I think this is the main thing preserving the (miserable) jobs of people at call centers.

But I'm not convinced. With today's models, is it really that much easier to defraud an AI agent than a human?

I do think a lot of people are much more WILLING to try and defraud an AI agent than a person, so maybe that's the difference. There's a parallel there to people being much more willing to mess with Waymos. I think both are a huge shame.

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modeless 37 minutes ago | parent | next [-]

The difference is AIs are identical and don't learn. If you figure out how to defraud a human once it may not work on the next guy. If you figure out how to defraud an AI once you can repeat it indefinitely until the AI is shut off.

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himata4113 14 minutes ago | parent [-]

Fortunately they can escalate to a generally intelligent model, opus deception benchmarks are approaching 0%.

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modeless 11 minutes ago | parent [-]

Still, all instances of Opus are identical and do not learn. As long as the rate of mistakes is nonzero, my point stands.

	▲	himata4113 3 minutes ago \| parent [-]
		I believe that still reduces the workload by a huge factor as you would need a lot less people handling approvals, besides inverse is true agents trained in detecting deception might outperform human verifiers (two agent system). If a model can hold up to attacks for a long period of time the approval process can be automated as well, but this would have to be a very slow rollout spanning more than a year.

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rcxdude an hour ago | parent | prev [-]

Largely this can be solved the same way it is at a lot of call centers: first line support isn't actually given permission to do much more than the customer can do themselves.

	▲	howunfortunate an hour ago \| parent [-]
		I wouldn't exactly call that "solved", this still sucks for the customer. I think the ideal solution would be to track and punish fraudsters, but there seems to be little political will to do anything about petty crime these days.