A recent survey by Pluralsight revealed that 79% of tech workers and 91% of executives in the US and UK admit to faking their AI knowledge. Despite this dishonesty, the majority believe they possess the necessary AI skills for their roles, often due to the Dunning-Kruger effect. Furthermore, while 95% of executives recognize the importance of AI skills for job security, many employees fear being labeled as "lazy" for using AI tools, leading to increased use of "shadow AI" which poses security risks. Fortunately, half of companies are beginning to offer AI training to bridge this knowledge gap.
One potential explanation for this gap is the Dunning-Kruger effect - a well-researched phenomenon where a person's lack of knowledge and skill in a specific area causes them to greatly overestimate their competence.
If this is the case, then it's likely that a large percentage of the workforce believe they have greater AI skills than they do because they lack enough knowledge about AI to 'know what they don't know'.
With this stigma, workers often use AI tools for work projects without disclosing their use to avoid being labeled lazy, leading to potential security risks.
Despite admitting to faking AI knowledge, nine-in-ten tech workers and execs believe they had the necessary skills to use AI in their day-to-day roles.
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