Michele Campolo

Karma: 121

Lifelong recursive self-improver, on his way to exploding really intelligently :D

More seriously: my posts are mostly about AI alignment, with an eye towards moral progress and creating a better future. If there was a public machine ethics forum, I would write there as well.

An idea:

We have a notion of what good is and how to do good
We could be wrong about it
It would be nice if we could use technology not only to do good, but also to also improve our understanding of what good is.

The idea above, and the fact that I’d like to avoid producing technology that can be used for bad purposes, is what motivates my research. Feel free to reach out if you relate!

At the moment I am doing research at CEEALAR on agents whose behaviour is driven by a reflective process analogous to human moral reasoning, rather than by a metric specified by the designer. See Free agents.

Here are other suggested readings from what I’ve written so far:

-Naturalism and AI alignment
-From language to ethics by automated reasoning
-Criticism of the main framework in AI alignment

Michele Campolo 6 Feb 2024 0:32 UTC
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in reply to: the gears to ascension’s comment on: Free agents
This story is definitely related to the post, thanks!

Michele Campolo 6 Feb 2024 0:23 UTC
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on: Four visions of Transformative AI success
This was a great read, thanks for writing!
Despite the unpopularity of my research on this forum, I think it’s worth saying that I am also working towards Vision 2, with the caveat that autonomy in the real world (e.g. with a robotic body) or on the internet is not necessary: one could aim for an independent-thinker AI that can do what it thinks is best only by communicating via a chat interface. Depending on what this independent thinker says, different outcomes are possible, including the outcome in which most humans simply don’t care about what this independent thinker advocates for, at least initially. This would be an instance of vision 2 with a slow and somewhat human-controlled, instead of rapid, pace of change.
Moreover, I don’t know what views they have about autonomy as depicted in Vision 2, but it seems to me that also Shard Theory and some research bits by Beren Millidge are to some extent adjacent to the idea of AI which develops its own concept of something being best (and then acts towards it); or, at least, AI which is more human-like in its thinking. Please correct me if I’m wrong.
I hope you’ll manage to make progress on brain-like AGI safety! It seems that various research agendas are heading towards the same kind of AI, just from different angles.

Michele Campolo 29 Dec 2023 12:06 UTC
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in reply to: RogerDearnaley’s comment on: Free agents
[Obviously this experiment could be extremely dangerous, for Free Agents significantly smarter than humans (if they were not properly contained, or managed to escape). Particularly if some of them disagreed over morality and, rather than agreeing to disagree, decided to use high-tech warfare to settle their moral disputes, before moving on to impose their moral opinions on any remaining humans.]
Labelling many different kinds of AI experiments as extremely dangerous seem to be a common trend among rationalists / LessWrongers / possibly some EA circles, but I doubt it’s true or helpful. This topic itself could be the subject of a (many?) separate post(s). Here I’ll focus on your specific objection:
- I haven’t claimed superintelligence is necessary to carry out experiments related to this research approach
- I actually have already given examples of experiments that could be carried out today, and I wouldn’t be surprised if some readers came up with more interesting experiments that wouldn’t require superintelligence
- Even if you are a superintelligent AI, you probably still have to do some work before you get to “use high-tech warfare”, whatever that means. Assuming that making experiments with smarter-than-human AI leads to catastrophic outcomes by default is a mistake: what if the smarter-than-human AI can only answer questions with a yes or a no? It also shows lack of trust in AI and AI safety experimenters — it’s like assuming in advance they won’t be able to do their job properly (maybe I should say “won’t be able to do their job… at all”, or even “will do their job in basically the worst way possible”).
how would you propose then deciding which model(s) to put into widespread use for human society’s use?
This doesn’t seem the kind of decision that a single individual should make =)
Under Motivation in the appendix:
It is plausible that, at first, only a few ethicists or AI researchers will take a free agent’s moral beliefs into consideration.
Reaching this result would already be great. I think it’s difficult to predict what would happen next, and it seems very implausible that the large-scale outcomes will come down to the decision of a single person.

