Over the past eight years, we have shared ideas ranging from the ocean’s power, to the musical evolution of the Erhu, to urban beekeeping, and even the counterfeit drug trade. Last year, we honed our focus to artificial intelligence and machine learning, and the potential in this space captivated our collective imagination. We just weren’t ready to let it go yet.

So we dove even deeper into AI and ML this year. We heard about filmmaking with a program that named itself Benjamin, machines that could fix themselves to adapt to their environment, emerging legal and ethical issues, and much, much more.

The entire event was livestreamed on our website (https://tedxboston.org/) for free. We encouraged people to get together with friends, family, and colleagues to watch as a group, or organize a meet-up.

The Institute of Contemporary Art
25 Harbor Shore Drive
Boston, Massachusetts, 02210
United States

Barbara Engelhardt

Barbara Engelhardt is an assistant professor in the Computer Science Department at Princeton University since 2014. She graduated from Stanford University and received her Ph.D. from the University of California, Berkeley, advised by Professor Michael Jordan. She did postdoctoral research at the University of Chicago, working with Professor Matthew Stephens, and three years at Duke University as an assistant professor. Interspersed among her academic experiences, she spent two years working at the Jet Propulsion Laboratory, a summer at Google Research, and a year at 23andMe, a DNA ancestry service. Professor Engelhardt received an NSF Graduate Research Fellowship, the Google Anita Borg Memorial Scholarship, the Walter M. Fitch Prize from the Society for Molecular Biology and Evolution, an NIH NHGRI K99/R00 Pathway to Independence Award, and the Sloan Faculty Fellowship. Professor Engelhardt is currently a PI on the Genotype-Tissue Expression (GTEx) Consortium. Her research interests involve statistical models and methods for analysis of high-dimensional data, with a goal of understanding the underlying biological mechanisms of complex phenotypes and human diseases.

Claudia Perlich

Claudia Perlich leads the machine learning efforts that power Dstillery’s digital intelligence for marketers and media companies. With more than 50 published scientific articles, she is a widely acclaimed expert on big data and machine learning applications, and an active speaker at data science and marketing conferences around the world. Claudia is the past winner of the Advertising Research Foundation’s (ARF) Grand Innovation Award and has been selected for Crain’s New York’s 40 Under 40 list, Wired Magazine’s Smart List, and Fast Company’s 100 Most Creative People. Claudia holds multiple patents in machine learning. She has won many data mining competitions and awards at Knowledge Discovery and Data Mining (KDD) conferences, and served as the organization’s General Chair in 2014. Prior to joining Dstillery in 2010, Claudia worked at IBM’s Watson Research Center, focusing on data analytics and machine learning. She holds a PhD in Information Systems from New York University (where she continues to teach at the Stern School of Business), and an MA in Computer Science from the University of Colorado.

Finale Doshi-Velez

Finale Doshi-Velez is an Assistant Professor of Computer Science at the Harvard Paulson School of Engineering and Applied Sciences. Her interests lie at the intersection of machine learning and healthcare. She completed her PhD at MIT, her postdoc at Harvard Medical School, and is a Marshall Scholar.

Jim Bellingham

Jim Bellingham is a pioneer in the development of autonomous marine robots. He has led and participated in research expeditions around the world from the Arctic to the Antarctic. He is the founding Director of the Center of Marine Robotics at the Woods Hole Oceanographic Institution, founded the Autonomous Underwater Vehicles Laboratory at MIT, and co-founded Bluefin Robotics. He serves on numerous advisory committees and boards, including the Secretary of the Navy Advisory Panel, several National Academies studies and he Chairs the Naval Research Advisory Committee. Jim?s awards include the Lockheed Martin Award for Ocean Science and Engineering, and the MIT Fourteenth Robert Bruce Wallace lecturer. Jim received an S.B., S.M., and Ph.D. in physics from the Massachusetts Institute of Technology.

Kenneth Anderson

Kenneth Anderson teaches law at Washington College of Law, American University in Washington DC. He comes to law, regulation, and ethics of emerging technologies from a background in the international law of war and weapons, and has written extensively on drone warfare and, most recently, emerging autonomous weapons. While a visiting professor at Harvard Law School in 2016, he served as moderator of an interdisciplinary reading group on law, regulation and emerging automation and robotics technology under the auspices of the Berkman Klein Center for Internet and Society at Harvard University. He also serves as book review editor of the national security and law website, Lawfareblog.com; his most recent book, with Lawfare Editor-in-Chief Benjamin Wittes, is “Speaking the Law: The Obama Administration’s Addresses on National Security and Law.”

Michael Littman

Michael L. Littman is a Computer Science Professor at Brown University, studying machine learning and decision making under uncertainty. He is co-director of Brown’s Humanity Centered Robotics Initiative, a Fellow of the Association for the Advancement of Artificial Intelligence, and has earned multiple awards for his teaching and research. An enthusiastic performer, Michael has had roles in numerous community theater productions and a TV commercial.

