Last summer, I went online to purchase a new inner tube for my bicycle tire. It was a one-time requirement that was fixed and done with. But then I noticed for weeks afterwards, I was being served online ads for bicycle tire inner tubes when surfing the web. The algorithm that picked up my data trail on shopping for inner tubes had predicted that I would have an ongoing, insatiable need for bicycle inner tubes! (I should have told it about my plans to try to avoid sharp objects laying on pavements.)
Such are the pitfalls with algorithms they can pick up some nuggets of data, and draw erroneous conclusions. I was thinking about this when INN colleague Chris McMahon recently posted the results of an intriguing survey, disclosing how underwriters are resistant to predictive analytics out of fears it will replace their jobs. While 45 percent report they are incorporating predictive analytics solutions into their companies, 24 percent of underwriters believe that their experience is more valuable than a predictive score when assessing risk, the survey finds. One in four underwriters believe predictive analytics will replace their jobs entirely.
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