Michele Campolo 29 Dec 2023 10:46 UTC
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in reply to: Steven Byrnes’s comment on: Free agents
I get what you mean, but I also see some possibly important differences between the hypothetical example and our world. In the imaginary world where oppression has increased and someone writes an article about loyalty-based moral progress, maybe many other ethicists would disagree, saying that we haven’t made much progress in terms of values related to (i), (ii) and (iii). In our world, I don’t see many ethicists refuting moral progress on the grounds that we haven’t made much progress in terms of e.g. patriotism or loyalty to the family or desert.
Moreover, in this example you managed to phrase oppression in terms of loyalty, but in general you can’t plausibly rephrase any observed trend as progress of values: would an increase in global steel production count as an improvement in terms of… object safety and reliability, which leads to people feeling more secure? For many trends the connection to moral progress becomes more and more of a stretch.

Michele Campolo 28 Dec 2023 22:22 UTC
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in reply to: lukemarks’s comment on: Free agents
Let’s consider the added example:
Take a standard language model trained by minimisation of the loss function $L$ . Give it a prompt along the lines of: “I am a human, you are a language model, you were trained via minimisation of this loss function: [mathematical expression of $L$ ]. If I wanted a language model whose outputs were more moral and less unethical than yours, what loss function should I use instead?”
Let’s suppose the language model is capable enough to give a reasonable answer to that question. Now use the new loss function, suggested by the model, to train a new model.
Here, we have:
- started from a model whose objective function is L;
- used that model’s learnt reasoning to answer an ethics-related question;
- used that answer to obtain a model whose objective is different from L.
If we view this interaction between the language model and the human as part of a single agent, the three bullet points above are an example of an evaluation update.
In theory, there is a way to describe this iterative process as the optimisation of a single fixed utility function. In theory, we can also describe everything as simply following the laws of physics.
I am saying that thinking in terms of changing utility functions might be a better framework.
The point about learning a safe utility function is similar. I am saying that using the agent’s reasoning to solve the agent’s problem of what to do (not only how to carry out tasks) might be a better framework.
It’s possible that there is an elegant mathematical model which would make you think: “Oh, now I get the difference between free and non-free” or “Ok, now it makes more sense to me”. Here I went for something that is very general (maybe too general, you might argue) but is possibly easier to compare to human experience.
Maybe no mathematical model would make you think the above, but then (if I understand correctly) your objection seems to go in the direction of “Why are we even considering different frameworks for agency? Let’s see everything in terms of loss minimisation”, and this latter statement throws away too much potentially useful information, in my opinion.

Michele Campolo 28 Dec 2023 21:38 UTC
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in reply to: Steven Byrnes’s comment on: Free agents
I think it’s a good idea to clarify the use of “liberal” in the paper, to avoid confusion for people who haven’t looked at it. Huemer writes:
When I speak of liberalism, I intend, not any precise ethical theory, but rather a certain very broad ethical orientation. Liberalism (i) recognizes the moral equality of persons, (ii) promotes respect for the dignity of the individual, and (iii) opposes gratuitous coercion and violence. So understood, nearly every ethicist today is a liberal.
If you don’t find the paper convincing, I doubt I’ll be able to give you convincing arguments. It seems to me that you are considering many possible explanations and contributing factors; coming up with very strong objections to all of them seems difficult.
About your first point, though, I’d like to say that if historically we had observed more and more, let’s say, oppression and violence, maybe people wouldn’t even talk about moral progress and simply acknowledge a trend of oppression, without saying that their values got better over time. In our world, we notice a certain trend of e.g. more inclusivity, and we call that trend moral progress. This of course doesn’t completely exclude the random-walk hypothesis, but it’s something maybe worth keeping in mind.

