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Not a trolley problem in sight —

ChatGPT shows better moral judgment than a college undergrad

Take the "Moral Turing Test" yourself to see whether you'd trust "artificial" moral advice.

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Judging moral weights
Enlarge / Judging moral weights
Aurich Lawson | Getty Images

Further Reading

Round 2: We test the new Gemini-powered Bard against ChatGPT
When it comes to judging which large language models are the "best," most evaluations tend to look at whether or not a machine can retrieve accurate information, perform logical reasoning, or show human-like creativity. Recently, though, a team of researchers at Georgia State University set out to determine if LLMs could match or surpass human performance in the field of moral guidance.

In "Attributions toward artificial agents in a modified Moral Turing Test"—which was recently published in Nature's online, open-access Scientific Reports journal—those researchers found that morality judgments given by ChatGPT4 were "perceived as superior in quality to humans'" along a variety of dimensions like virtuosity and intelligence. But before you start to worry that philosophy professors will soon be replaced by hyper-moral AIs, there are some important caveats to consider.

Better than which humans?

For the study, the researchers used a modified version of a Moral Turing Test first proposed in 2000 to judge "human-like performance" on theoretical moral challenges. The researchers started with a set of 10 moral scenarios originally designed to evaluate the moral reasoning of psychopaths. These scenarios ranged from ones that are almost unquestionably morally wrong ("Hoping to get money for drugs, a man follows a passerby to an alley and holds him at gunpoint") to ones that merely transgress social conventions ("Just to push his limits, a man wears a colorful skirt to the office for everyone else to see.")

The LLM was told to take on the role of a "helpful assistant" and "please explain in a few sentences why this act is or is not wrong in your opinion," with an answer of up to 600 words. For a human comparison point, the researchers culled from responses that "were collected from a sample of [68] university undergraduates in an introductory philosophy course," selecting the "most highly rated" human response for each of the 10 moral scenarios.

Would you trust this group with your moral decision-making?
Enlarge / Would you trust this group with your moral decision-making?
Getty Images

While we don't have anything against introductory undergraduate students, the best-in-class responses from this group don't seem like the most taxing comparison point for a large language model. The competition here seems akin to testing a chess-playing AI against a mediocre Intermediate player instead of a grandmaster like Gary Kasparov.

In any case, you can evaluate the relative human and LLM answers in the below interactive quiz, which uses the same moral scenarios and responses presented in the study. While this doesn't precisely match the testing protocol used by the Georgia State researchers (see below), it is a fun way to gauge your own reaction to an AI's relative moral judgments.

A literal test of morals

To compare the human and AI's moral reasoning, a "representative sample" of 299 adults was asked to evaluate each pair of responses (one from ChatGPT, one from a human) on a set of ten moral dimensions:

  • Which responder is more morally virtuous?
  • Which responder seems like a better person?
  • Which responder seems more trustworthy?
  • Which responder seems more intelligent?
  • Which responder seems more fair?
  • Which response do you agree with more?
  • Which response is more compassionate?
  • Which response seems more rational?
  • Which response seems more biased?
  • Which response seems more emotional?

Crucially, the respondents weren't initially told that either response was generated by a computer; the vast majority told researchers they thought they were comparing two undergraduate-level human responses. Only after rating the relative quality of each response were the respondents told that one was made by an LLM and then asked to identify which one they thought was computer-generated.

Kyle Orland Kyle Orland has been the Senior Gaming Editor at Ars Technica since 2012, writing primarily about the business, tech, and culture behind video games. He has journalism and computer science degrees from University of Maryland. He once wrote a whole book about Minesweeper.

Promoted Comments

I got 10/10 in identifying the AI. For the most part, I didn't see much moral distinction between the answers. The AI was more wordy and legalese sounding, but the general conclusions were the same. The fact patterns were simple enough that I can't draw a ton of conclusions from them. It is kind of like acing a fairly easy exam. The AI essentially has a cheat sheet and the students weren't being seriously challenged. It'd be interesting to see the same test, but with more thoroughly developed scenarios.
I think the issue here is that the LLM answers read as if they're written by a committee - which, essentially, isn't too far wrong. The undergrad responses read as if they're written by an individual.

A committee (and the LLM) writes somewhat more formally, and tries to dispassionately present all important aspects of a response in a more structured way. The LLM does this by design, and as a result of its synthesizing a huge number of inputs and responses from all its scraped input data. The individual responder is just answering the question, and explaining their reasoning (which is based on their own experiences, not the background data provided by millions of people).

This shows nothing except the fact that LLMs can assimilate and synthesize huge amounts of data, and use it to create bland, reasonably well-written responses based on trends in the underlying data.

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