What are the most plausible "AI Safety warning shot" scenarios?

I think "makes 50% of currently-skeptical people change their minds" is a high bar for a warning shot. On that definition e.g. COVID-19 will probably not be a warning shot for existential risk from pandemics. I do think it is plausible that AI warning shots won't be much better than pandemic warning shots. (On your definition it seems likely that there won't ever again be a warning shot for any existential risk.)

For a more normal bar, I expect plenty of AI systems to fail at large scales in ways that seem like "malice," and then to cover up the fact that they've failed. AI employees will embezzle funds, AI assistants will threaten and manipulate their users, AI soldiers will desert. Events like this will make it clear to most people that there is a serious problem, which plenty of people will be working on in order to make AI useful. The base rate will remain low but there will be periodic high-profile blow-ups.

I don't expect this kind of total unity of AI motivations you are imagining, where all of them want to take over the world (so that the only case where you see something frightening is a failed bid to take over the world). That seems pretty unlikely to me, though it's conceivable (maybe 10-20%?) and may be an important risk scenario. I think it's much more likely that we stamp out all of the other failures gradually, and are left with only the patient+treacherous failures, and in that case whether it's a warning shot or not depends entirely on how much people are willing to generalize.

I do think the situation in the AI community will be radically different after observing these kinds of warning shots, even if we don't observe an AI literally taking over a country.

There is a very narrow range of AI capability between "too stupid to do significant damage of the sort that would scare people" and "too smart to fail at takeover if it tried."

Why do you think this is true? Do you think it's true of humans? I think it's plausible if you require "take over a country" but not if you require e.g. "kill plenty of people" or "scare people who hear about it a lot."

(This is all focused on intent alignment warning shots. I expect there will also be other scary consequences of AI that get people's attention, but the argument in your post seemed to be just about intent alignment failures.)

One of the basic problems in the embedded agency sequence [LW · GW] is: how does an agent recognize its own physical instantiation in the world, and avoid e.g. dropping a big rock on the machine it's running on? One could imagine an AI with enough optimization power to be dangerous, which gets out of hand but then drops a metaphorical rock on its own head - i.e. it doesn't realize that destroying a particular data center will shut itself down.

Similarly, one could imagine an AI which tries to take over the world, but doesn't realize that unplugging the machine on which it's running will shut it down - because it doesn't model itself as embedded in the world. (For similar reasons, such an AI might not see any reason to create backups of itself.)

Another possible safety valve: one could imagine an AI which tries to wirehead, but its operators put a lot of barriers in place to prevent it from doing so. The AI seizes whatever resources it needs to metaphorically smash those barriers, does so violently, then wireheads itself and just sits around.

Generalizing these two scenarios: I think it's plausible that unprincipled AI architectures tend to have built in safety valves - they'll tend to shoot themselves in the foot if they're able to do so. That's definitely not something I'd want to bet the future of the human species on, but it is a class of scenarios which would allow for an AI to deal a lot of damage while still failing to take over.

Currently, the answer that seems most plausible to me is an AGI that is (a) within the narrow range I described, and (b) willing to take a gamble for some reason -- perhaps, given its values and situation, it has little to gain from biding its time. So it makes an escape-and-conquest attempt even though it knows it only has a 1% chance of success; it gets part of the way to victory and then fails. I think I'd assign, like, 5% credence to something like this happening.

A "AI safety warning shot" is some event that causes a substantial fraction of the relevant human actors (governments, AI researchers, etc.) to become substantially more supportive of AI research and worried about existential risks posed by AI.

A really well written book on AI safety, or other public outreach campaign could have this effect.

For many events, such as a self driving car crashing, it might be used as evidence for an argument about AI risk.

On to powerful AI systems causing harm, I agree that your reasoning applies to most AI's. There are a few designs that would do something differently. Myopic agents are ones with lots of time discounting within their utility function. If you have a full super-intelligence that wants to do X as quickly as possible, such that the fastest way to do X will also destroy itself, that might be survivable. Consider an AI set to maximize the probability that its own computer case is damaged within the next hour. The AI could bootstrap molecular nanotech, but that would take several hours. The AI thinks that time travel is likely impossible, so by that point, all the mass in the universe can't help it. The AI can hack a nuke and target itself. Much better by its utility function. Nearly max utility. If it can, it might upload a copy of its code to some random computer. (There is some tiny chance that time travel is possible, or that its clock is wrong) So we only get a near miss, if the AI doesn't have enough spare bandwidth or compute to do both. This is assuming that it can't hack reality in a microsecond.

There are a few other scenarios, for instance impact minimising agents. There are some designs of agents that are restricted to have a "small" effect on the future, as a safety measure. This is measured by the difference between what actually happens, and what would happen if it did nothing. When this design understands chaos theory, it will find that all other actions result in too large an effect, and do nothing. It might do a lot of damage before this somehow, depending on circumstances. I think that the AI discovering some fact about the universe that causes the AI to stop optimising effectively is a possible behaviour mode. Another example of this would be pascals mugging. The agent acts dangerously, and then starts outputting gibberish as it capitulates to a parade of fanciful pascals muggers.