This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: Artificial intelligence has taken over the role of assistant in many professional fields. Doctors, researchers and software developers rely on it in their work.
At worst, this results in a phenomenon described by researchers as deskilling: people's professional skills deteriorate as they outsource their tasks to AI. Kaisa Kärki, an academy research fellow in theoretical philosophy, discusses deskilling in a research article titled "Who is Responsible for Tackling Professional Deskilling?" The findings are published in the journal Human Affairs. "One of the problems with deskilling is that professionals have difficulty noticing it in their everyday lives, partly due to biases about AI reliance.
When we converse with large language models and they respond convincingly, it easily leads to overreliance. However, these models also make mistakes." Kärki gives health care as an example: A doctor relying on a large language model without noticing its inaccuracies can make a medical error. Who is responsible for the error?
"Generally, philosophical theories of responsibility have suggested that an agent should be held responsible for those actions she has done with awareness. The inconspicuous biases associated with AI use pose something of a challenge to these viewpoints: after all, we don't notice our own biases or, say, tendency to rely too much on AI. It's therefore unclear whether we can be held responsible for the insidious deterioration of our skills and the mistakes that will result." Kärki points out that, because deskilling easily goes unnoticed, individual professionals cannot be held responsible for related problems, at least not all of them.
The issue is societal and structural. Professional communities should identify the core skills of the profession that should be kept in human hands. For example, pilots practice responding to autopilot failures.
Other professions should consider the same: How will people fare without AI when necessary? "In medical education, it has already been argued that training in basic skills should include a stage where AI is not used. For instance, diagnostic reasoning is a skill central to medical practice, as is a general understanding of the field and the associated tasks." If AI is increasingly used in the workplace without considering the problems that deskilling causes, we may end up incapable of training new professionals without AI.
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