Oren Etzioni is an AI researcher, while his father Amitai Etzioni was one of the most important intellectual voices in the U.S. prior to his recent passing. In Amitai Etzioni's final interview, he and his son discuss the dangers of artificial intelligence.

The Hoover Institution's Condoleezza Rice and HAI Co-Director Fei-Fei Li discuss AI ethics, technology advances, and the...

Editor's note: Etzioni has answered this question in the form of a hypothetical news story from the future. BREAKING: Food company X and technology company Y have officially completed their merger into a juggernaut computer manufacturer--lab-grown computers with super-human intelligence. In the early 2000s, scientists speculated that cellular DNA offered transformative opportunities for computer memory. Likewise, companies began to investigate high-bandwidth links between our human neurons and artificial neural networks. Proceeding in secrecy, in offshore locations, ethical concerns were quickly shunted and a race ensued toward growing an artificial brain in a lab; a genuine "brain in a vat."

For more depth, we recommend this insightful review article by UW Prof. Pedro Domingos: A Few Useful Things to Know about Machine Learning

Artificial-intelligence researcher Oren Etzioni has suggestions for keeping enough AI faculty members around to train the next generation.Credit: Bret Hartman/TED Oren Etzioni is chief executive of the non-profit Allen Institute for Artificial Intelligence (AI2) in Seattle, Washington, and is on leave from the nearby University of Washington. He offers some recommendations for how to stem the outflow of artificial-intelligence (AI) researchers from academia to industry -- a loss that is damaging academia's ability to teach incoming undergraduates. It is a very sizeable trend for fresh PhD graduates and faculty members. In machine learning, you see some significant departures. Industry compensation packages are highly variable.

Question answering (QA) has been a longstanding challenge in the field of artificial intelligence. Numerous research works have pushed forward techniques for building QA systems. Many existing approaches achieve high performance on benchmark datasets. However, most of the questions in those datasets only require surface-level reasoning, and do not reveal the full-scale complexity and challenge of the question answering problem. Recently, the AI2 Reasoning Challenge (ARC) has been proposed [Clark et al., 2018], which is designed to pose a challenge to the QA community. On the ARC Challenge Set, several state-of-the-art QA systems, including leading neural models from the well-known SQuAD and SNLI tasks, only perform slightly better than the random baseline. This striking observation has demonstrated that QA is still far from being solved. Why it is so difficult to answer the questions in the ARC Challenge Set? 1) ARC consists of natural science questions, namely questions authored for human exams. All of these questions are drawn from real exams; 2) In order to encourage progress on hard questions, a Challenge Set has been partitioned from ARC.

This article appears in print in the April 2018 issue. Artificial intelligence (AI) promises to revolutionize virtually every sector of the economy --from automobile manufacturing to health care delivery to building maintenance. And the Seattle region's prominent role in cloud computing -- a key driver in AI's widespread use -- means the technology is becoming as prominent here as damp shoes. Indisputably, AI has quietly and inexorably made its way into our daily lives. "We see it in a lot of the things that require speech recognition," says Oren Etzioni, CEO of the Paul Allen Institute for Artificial Intelligence.

"Common sense" is a phrase everyone hears at one time or another, usually from an angry bystander who think you don't have any. "Humans use common sense to fill in the gaps of any question they are posed, delivering answers within an understood but non-explicit context," Swapna Krishna wrote in Engadget. Add a few years of developmental growth in the young child, and he or she acquires common sense but AI has problems. Calling out the challenge in AI research is Dr. Oren Etzioni, researcher and professor, who leads the Allen Institute for Artificial Intelligence, or AI2, in Seattle, Washington. To get at the fluidity that people have, their natural ability to move from one thing to the next, the programs need what every ten year old has in spades, he said, and that is called common sense---a set of facts, heuristics, observations, all the things that we can bring to the table, but the computer does not.

Byron Reese: This is Voices in AI, brought to you by Gigaom. Today, our guest is Oren Etzioni. He's a professor of computer science who founded and ran University of Washington's Turing Center. And since 2013, he's been the CEO of the Allen Institute for Artificial Intelligence. The Institute investigates problems in data mining, natural language processing, and the semantic web. And if all of that weren't enough to keep a person busy, he's also a venture partner at the Madrona Venture Group. Business Insider called him, quote: "The most successful entrepreneur you've never heard of." Welcome to the show, Oren. Oren Etzioni: Thank you, and thanks for the kind introduction. I think the key emphasis there would be, "you've never heard of." Well, I've heard of you, and I've followed your work and the Allen Institute's as well. And let's start, if that's Okay, let's start there. So if you would just start off by telling us a bit about the Allen Institute, and then I would love to go through the four projects that you feature prominently on the website. And just talk about each one; they're all really interesting. The Allen Institute for AI is really Paul Allen's brainchild. He's had a passion for AI for decades, and he's founded a series of institutes--scientific institutes--in Seattle, which were modeled after the Allen Institute for Brain Science, which has been very successful running since 2003. We were launched as a nonprofit on January 1, 2014, and it's a great honor to serve as CEO. Our mission is AI for the common good, and as you mentioned, we have four projects that I'm really excited about.

One of the activities of AI-Ethics.com is to monitor and report on the work of all groups that are writing draft principles to govern the future legal regulation of Artificial Intelligence. Many have been proposed to date. Click here to go to the AI-Ethics Draft Principles page. If you know of a group that has articulated draft principles not reported on our page, please let me know. At this point all of the proposed principles are works in progress.