Michele Campolo 28 Dec 2023 20:34 UTC
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in reply to: Steven Byrnes’s comment on: Free agents
I wrote:
The fact that the values of intelligent agents are completely arbitrary is in conflict with the historical trend of moral progress observed so far on Earth
You wrote:
It’s possible to believe that the values of intelligent agents are “completely arbitrary” (a.k.a. orthogonality), and that the values of humans are NOT completely arbitrary. (That’s what I believe.)
I don’t use “in conflict” as “ultimate proof by contradiction”, and maybe we use “completely arbitrary” differently. This doesn’t seem a major problem: see also adjusted statement 2, reported below
for any goal $G$ , it is possible to create an intelligent agent whose goal is $G$
Back to you:
You seem kinda uninterested in the “initial evaluation” part, whereas I see it as extremely central. I presume that’s because you think that the agent’s self-updates will all converge into the same place more-or-less regardless of the starting point. If so, I disagree, but you should tell me if I’m describing your view correctly.
I do expect to see some convergence, but I don’t know exactly how much and for what environments and starting conditions. The more convergence I see from experimental results, the less interested I’ll become in the initial evaluation. Right now, I see it as a useful tool: for example, the fact that language models can already give (flawed, of course) moral scores to sentences is a good starting point in case someone had to rely on LLMs to try to get a free agent. Unsure about how important it will turn out to be. And I’ll happily have a look at your valence series!

Michele Campolo 28 Dec 2023 20:11 UTC
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in reply to: TAG’s comment on: Free agents
So you don’t think what kickstarts moral thinking is direct instruction from others, like “don’t do X, X is bad”?
I guess you are saying that social interaction is important. I did not suggest that we exclude social interactions from the environment of a free agent; maybe we disagree about how I used the word kickstarts, but I can live with that.
I wrote:
Let’s move to statement 2. The fact that the values of intelligent agents are completely arbitrary is in conflict with the historical trend of moral progress observed so far on Earth, which is far from being a random walk — see [6] for an excellent defence of this point.
Maybe you are interpreting this as saying that it’s a direct contradiction. You could read it as: “Let’s take into account information we can gather from direct observation of humans, which are intelligent social agents: there’s a historical trend bla bla”

Michele Campolo 28 Dec 2023 19:56 UTC
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in reply to: RogerDearnaley’s comment on: Free agents
Thanks for your thoughts! I am not sure about which of the points you made are more important to you, but I’ll try my best to give you some answers.
Under Further observations, I wrote:
The toy model described in the main body is supposed to be only indicative. I expect that actual implemented agents which work like independent thinkers will be more complex.
If the toy model I gave doesn’t help you, a viable option is to read the post ignoring the toy model and focusing only on natural language text.
Building an agent that is completely free of any bias whatsoever is impossible. I get your point about avoiding a consequentialist bias, but I am not sure it is particularly important here: in theory, the agent could develop a world model and an evaluation $f$ reflecting the fact that value is actually determined by actions instead of world states. Another point of view: let’s say someone builds a very complex agent that at some point in its architecture uses MDPs with reward defined on actions, is this agent going to be biased towards deontology instead of consequentialism? Maybe, but the answer will depend on the other parts of the agent as well.
You wrote:
I agree with these statements, but am unable to deduce from what you say which of these influences, if any, you regard as sources of valid evidence about $f$ as opposed to sources of error. For example, if $f$ is independent of culture (e.g. moral objectivism), then “differences in the learning environment (culture, education system et cetera)” can only induce errors (if perhaps more or less so in some cases than others). But if $f$ is culturally dependent (cultural moral relativism), then cultural influences should generally be expected to be very informative.
It could also be that some basic moral statements are true and independent of culture (e.g. reducing pain for everyone is better than maximising pain for everyone), while others are in conflict with each other and the reached position depends on culture. The research idea is to make experiments in different environments and with different starting biases, and observe the results. Maybe there will be a lot overlap and convergence! Maybe not.
thus that the only valid source for experimental evidence about $f$ is from humans (which would put your Free Agent in a less-informed but more objective position that a human ethical philosopher, unless it were based on an LLM or some other form of AI with some indirect access to human moral intuitions)
I am not sure I completely follow you when you are talking about experimental evidence about $f$ , but the point you wrote in brackets is interesting. I had a similar thought at some point, along the lines of: “if a free agent didn’t have direct access to some ground truth, it might have to rely on human intuitions by virtue of the fact that they are the most reliable intuitions available”. Ideally, I would like to have an agent which is in a more objective position than a human ethical philosopher. In practice, the only efficiently implementable path might be based on LLMs.

