AI ethics is a hot topic these days, so you see all kinds of rhetoric zooming around. Complaints range from "the robots took my job" to "your computer system is just as biased as you are (you jerk)." Why aren't we talking about what makes ML/AI uniquely more dangerous than other technologies? The topics that come up in connection with AI ethics are vital, timely, and necessary. I just wish we wouldn't use the term AI ethics whenever it… isn't even about AI.

AI ethics is a hot topic these days, so you see all kinds of rhetoric zooming around. Complaints range from "the robots took my job" to "your computer system is just as biased as you are (you jerk)." Why aren't we talking about what makes ML/AI uniquely more dangerous than other technologies? The topics that come up in connection with AI ethics are vital, timely, and necessary. I just wish we wouldn't use the term AI ethics whenever it… isn't even about AI.

AI ethics is a hot topic these days, so you see all kinds of rhetoric zooming around. Complaints range from "the robots took my job" to "your computer system is just as biased as you are (you jerk)." Why aren't we talking about what makes ML/AI uniquely more dangerous than other technologies? The topics that come up in connection with AI ethics are vital, timely, and necessary. I just wish we wouldn't use the term AI ethics whenever it… isn't even about AI.

In December, Bloomberg reported that desperate demand for software engineers who know how to build artificial intelligence systems turned a previously low-key academic event into a recruiting frenzy more akin to the National Football League's draft day.

In December, Bloomberg reported that desperate demand for software engineers who know how to build artificial intelligence systems turned a previously low-key academic event "into a recruiting frenzy more akin to the National Football League's draft day." Meanwhile, the Tencent Research Institute released a report indicating that there are currently only 300,000 AI researchers and practitioners worldwide, but the demand is for millions. Earlier this month, Element AI set out to assess the AI talent pool. Based on LinkedIn postings, conference proceedings, and other data, the firm concluded that there are 22,000 PhD-educated researchers in the entire world who are capable of working in AI research and applications--but only 3,074 candidates currently looking for work. And this week, job search firm Indeed weighed in, reporting that demand for engineers with AI expertise has grown consistently over the past year and a half, and more than doubled over the past three years, however, job seeker interest in these positions has leveled off.

A massive school of fish in the ocean forms a fascinating natural sight. But for sharks, they become breakfast, lunch, and dinner. A vacationer with a drone camera captured a scene fit for a horror movie: a group of sharks, also known as a shiver, feasting on a school of menhaden fish off the coast of New York's Hamptons, one of the most famous vacation spots in the United States. Gregory Skomal, a senior scientist with Massachusetts Marine Fisheries, says sharks often feed on large schools like this, even off popular vacation spots like the Hamptons. "Sharks' travel patterns in the area are well documented, and include regularly feeding on large schools of fish," he said.

At a recent presentation in San Francisco, CB Insights CEO Anand Sanwal said half-jokingly that if startups want attention from investors, they should put phrases like "artificial intelligence" and "machine learning" in their pitch deck. While there's an argument to be made that AI is over-hyped as a technology, there's data to back up Sanwal's tongue-in-cheek advice: Mergers and acquisitions of AI startups increased by a factor of seven between 2011 and 2015, from five to more than 35 deals, according to the research firm. The increase runs against the grain of what the Silicon Valley Business Journal reported as an overall decline in the number of exits and deals of startups across fields starting in the second quarter of 2014. The poster child for the recent surge in interest in AI: Twitter's acquisition of machine learning startup Magic Pony Technology, announced earlier this month. If you look at the deal primarily as an "acquihire," Twitter is reportedly paying 13 million per machine-learning PhD.