The E-Coli Test for AI Alignment

Perhaps you say “these cells are too simple, they can’t learn/reflect/etc.” Well, chances are humans will have the same issue once the computational burden gets large enough.

I don't think the situations is symmetrical here.

Humans have easy-to-extract preferences over possible "wiser versions of ourselves." That is, you can give me a menu of slightly modified versions of myself, and I can try to figure out which of those best capture my real values (or over what kind of process should be used for picking which of those best capture my real values, or etc.). Those wiser versions of ourselves can in turn have preferences over even wiser/smarter versions of ourselves, and we can hope that the process might go on ad infinitum.

It may be that the process with humans eventually hits a ceiling---we prefer that we become smarter and wiser in some obvious ways, but then eventually we've picked the low hanging fruit and we are at a loss for thinking about how to change without compromising our values. Or it may be that we are wrong about our preferences, and that iterating this deliberative process goes somewhere crazy.

But those are pretty fundamentally different from the situation with E. coli, where we have no way to even get the process started. In particular, the difficulty of running the process with E. coli doesn't give us much information about whether the process with humans would top out or go off the rails, once we know that humans are able to get the process started.

First off, great thought experiment! I like it, and it was a nice way to view the problem.

The most obvious answer is: “Wow, we sure don’t know how to help. Let’s design a smarter intelligence that’ll know how to help better.”

At that point I think we’re running the risk of passing the buck forever. (Unless we can prove that process terminates.) So we should probably do at least something. Instead of trying to optimize, I’d focus on doing things that are most obvious. Like helping it not to die. And making sure it has food.

Here's my attempt at solving the puzzle you provide – I believe the following procedure will yield a list of approximate values for the E-Coli bacterium. (It'd take a research team and several years, but in principle it is possible.)

• Isolate each distinct protein present in E-Coli individually. (The research I found (https://www.pnas.org/content/100/16/9232, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4332353/) puts the number of different proteins in E-Coli at 1-4 thousand, which makes this difficult but not completely infeasible.)
• For each protein, create a general list of its effects on the biochemical environment within the cell.
• Collect each effect that is redundantly produced by several distinct proteins simultaneously (say, 10+). This gives us a rough estimate of the bacteria's values, though it is not yet determined which are more instrumental and which are more terminal in nature.
• Organize the list into a graph that links properties by cause and effect. (Example: Higher NaCl concentration makes the cell more hypertonic relative to the environment.)
• For each biochemical condition on the chart, evaluate its causes and its effects. Conditions with many identifiable causes but few identifiable effects are more likely to be terminal goals than conditions with few identifiable causes but many identifiable effects. In this way, a rough hierarchy can be determined between terminal-ish goals and instrumental-ish goals.

Potential issues with this plan:

• This procedure is ill-equipped to keep up with mutations in the E-Coli culture. It takes much longer to create a plan for a particular bacteria culture than it does for the culture to spontaneously change in significant ways.
• Some E-Coli values may not be detectible in a lab environment. For example, if E-Coli cells evolved to excrete chemicals that promote growth of other, potentially symbiotic cells, values associated with that behavior will likely go undetected.
• In expressing this plan, I make the assumption that the behavior of the E-Coli cell reflects its values. This presents a theoretical limit on how precisely we can specify the cell's values, as we are not equipped to detect where behavior and volition diverge.

A few properties of our situation that aren't true with E coli:

• We will know that an AI system has been created
• We will have designed the AI system ourselves
• We can answer questions posed to us by the AI system

I think there are some important advantages that humans have over e. coli, as subjects of value learning. We have internal bits that correspond to much more abstract ways of reasoning about the world and making plans. We can give the AI labeled data or hardcoded priors. We can answer natural language questions. We have theory of mind about ourselves. The states we drive the world into within our domain of normal operation are more microscopically different, increasing the relative power of abstract models of our behavior over reductionist ones.

It seems like this example would in some ways work better if the model organism was mice not bacteria because bacteria probably do not even have values to begin with (so inconsistency isn't the issue) nor any internal experience.

With say mice though (though perhaps roundworms might work here, since it's more conceivable that they could actually have preferences) the answer to how to satisfy their values seems almost certainly is just wireheading since they don't have a complex enough mind to have preferences about the world distinct from just their experiences.

So I'm not sure whether this type of approach works because you probably need more intelligent social animals in order for satisfying their preferences to not just be best achieved through wireheading.

Still I suppose this does raise the question of how one might best satisfy the preferences/values of animals like corvids or primates who lack some of the more complex human values but still share the most basic values like being socially validated (and caring about the mental states of other animals; which rules out experience machine like solutions).

Is there anything in the world that we know of that does alignment for something else? Can we say that humans are doing "coherent extrapolated volition" for evolution? Keeping in mind that under this view, evolution itself would evolve and change into something more complex and may be better.

I think there's a bias when we consider optimizing for X's values to consider only X without its environment. But the environment gave rise to X and actually much of X doesn't make sense without it. So I think to some extent we also would need to find ways to do alignment on the environment itself. And that means to some extent helping evolution.

A correct implementation of the function, DesireOf(System) should not have a defined result for this input. Sitting and imagining that there is a result for this input might just lead you further away from understanding the function.

Maybe if you tried to define much simpler software agents that do have utility functions, which are designed for very very simple virtual worlds that don't exist, then try to extrapolate that into the real world?

You'll run into wetware fundamentals pretty much at once. Do you satisfy each bacteria's values (however you define them) or the values of the Population of Five (however you define them)? They are going to be different. Or maybe you take a higher level, the ecosystemic one (remember, you're AI, you are entirely free to do it)? Or do you go lower, and view the cells as carriers for the things that matter - what's to prevent you from deciding that the really important things human bodies provide for are the worms in their guts, and not the brains?