Oscar Sharp

Oscar is a BAFTA-nominated filmmaker and Screen International Star of Tomorrow. His films have received many prizes internationally, from the likes of Joss Whedon, Guillermo del Toro and Sir Alan Parker. Awarded a Fulbright and a BAFTA scholarship, he attended at NYU Graduate Film, alma mater of Scorsese and Ang Lee, studying under professors Todd Solondz, Spike Lee and Darren Aronofsky. In 2015 his short film The Kármán Line was nominated for a BAFTA and released by The New Yorker. He signed a one-picture blind deal with Tobey Maguire's Material Pictures. In spring of 2016, he and his technologist collaborator Ross Goodwin created Benjamin, the world's first artificially-intelligent screenwriter, and shot the first purely AI-written film, Sunspring starring Thomas Middleditch. In 2017 they followed this up with It's No Game starring David Hasselhoff and Sarah Hay. In summer 2016, 20th Century Fox acquired Ben Mezrich's upcoming book Woolly: The True Story of the De-Extinction of One of History’s Most Iconic Creatures for Oscar to adapt for the screen. He is also developing feature films with Echo Lake Entertainment and SUMS. He is represented in the USA by United Talent Agency and in the UK by Independent Talent.

Ross Goodwin

Ross Goodwin is an artist, creative technologist, hacker, gonzo data scientist, and former White House ghostwriter. He employs machine learning, natural language processing, and other computational tools to realize new forms and interfaces for written language. His projects — from word.camera, a camera that expressively narrates photographs in real time using artificial neural networks, to Sunspring (with Oscar Sharp, starring Thomas Middleditch), the world’s first film created from an AI-written screenplay — have earned international acclaim. Goodwin’s work has been featured in the New York Times, the Chicago Tribune, NPR, CBS News, the Financial Times, the Irish Times, El Pais, CBC Radio Canada, RTE Radio Ireland, ABC Radio Australia, Deutschlandradio, the Guardian, the Globe and Mail, Ars Technica, VICE Motherboard, Gizmoto, Engadget, TechCrunch, CNET, Forbes, Slate, FiveThirtyEight, Fast Company, the Huffington Post, Mashable, Fusion, Quartz, PetaPixel, and other publications. He has exhibited or spoken at Science Gallery Dublin, the International Documentary Film Festival (IDFA) DocLab in Amsterdam, the TriBeCa Film Festival Interactive Showcase in New York, the International Center of Photography (ICP) in New York, Phi Centre in Montreal, Gray Area in San Francisco, the MIT Media Lab, Maker Faire, GitHub Universe, the NIPS machine learning conference, Molasses Books in Bushwick, and other venues. Goodwin earned his undergraduate degree in Economics from MIT in 2009, and his graduate degree from NYU ITP in May 2016.

Shea Rose

Shea Rose has held a host of titles over the course of her career: singer, songwriter, and music curator, among others. Her music, influenced by R&B, soul, hip-hop, rock, and folk, speaks to personal and cultural issues. Rose’s voice—both musical style and the message she speaks—has grown and matured dramatically since graduating from Berklee College of Music. This year, she released the D.T.M.A. (Dance This Mess Around) EP. Prior to releasing D.T.M.A., Rose recorded a cover of Sinéad O’Connor’s “Black Boys on Mopeds” in 2016 at a time when the loss of young, black lives at the hands of the police was becoming increasingly publicized, and awareness and anger were swelling. Rose is also well-known in the fashion community, gracing the covers of Boston Globe magazine’s annual style issue, Improper Bostonian, Exhale, and Performer magazines, and featured in brand campaigns for CoverGirl, Tory Burch, Puma, Plndr and Converse. Recently, Rose has been curating the RISE Music Series at the Isabella Stewart Gardner Museum in Boston with Composer/Producer Simone Scazzocchio. RISE features local, national, and international aspiring and established artists from the realms of pop, rock, and hip-hop. Later this year, she will release music videos for “Black Boys on Mopeds” and the title track of her latest EP, “D.T.M.A. (Dance This Mess Around).” Dig Boston calls Rose’s version of “D.T.M.A.” “a biting reimagination of the B-52’s carefree club tune” and hails the “exceptional amount of artistry required to take an ’80s groove track and turn it into a 2017 social justice anthem.” Find more about Shea Rose at www.shearose.com, and listen to her music on Bandcamp, iTunes, or Spotify.

Ziad Obermeyer

Ziad Obermeyer is an Assistant Professor at Harvard Medical School and a practicing emergency physician at the Brigham and Women’s Hospital, both in Boston. His work uses machine learning to solve critical problems in clinical medicine. As patients get older and more complex, the volume of health data grows exponentially, and it becomes harder and harder for the human mind to keep up. Dr. Obermeyer’s work is focused on applying machine learning to find hidden signals in health data, and help doctors make better decisions and drive innovations in clinical research. He is a recipient of an Early Independence Award from the NIH Common Fund, and a faculty affiliate at ideas42, Ariadne Labs, the Institute for Quantitative Social Science at Harvard University. He holds an A.B. (magna cum laude) from Harvard and an M.Phil. from Cambridge, and worked as a consultant at McKinsey & Co. in Geneva, New Jersey, and Tokyo, before returning to Harvard for his M.D (magna cum laude).