The next target for hackers

I was speaking recently with Eric Siegel, PhD about machine learning and predictive analytics, specifically what he likes to call The Power to Predict Who Will Click, Buy, Lie, or Die. In that conversation, we talked about the black box that lies at the heart of many company’s AI deployments. But we didn’t talk about the security considerations that stem from this situation: that is, it’s not just a company’s computers that are vulnerable to hackers. It’s the AI running on those computers, that’s making use of data.

Every day, we hear about companies deploying applications with the dreadful acronym AI to provide the best customer service or something. They talk up their solution, the most advanced solution, with the best AI that money can buy. And of course all that AI that is their big differentiator is a highly guarded secret. It’s also a source of vulnerabilities.

And this is where it gets tricky. In order to build your analytics, you need data. You need to take the data and build models. Where can you get the data? If you are a mature organization, the chances are that you already sit on a lot of it. In the case of a startup, most likely you go on the Internet and find publicly available data sources like this one, download it and start training and building your models.