Will ChatGPT have a positive or negative impact on labour market outcomes? On the positive side, ChatGPT and other large language models are seen by many as a 'force multiplier', increasing productivity. And more productive workers are generally paid more. On the negative side, ChatGPT and other large language models can complete many routine tasks that human workers currently do. Jobs that are predominantly made up of routine tasks are likely to be replaced, or heavily changed, by these models.
Does reading the latest (positive or negative) news story affect your views about whether the labour market impacts will be positive or negative overall? That is essentially the question addressed in this new article by Samir Huseynov (Auburn University), published in the Journal of Economic Psychology (ungated earlier version here). Huseynov focuses on the views of students, because:
Today’s students face the possibility that AI may partially or entirely overtake their anticipated jobs upon graduation. This challenging scenario could affect expected salaries, pushing students to drop out or switch to ‘‘safer’’ majors to secure future earnings... However, it is also possible that AI technologies could potentially enhance future workers’ productivity and earning potential... The discourse on AI, both optimistic and pessimistic, could shape students’ educational choices, leading to career-defining decisions.
Huseynov used a survey experiment, where student research participants were first asked about their beliefs about future labour market outcomes for themselves (and for the median student in their studying the same major). They then read either an optimistic ('GoodNews') story about the potential impacts of ChatGPT and other AI tools, or a pessimistic ('BadNews') story, and were then asked again about those beliefs. Huseynov then tests whether the good news or bad news affects students' beliefs. Based on a sample of 716 US students, they find that:
...exposure to both optimistic and pessimistic AI ChatGPT discussions leads students to revise down their beliefs about ranking in the top 50% of the post-graduation earning distribution. The BadNews treatment, however, induces a more significant revision than the GoodNews condition. Interestingly, neither condition influences students’ reported expected earnings...
In terms of the mean value, students rated themselves as 10 percent less likely to be in the top half of the earnings distribution after receiving the BadNews treatment, and 4 percent less likely after receiving the GoodNews treatment. The effects were smaller when asked about the median student - 8 percent less likely in the BadNews treatment, but 3 percent more likely in the GoodNews treatment. However, it is worth noting that both GoodNews treatment effects were statistically insignificant. Interestingly, Huseynov also found that the effect of the BadNews treatment was particularly larger for female students and for students in non-STEM majors.
It is interesting that reading a single story about the potential impacts of ChatGPT and other AI tools would have an effect on students' beliefs. It would be more interesting to know whether the results were related to students' prior experience with generative AI. Huseynov reports that:
Nearly half of our subjects have never used ChatGPT or only used it a few times.
I thought that was surprising. However, I guess the students in the sample could have used other generative AI tools that they weren't asked about. We do perhaps get some sense of whether prior familiarity with generative AI affects perceptions, because the effects for students in STEM majors (who I guess are more likely to have encountered or used generative AI before) are not statistically significant.
If students' only understanding of the impacts of generative AI on their labour market prospects comes from doomscrolling through pessimistic perspectives online, it should be no surprise that students will become concerned about their future prospects. This reinforces that giving students experience in using generative AI in an intentional way will be helpful, and not just for their learning. It will also help students to understand their future potential and how they can work alongside generative AI. It isn't all bad news for current students, and they need to recognise that.
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