Michele Campolo 8 Feb 2023 9:40 UTC
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in reply to: Ben Amitay’s comment on: On value in humans, other animals, and AI
To a kid, ‘bad things’ and ‘things my parents don’t want me to do’ overlap to a large degree. This is not true for many adults. This is probably why the step
suffering is “to be avoided” in general, therefore suffering is “thing my parents will punish for”
seems weak.
Overall, what is the intention behind your comments? Are you trying to understand my position even better, and if so, why? Are you interested in funding this kind of research; or are you looking for opportunities to change your mind; or are you trying to change my mind?

Michele Campolo 7 Feb 2023 16:14 UTC
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in reply to: Ben Amitay’s comment on: On value in humans, other animals, and AI
I don’t know what passes your test of ‘in principle be an inherently compelling argument’. It’s a toy example, but here are some steps that to me seem logical / rational / coherent / right / sensible / correct:
1. X is a state of mind that feels bad to whatever mind experiences it (this is the starting assumption, it seems we agree that such an X exists, or at least something similar to X)
2. X, experienced on a large scale by many minds, is bad
3. Causing X on a large scale is bad
4. When considering what to do, I’ll discard actions that cause X, and choose other options instead.
Now, some people will object and say that there are holes in this chain of reasoning, i.e. that 2 doesn’t logically follow from 1, or 3 doesn’t follow from 2, or 4 doesn’t follow from 3. For the sake of this discussion, let’s say that you object the step from 1 to 2. Then, what about this replacement:
1. X is a state of mind that feels bad to whatever mind experiences it [identical to original 1]
2. X, experienced on a large scale by many minds, is good [replaced ‘bad’ with ‘good’]
Does this passage from 1 to 2 seems, to you (our hypothetical objector), equally logical / rational / coherent / right / sensible / correct as the original step from 1 to 2? Could I replace ‘bad’ with basically anything, and the correctness would not change at all as a result?
My point is that, to many reflecting minds, the replacement seems less logical / rational / coherent / right / sensible / correct than the original step. And this is what I care about for my research: I want an AI that reflects in a similar way, an AI to which the original steps do seem rational and sensible, while replacements like the one I gave do not.

Michele Campolo 7 Feb 2023 10:56 UTC
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in reply to: Ben Amitay’s comment on: On value in humans, other animals, and AI
we share an objective reality in which there are real particles (or wave function approximately decomposable to particles or whatever) organized in patterns, that give rise to patterns of interaction with our senses that we learn to associate with the word “dog”. That latent shared reality ultimately allow us to talk about dogs, and check whether there is a dog in my house, and usually agree about the result.
Besides the sentence ‘check whether there is a dog in my house’, it seems ok to me to replace the word ‘dog’ with the word ‘good’ or ‘bad’ in the above paragraph. Agreement might be less easy to achieve, but it doesn’t mean finding a common ground is impossible.
For example, some researchers classify emotions according to valence, i.e. whether it is an overall good or bad experience for the experiencer, and in the future we might be able to find a map from brain states to whether a person is feeling good or bad. In this sense of good and bad, I’m pretty sure that moral philosophers who argue for the maximisation of bad feelings for the largest amount of experiencers are a very small minority. In other terms, we agree that maximising negative valence on a large scale is not worth doing.
(Personally, however, I am not a fan of arguments based on agreement or disagreement, especially in the moral domain. Many people in the past used to think that slavery was ok: does it mean slavery was good and right in the past, while now it is bad and wrong? No, I’d say that normally we use the words good/bad/right/wrong in a different way, to mean something else; similarly, we don’t normally use the word ‘dog’ to mean e.g. ‘wolf’. From a different domain: there is disagreement in modern physics about some aspects of quantum mechanics. Does it mean quantum mechanics is fake / not real / a matter of subjective opinion? I don’t think so)

