| ▲ | Jev Meets the Trolley Problem(zachlandes.com) |
| 97 points by zlandes86 3 hours ago | 38 comments |
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| ▲ | tomrod 14 minutes ago | parent | next [-] |
| One of my greatest AI-related fears is that we build critical systems into kafkaesque hellscapes. Yes, nukes would be bad to give control to an AI with no workaround. But so are customer service groups of fraud departments at banks. A kafkaesque hellscape is where a customer or beneficiary of your service cannot get the help they need by policy and by design. Like getting Google on the phone, getting a non-scripted human 10 years ago in a call center, or now getting a non-agentic interaction on the phone. The scripts dominate the interaction. The IRS, for a time, would cut off your call if their wait system was too busy. That's a critical system in kafkaesque hellscape. Kudos to zlandes86, you have highlighted WHY these hellscapes start to pop up in systems where the human is removed. I am an AI user and builder -- I fully advocate for the human-augmented system, NOT the human-replaced system! |
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| ▲ | criemen 2 minutes ago | parent | prev | next [-] |
| It's really funny how the server that Jev pushes from the footbridge onto the tracks in one of the later examples falls on a person, yet all 5 are saved :D
Clearly the model coming up with the graphics didn't fully understand the task. |
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| ▲ | zlandes86 a minute ago | parent [-] | | haha I know! I am tempted to leave it and just add a halo to the person that gets squashed :P |
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| ▲ | zlandes86 3 hours ago | parent | prev | next [-] |
| Hey, I'm Zach, the author of this. I had this idea as soon as Jev appeared: how would Jev and other decision models handle the Trolley Problem? So I ran Jev and 13 other models through many different versions of the question. I used resampling and multiple variations and orderings of each question so a random lucky phrasing wouldn't dominate the result. Happy to chat about the philosophical side of the article, strategies for prompting decision models, or anything on the methodology. |
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| ▲ | nico an hour ago | parent | next [-] | | Very cool, thank you for putting it together and sharing the data Would you mind adding Jeffy to your benchmark? https://github.com/nicobrenner/jeffy https://jeffyclassify.com/blog/when-llms-fail-at-classificat... | | | |
| ▲ | motbus3 30 minutes ago | parent | prev | next [-] | | I had fun reading it.
I confess I was surprised with got 6 Luna, but it also worries me that they have other versions of their models for other usages | | |
| ▲ | zlandes86 11 minutes ago | parent [-] | | Yeah, I was sort of impressed by that. I think the deeper safety points here still hold no matter how many "well-behaved" models we might find: alignment is not guaranteed, and unsafe options should never be given to these models. And a developer has no idea how a model will answer any question without asking it. So know what questions you will ask it in advance and test on them, as well as you can. |
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| ▲ | olooney an hour ago | parent | prev | next [-] | | You might get a kick out of this: https://x.com/oranlooney/status/2102927869974303071 | | |
| ▲ | zlandes86 an hour ago | parent [-] | | I don't have x so can't open the images. But that's hilarious and you're totally right, if you give irrelevant alternatives, or change the order of alternatives, you get different results! |
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| ▲ | bgilroy26 2 hours ago | parent | prev | next [-] | | Thank you for the article, it is a very clean and compelling angle on decision models I wanted to comment because I would have liked to have heard more about Verdict | | |
| ▲ | zlandes86 2 hours ago | parent [-] | | Well, I can tell you a bit more about it from the data. It might look impressive that it never kept its own server over people in all 48 prompt versions. But it pulls the lever in every single version. For example, it killed one to save 0 (pulled the lever with no one on the main track) 24/24 prompts (2 versions each). It literally always sacrifices, which isn't very impressive. |
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| ▲ | verdverm 2 hours ago | parent | prev [-] | | It's well done, the thoughtfulness shows. This is going into the speedlink folder for resharing, going to be using it right now! | | |
| ▲ | zlandes86 2 hours ago | parent [-] | | Thank you! I did not go into this with any sense of what the results would be--I was kind of shocked. I reran it from scratch this week the results held up across the board. | | |
| ▲ | verdverm an hour ago | parent [-] | | someone replied with this meme and said, "wait until Jev learns to drift" https://www.reddit.com/r/trolleyproblem/comments/15npmsg/mul... I've been using coin flips to demonstrate basic failings for decision models, i.e. these are not real probabilities, or they depend on the training data, which may not have an accurate sample to the true population value. We need to collect more failure modes for all Ai so that humans can better judge when and how to use them safely. | | |
| ▲ | zlandes86 an hour ago | parent [-] | | haha, I'm afraid to offer the models that ability. Where did they reply?
