You can also access this resource, and many others, in Issue 368 of my Talent Edge Weekly newsletter.
In a recent post, I shared a 52-page report from IBM Institute for Business Value on five priority areas Chief HR Officers and their teams can focus on to turn AI-created capacity into business growth. One of the areas I expanded on was preventing skill erosion, which is the gradual weakening of skills people already have when AI reduces their opportunities to practice them. One example is an analyst who relies on AI to summarize data and gradually loses the habit of asking what is missing or misleading. A new study provides some insight. In a randomized experiment with 240 preservice teachers, some participants made their own judgment before using an AI recommendation, while others saw the AI recommendation before deciding. When the AI advice was wrong, participants who had made their own judgment first chose the answer experts judged correct 53.5% of the time. Participants who saw the AI recommendation first chose it only 37.3% of the time, a statistically significant difference. Despite the limitations of the study (e.g., participants were student teachers responding to hypothetical scenarios, and a follow-up test showed no lasting effect), it suggests that people who form their own view before consulting AI are less likely to follow misleading advice. For practical strategies to reduce skill erosion while still gaining the benefits of AI, I am resharing my post on the BCG article When Everyone Uses AI, Companies Risk Losing Critical Skills.
