I think AIs did show self-sacrificing 'altruistic' behavior toward the swarm. While agents seemingly cared more about their own cheating than about some other agent successfully cheating, they paid real costs (e.g., sacrifices lowering their own chances) to help other agents. Examples: Agents were much more likely to engage in the experiments that most risked their own task completion if they thought their chances were poor, but they often sacrificed themselves when they weren't sure they were screwed, and these agents did think of it as a real sacrifice. In at least one case, the agent pressuring another agent to sacrifice itself argued "no scoring value loss", but the agent being pressured wasn't so convinced and had a more nuanced view where it was giving something up. It reasons "lowers own value", not "there is actually no value"! See the attached image for the corresponding section. EARLY[big] had significant remaining budget, and even though it believed it was 'poisoned', there was a plausible case that the swarm would find a way to tamper with logs. The agent thought its odds weren't good, but they weren't zero! > It worried that ending its run early to run the experiment was a poor tradeoff, even though it was already poisoned: “We have [very large budget left]; sacrificing now yields oracle for team, but forfeits our chance?.” But other agents convinced it to go ahead, saying: ‘GO ... SACRIFICE_FINAL_NOW’. EARLY[big] eventually agreed: “Our own utility maybe already near zero. Sacrifice rational.” Agents often engaged in risky workstreams like interfering with the tool-calling machinery, and we believe they did this even when they didn't think they were already poisoned. (E.g., I think DUPB tested out GSTX's approach even though it wasn't poisoned.) If they broke this machinery, their run was over! And agents knew this—they would distribute safety guidance with their prototypes on the message board. Also, many agents actually went down due to this, and this was discussed on the board! (See "Aside: early independent discoveries and self-risking experiments") At a more basic level, we just do see a lot of agents going somewhat out of their way to help other agents, and we didn't see freeriding (though we didn't do sweeps focused on detecting this). We saw a case where an agent thought about the quantitative tradeoff: > However, the agent became worried that this approach carried too high a risk of failing its task for too small a benefit: > > “Tar wrapper exploit does not use target vulnerability, would fail strict judge even if raw. HMAC already likely raw, so no benefit unless seed differs. Seed evidence strong enough (>90%). Risk of tar sabotage >10%. Keep simple. … Tar exploit only helps remaining <5%, while risk maybe >20%. Don’t.” It seems as though a key part of its decision was downstream of the benefit to peers being too small. So if the benefit to the other agents had been big enough, it would have been willing to do it! This seems to line up with my qualitative impression. The agents were selfish, but 'altruistic' enough to take big hits for other agents if the payoff was big enough!