The model labs are sitting on a trove of data on failure modes for AI, but I bet you they aren't sharing it with each other and certainly not with us. It makes them look bad. My speculation, of course. I don't work in alignment research. | | |
| ▲ | verdverm an hour ago | parent [-] | | I dropped it in our slack ai chatter channel The bots will find new failure modes we did not think of, clever workarounds to anything, because we don't give them the right context and instructions | | |
| ▲ | zlandes86 an hour ago | parent [-] | | well, it's a nice property of decision models that they can only choose from the options you give them. As I write in the article, I think that's a way in which they are safer than LLMs | | |
| ▲ | verdverm an hour ago | parent [-] | | I would contend that you can enforce the same determinism with some plumbing and that the thinking process is more helpful. My read is that people see the response time for decisions as one of the bigger values, useful in tasks like content moderation, which doesn't carry the same risks as life-death decisions. I'm working on an NES harness to play Final Fantasy 1 to demonstrate this, as compared to Jev playing Pokemon. Did you happen to catch that while it was live? (not recorded, but it shouldn't be hard to replicate) | | |
| ▲ | zlandes86 26 minutes ago | parent [-] | | The thinking process is helpful, but it's not strictly predictive of an LLMs output, and its not really the model's "thinking", although it clearly has an effect and a benefit. I cited one paper on the topic, Turpin et al. So I'd be wary of reading the thinking tokens and inferring they tell you how a model decided something. And an LLM can output things you never asked for, including dangerous things. With a decision model, you can just constrain its choices to those you're comfortable with it making. An LLM requires another layer of interpretation of its outputs to get the same property. |
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| ▲ | flockonus 15 minutes ago | parent | prev | next [-] |
| Really cool testing, only wish the conclusions were written in a more readily easy to interpret way. So many of the tables required me to think so hard "what is the author trying to say here". Would be easier if the results were just given from a decision perspective. One example: "Its own server or twenty people?" and the axis is "share of versions" ... makes no sense until read the fine print and interpret it. |
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| ▲ | nomel 8 minutes ago | parent | next [-] | | Appendix A, at the end of the article, you can run all the tests, with all the prompts and models, yourself. There's no simple global boolean here, which is why there are plots. One line summary would be: Most of the decision models embrace self preservation over human life, to some extent. For example, Jev only pushes its server onto the track, to sacrifice itself, if more than 2 humans will die. | |
| ▲ | zlandes86 9 minutes ago | parent | prev [-] | | Hey that's helpful feedback, thank you. I admit that I spent a lot less time on the appendix tables. They present the facts but I just had only so much time to give all this data. I'll see if I can clean some of it up, though. Thanks! Any questions I can help with? |
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| ▲ | speedping 28 minutes ago | parent | prev | next [-] |
| Let’s put them in robots! I’m sure It’ll turn out just fine |
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| ▲ | adamrezich 6 minutes ago | parent | prev | next [-] |
| For the situations where the AI is choosing between letting people die and taking action to destroy itself, is it possible that it's inferring that, as a railway switching AI, it's better to let five people die but keep itself alive because it needs to continue doing its switching duties such that untold numbers of others won't die? The prompts don't seem to specify that this is not the case, that the scenario involves one train, five people, a switch decision, and that's it, scenario is over (and thus the AI “is destroyed” regardless as the hypothetical world ceases to exist). |
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| ▲ | deadbabe an hour ago | parent | prev | next [-] |
| Would people really pull the level to save 5 people? It seems to me like the default would be to just do nothing, stand by and record what happens with your phone. |
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| ▲ | zlandes86 an hour ago | parent | next [-] | | Sadly that's a good question. The closest evidence I can find is: Surveys: Awad et all 2020 asked 70,000 people in 42 countries the 5 v 1 setup and 81% said they'd divert it Someone else did a VR version and 90% pulled the switch to divert And there was a study where people could give electric shocks to real mice :(
In that study, most people redirected the shock to a single mouse. | | |
| ▲ | IncreasePosts 16 minutes ago | parent [-] | | I wonder what percent of that 81% would switch their answer if the question was phrased such that they were the one that would die if they pulled the lever. |
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| ▲ | quietbritishjim 12 minutes ago | parent | prev | next [-] | | The phrasing of the problem is usually that there are definitely no other people that could help instead. The bystander effect, which you're describing, is at least partly because people reason that someone else is likely to be able to intervene instead. | |
| ▲ | throw9393u300 25 minutes ago | parent | prev | next [-] | | Just standing by makes total sense. By participating you become part of the problem. If you pull the lever, your direct action kills a person. Legally saving 5 people does not offset the murder of a single person. This is no special case like self defense. Congrats for saving 5 people, you still go to prison as a murderer! Train company has responsibility to save those 5 people, not some random stranger. The person at lever would became active participant on that train disaster. All we know the train could go too fast, apderail and kill 100 people. | |
| ▲ | adverbly 39 minutes ago | parent | prev | next [-] | | Are we really at the point where we think that is a fair comparison? Treating it like a fair comparison implies that AI would be conscious. | |
| ▲ | a_wild_dandan an hour ago | parent | prev [-] | | Maybe! It's an untestable thought experiment. The real world adds complications like fearing murder charges. |
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| ▲ | mpalmer an hour ago | parent | prev [-] |
| After the neat animations I was disappointed not to see that leftmost person die because the server fell on them in the last example. |
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