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5 AI fears and how to address them
IT leaders implementing AI will encounter fears – many of them well-founded. The trick is to focus on these real-world concerns, not the time-traveling robot assassins
4. Fear: AI will lead to a loss of anonymity
McGehee points to a lesser-known concern, one that could become a higher-profile area of AI security: A loss of anonymity, or privacy, when that anonymity had been assumed as a given.
“It was previously a widely held belief among AI practitioners that once a machine learning model has been trained, its weights – the parameters that enable it to make predictions – do not contain any traceable representation of the training data,” McGehee says. “However, recent techniques have emerged that would enable nefarious actors to inspect a trained machine learning model and make meaningful deductions about individual data points used for training. This is concerning if an individual data point was a person, who wishes to remain anonymous.”
How to address it:
Again, by recognizing the legitimate issue underlying the fear, you can take steps to address it. Protecting the privacy or anonymity of data when necessary is an area where organizations can take proactive steps as part of their overall security strategy. It’s also an area of ongoing research and development in machine learning.
“While this is a valid fear, proper protection and encryption of the model weights can reduce the likelihood of them falling in the wrong hands, and creating new machine learning techniques that are not susceptible to this threat is an active area of research,” McGehee says.
5. Fear: AI will put me out of a job
We close with probably the most visible AI-related fear out there, one that bridges both present reality and more speculative scenarios. Most experts agree AI will impact a wide range of jobs, if it hasn’t already. In some cases, that will mean job loss. Pretending otherwise isn’t a strategy for mitigating fear.
But neither is embracing the doom-and-gloom scenarios. In the foreseeable future, increasing adoption of AI (and automation more broadly) is better compared to rise of the PC era, which came with similar worries. Research has found that the PC, while certainly impacting the workforce, created millions of jobs more than the number it displaced.
How to address it:
“Historically, new technologies don’t just automate jobs, but they make new jobs possible,” Nicholson says. “Think of all the jobs that are possible because of computers. New technologies usually need people to master them, support them and maintain them, and AI is no different.”
Proactively addressing this fear will be key to AI success in the business world, because otherwise people won’t get on board. And you’ll notice just about all of the above requires people not just getting on board but actively managing AI in their organizations.
“The crucial thing to understand is that work in the future will be a collaborative effort between people and machines,” Nicholson says. “Think about heavy machinery. It does a lot of labor that people used to do with, say, shovels. But that machinery still needs people to operate and maintain it. AI will be like that.”
[ Want lessons learned from CIOs applying AI? Get the full HBR Analytic Services report, An Executive’s Guide to Real-World AI. ]