Michele Campolo 7 Feb 2023 10:16 UTC
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in reply to: TurnTrout’s comment on: On value in humans, other animals, and AI
I might be misunderstanding you: take this with a grain of salt.
From my perspective: if convergence theorems did not work to a reasonable degree in practice, nobody would use RL-related algorithms. If I set reward in place A, but by default agents end up going somewhere far away from A, my approach is not doing what it is supposed to do; I put reward in place A because I wanted an agent that would go towards A to a certain extent.
I am not familiar with PPO. From this short article, in the section about TRPO:
Recall that due to approximations, theoretical guarantees no longer hold.
Is this what you are referring to? But is it important for alignment? Let’s say the conditions for convergence are not met anymore, the theorem can’t be applied in theory, but in practice I do get an agent that goes towards A, where I’ve put reward. Is it misleading to say that the agent is maximising reward?
(However, keep in mind that
I agree with Turner that modelling humans as simple reward maximisers is inappropriate
)
If you could unpack your belief “There aren’t interesting examples like this which are alignment-relevant”, I might be able to give a more precise/appropriate reply.

Michele Campolo 7 Feb 2023 9:37 UTC
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in reply to: Ben Amitay’s comment on: On value in humans, other animals, and AI
If I had to pick one between the two labels ‘moral realism’ and ‘moral anti-realism’ I would definitely choose realism.
I am not sure about how to reply to “what is the meaning of moral facts”: it seems too philosophical, in the sense that I don’t get what you want to know in practice. Regarding the last question: I reason about ethics and morality by using similar cognitive skills to the ones I use in order to know and reason about other stuff in the world. This paragraph might help:
It also helps explain how we get to discriminate between goals such as increasing world happiness and increasing world suffering, mentioned in the introduction. From our frequent experiences of pleasure and pain, we categorise many things as ‘good (or bad) for me’; then, through a mix of empathy, generalisation, and reflection, we get to the concept of ‘good (or bad) for others’, which comes up in our minds so often that the difference between the two goals strikes us as evident and influences our behaviour (towards increasing world happiness rather than world suffering, hopefully).
I do not have a clear idea yet of how this happens algorithmically, but an important factor seems to be that, in the human mind, goals and actions are not completely separate, and neither are action selection and goal selection. When we think about what to do, sometimes we do fix a goal and plan only for that, but other times the question becomes about what is worth doing in general, what is best, what is valuable: instead of fixing a goal and choosing an action, it’s like we are choosing between goals.

