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The hidden cost of using AI at work: You may be training yourself to be average

The Hidden Cost of Using AI at Work: You May Be Training Yourself to Be Average

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If you find yourself relying on AI a lot, beware of ‘cognitive surrender.’ Instead, approach AI this way.

If you find yourself relying on AI a lot, beware of ‘cognitive surrender.’ Instead, approach AI this way.

AI gets a lot of flack. Some of it is warranted, some of it not so much. Sitting at your desk, it’s easy to brush off much AI criticism as overblown, as you busily type prompts into ChatGPT to help speed your workday along. But a new piece of research may concern you on a more personal level—it says that people who use AI at work may be becoming “boring.” And, worse, the habit may make you so complacent about your work duties that in the long term you actually harm your career prospects—a worrisome problem given the warnings some people make about AI and the future of work.

The research comes from Sandra Matz, a professor at Columbia Business School who spoke to CNBC about her studies. The threat from AI toward people’s jobs may be much more immediate than some speculative near future date when the AI is smart enough to replace you, Matz thinks. Instead, the concern is about stagnating in your duties and falling into mediocrity. Matz thinks it’s simple: workers outsourcing their critical thinking tasks or creative duties create a “real risk of gradually falling behind and becoming complacent,” she told CNBC. AI is a crutch in this scenario: turn to it too often, and you risk your own skills withering. 

The concerns about AI and mediocrity, or becoming boring, are subtle. AI tools tend toward obvious or safe responses to queries, Matz noted, meaning that if you’re relying on it to solve a problem in the same way someone in a rival company halfway round the world is using it, you risk becoming “just like everyone else,” Matz said. The more employees start consulting AI when developing ideas, the bigger the risk that independent thinking gives way to “algorithmic consensus,” Matz says.

To complement Matz’ theories, Americus Reed II, professor of marketing at the Wharton School of Business, also explained his work on the topic. He described the risk of over-relying on AI as “cognitive surrender.” The risk is that your own skills fade as you use AI more and more, with particular harm to someone early in their career when they’d traditionally be learning fast, and honing their skills through trial and error.

So how can you use AI and avoid becoming mediocre?

Reed suggested that workers try to “remember that adopting AI is not the same as outsourcing your identity.” His view is that workers should be conscious about when and where they deploy AI tools, being careful to rely on their own uniquely human intuition when they can.

Matz explained that she thinks workers should be careful about swapping in AI for themselves in different ways, such as relying on digital twins, particularly when it comes to interacting with real humans you know. That way you risk writing yourself out of the equation, which could leave you wondering about what value you bring, and if indeed there’s any real communication going on. 

As a company leader or team manager, you can set a more concrete example by clearly defining the boundaries of where and when your staff can and cannot use AI.

Asking for hand-written work could be one trick. 

An expert writing at the BBC agrees with the hand-written idea. Asking your workers to produce project plans that they’ve hand-written—not typed-out—may be a great way to ensure this kind of habit. Running truly old-school brainstorming sessions with whiteboards and sticky notes, where using AI or even Google is banned, could be another great way to kick off projects and cement the value of human creativity into your workers’ minds.

Showing that you value real human creativity is another: you could tell your workers you’re happy for them to use AI as a touchstone, but not for creating the whole solution. That’s because while mediocrity and skill erosion is an ephemeral personal risk for each of your workers and their long term prospects, for you it’s a more concrete problem: your workforce’s over reliance on AI solutions, with their tendency to normalize answers to problems, may mean you risk being unable to out-innovate your competition when tackling the same kind of marketplace problem. 

Essentially, this is a great chance for you to lead by example. As AI becomes more sophisticated, the unique quirks of the human mind will become more valuable. Making sure these qualities are valued and demonstrated in your company could become an important way to beat the ‘bots

This post originally appeared at inc.com.

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