SEPTEMBER 20198IN MY OPINIONThe last time I wrote about artificial intelligence (AI) in the insurance industry was in 2017. I discussed the spectacular possibilities of intelligent automated interactions, personalized service for complex issues, and new distribution channels. Looking back on the article, I feel some of the same optimism I expressed two years ago--but I also see my naivetéat the time. In some ways, the promise of machine learning appears even more spectacular today. We've seen remarkable achievements in game-playing in systems like AlphaZero and AlphaStar, realistic pictures of people "imagined" by generative adversarial networks and the image processing power of driverless cars and trucks. These remarkable technologies inspire a wealth of ideas for greater efficiency and effectiveness in the workplace.In the insurance industry, in particular, AI applications are becoming increasingly common; it is rare to find an insurance startup that does not use the words "machine learning" in its pitch deck. However, I am seldom impressed by these uses of technology. The reality is that AI is readily available to any startup. Google's decision to open-source TensorFlow--arguably one the most transformative decisions of the software age--made the power of machine learning available to anyone with some knowledge of computer programming. It is not surprising that new businesses are capitalizing on the availability of this technology and the excitement that surrounds it. Perhaps even more importantly, the ideas I hear for AI applications in insurance rarely take into account the current state of affairs on the ground. In my Artificial Intelligence: Empowering People--Not MachinesBy Michael Freilich, EVP & CTO, Renaissance Alliance
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