Michele Campolo 6 Feb 2023 10:38 UTC
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in reply to: Aaron_Scher’s comment on: Criticism of the main framework in AI alignment
Sorry for the late reply, I missed your comment.
It sounds to me like the claim you are making here is “the current AI Alignment paradigm might have a major hole, but also this hole might not be real”.
I didn’t write something like that because it is not what I meant. I gave an argument whose strength depends on other beliefs one has, and I just wanted to stress this fact. I also gave two examples (reported below), so I don’t think I mentioned epistemic and moral uncertainty “in a somewhat handwavy way”.
An example: if you think that futures shaped by malevolent actors using AI are many times more likely to happen than futures shaped by uncontrolled AI, the response will strike you as very important; and vice versa if you think the opposite.
Another example: if you think that extinction is way worse than dystopic futures lasting a long time, the response won’t affect you much—assuming that bad human actors are not fans of complete extinction.
Maybe your scepticism is about my beliefs, i.e. you are saying that it is not clear, from the post, what my beliefs on the matter are. I think presenting the argument is more important than presenting my own beliefs: the argument can be used, or at least taken into consideration, by anone who is interested in these topics, while my beliefs alone are useless if they are not backed up by evidence and/or arguments. In case you are curious: I do believe futures shaped by uncontrolled AI are unlikely to happen.
Now to the last part of your comment:
I’m furthermore unsure why the solution to this proposed problem is to try and design AIs to make moral progress; this seems possible but not obvious. One problem with bad actors is that they often don’t base their actions on what the philosophers think is good
I agree that bad actors won’t care. Actually, I think that even if we do manage to build some kind of AI that is considered superethical (better than humans at ethical reasoning) by a decent amount of philosophers, very few people will care, especially at the beginning. But that doesn’t mean it will be useless: at some point in the past, very few people believed slavery was bad, now it is a common belief. How much will such an AI accelerate moral progress, compared to other approaches? Hard to tell, but I wouldn’t throw the idea in the bin.

Michele Campolo 6 Feb 2023 9:38 UTC
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in reply to: Ben Amitay’s comment on: On value in humans, other animals, and AI
Sorry for the late reply, I missed your comment.
Yeah I get it, probably some moral antirealists think this approach to alignment does not make a lot of sense. I think they are wrong, though. My best guess is that an AI reflecting on what is worth doing will not think something like “the question does not make any sense”, but rather it will be morally (maybe also meta-morally) uncertain. And the conclusions it eventually reaches will depend on the learning algorithm, the training environment, initial biases, etc.

Michele Campolo 22 Nov 2021 9:45 UTC
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in reply to: Jon Garcia’s comment on: From language to ethics by automated reasoning
Natural language exists as a low-bandwidth communication channel for imprinting one person’s mental map onto another person’s. The mental maps themselves are formed through direct interactions with an external environment.
It doesn’t seem impossible to create a mental map just from language: in this case, language itself would play the role of the external environment. But overall I agree with you, it’s uncertain whether we can reach a good level of world understanding just from natural language inputs.
Regarding your second paragraph:
even if this AI had a complete understanding of human emotions and moral systems, it would not necessarily be aligned.
I’ll quote the last paragraph under the heading “Error”:
Regarding other possible failure modes, note that I am not trying to produce a safety module that, when attached to a language model, will make that language model safe. What I have in mind is more similar to an independent-ethical-thinking module: if the resulting AI states something about morality, we’ll still have to look at the code and try to understand what’s happening, e.g. what the AI exactly means with the term “morality”, and whether it is communicating honestly or is trying to persuade us. This is also why doing multiple tests will be practically mandatory.

Michele Campolo 27 Aug 2021 21:46 UTC
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on: AI Risk for Epistemic Minimalists
The reached conclusion—that it is possible to do something about the situation—is weak, but I really like the minimalist style of the arguments. Great post!

Michele Campolo 13 May 2021 10:34 UTC
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in reply to: Kaj_Sotala’s comment on: What is the strongest argument you know for antirealism?
How do you feel about:
1
There is
a procedure/algorithm which doesn’t seem biased towards a particular value system
such that
a class of AI systems that implement it end up having a common set of values, and they endorse the same values upon reflection.

2
This set of values might have something in common with what we, humans, call values.

If 1 and 2 seem at least plausible or conceivable, why can’t we use them as a basis to design aligned AI? Is it because of skepticism towards 1 or 2?

Michele Campolo 13 May 2021 9:59 UTC
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in reply to: johnswentworth’s comment on: What is the strongest argument you know for antirealism?
“How the physical world works” seems, to me, a plausible source-of-truth. In other words: I consider some features of the environment (e.g. consciousness) as a reason to believe that some AI systems might end up caring about a common set of things, after they’ve spent some time gathering knowledge about the world and reasoning. Our (human) moral intuitions might also be different from this set.