And we will continue to make new ground by standing on the shoulders of elephants!”

“Giraffes.” Corrected the fourth.

“Zebras.” Answered a fifth.