Unless you’ve been stuck under a rock, you’ve probably come to the conclusion that artificial intelligence–really machine learning, is going to take over the world. Elon Musk and Mark Zuckerberg have recently sparred each other over the risks and benefits of artificial intelligence.

Musk, founder of Tesla and SpaceX, has a well known belief that the future looks more like Ridley Scott’s famous cult science fiction film Blade Runner than the amazing Disney Word gee-whiz future in the marketing brochure. His company SpaceX’s mission is to make life on Mars possible for when Earth is no longer inhabitable. “I keep sounding the alarm bell,” he recently told attendees at a National Governors Association meeting. “But until people see robots going down the street killing people, they don’t know how to react.”

Elon Musk & Mark Zuckerberg

Mark Zuckerberg hit back in a Facebook Live event, calling Musk a “naysayer”. Going even further, he said “in some ways I actually think it is pretty irresponsible.” Facebook, Google, Salesforce, IBM and any major tech player of note are all betting big on the sunny-side scenario. But as with all things, some see the porridge as too hot, others too cold. The truth is always somewhere in the middle and the middle is a place where the raisins and brown sugar are best.

One such place in favor of the value of machine learning is the annual Data Science Bowl co-sponsored by Booz Allen and Kaggle (now owned by Google). The Data Science Bowl brings together data scientists, technologists, domain experts, and organizations to take on some the world’s toughest challenges challenges with data and technology.

The 2015 contest asked data scientists from around the world to examine over 100,000 underwater images to assess ocean health on a massive scale. The winning submission beat the state of the art by more than 10%. In 2016, contest participants applied analytics to cardiology. The winning team weren’t doctors or data scientists, they were hedge fund traders. This year’s contest winners created an algorithm that dramatically reduces the false positive rate in the diagnosis of lung cancer, and again the winners were not physicians, rather they were data scientists.

Quantitative insight is increasingly creating new product opportunities and opportunities for growth. New techniques, multidisciplinary approaches, and the dramatic increase of compute and storage bring new horizons. As with all things, new technology presents risk. Elon Musk isn’t wrong to think about the ethics of these powerful tools. But today, most enterprises are new to the power of data, data science, and machine learning techniques. While Doctor Evil may be lurking out there somewhere in a distant future, it’s clear that today these techniques will increasingly drive innovation, and so enterprises must master them.