NYU Data Science newsletter – September 2, 2016

GROUP CURATION: N/A

The optimism around modern technology lies in part in the belief that it’s a democratizing force—one that isn’t bound by the petty biases and prejudices that humans have learned over time. But for artificial intelligence, that’s a false hope, according to new research, and the reason is boneheadedly simple: Just as we learn our biases from the world around us, AI will learn its biases from us.

Employers are turning to mathematically modelled ways of sifting through job applications. Even when wrong, their verdicts seem beyond dispute – and they tend to punish the poor

The odds that artificial intelligence will enslave or eliminate humankind within the next decade or so are thankfully slim. So concludes a major report from Stanford University on the social and economic implications of artificial intelligence.

“The FTC’s complaint alleges that OMICS Group, Inc., along with two affiliated companies and their president and director, Srinubabu Gedela, claim that their journals follow rigorous peer-review practices and have editorial boards made up of prominent academics. In reality, many articles are published with little to no peer review and numerous individuals represented to be editors have not agreed to be affiliated with the journals.”

Technology giants like Google parent Alphabet Inc. and Amazon.com Inc. are jumping at the chance to help build the storage for the exchanges via their cloud services. That’s intensified resistance by Wall Street, since the new database, known as the Consolidated Audit Trail, or CAT, could include personal information such as names and addresses from more than 100 million customer accounts. Brokers and banks are worried about everything from data breaches to technology firms making one of their biggest inroads yet into the financial world.

Billionaire Thomas Siebel has raised $70 million for his data analytics startup C3 IoT as investor enthusiasm for the so-called Internet of Things begins to wane. … Customers include energy companies Enel SpA and Engie SA, as well as Cisco Systems Inc. C3 IoT won a $25 million contract this year to track energy use by the U.S. State Department at more than 22,000 facilities around the world.

What do you think your field will look like in 100 years? Speculating about the world a century from now may be too challenging, so what if instead a community took it upon itself to periodically assess its progress and potential nearer-term futures over time? How might such reflections influence the rate of progress, the types of problems that the field focuses on, the public perception of the work, or the ability to anticipate and address thorny ethical or policy questions?

Today, the first step on a project to answer these questions was taken with the release of the first report of the One Hundred Year Study on Artificial Intelligence (AI100).

In 2014, Stanford University launched the One Hundred Year Study, a long-term look into the future of artificial intelligence set to publish a paper every five years. … The report says evil AI isn’t what people need to anticipate—it’s the unintended consequences of otherwise helpful things AI gives, like the erosion of privacy or displacement of labor.

Browse report online by clicking on section headings in the ‘2016 Report’ box to the left.

“Five of the world’s largest tech companies are trying to create a standard of ethics around the creation of artificial intelligence.” … “The basic intention is clear: to ensure that A.I. research is focused on benefiting people, not hurting them.”

More on the Future of AI:

The Hype—and Hope—of Artificial Intelligence (August 26, The New Yorker, Om Malik)

What’s the future of Artificial Intelligence? (August 22, Raconteur Media, Sarah Allidina)

UC Berkeley launches Center for Human-Compatible Artificial Intelligence (August 29, University of California-Berkeley, Berkeley News)

G.E., the 124-Year-Old Software Start-Up (August 27, The New York Times, Steve Lohr)

The AI revolution is coming fast. But without a revolution in trust, it will fail (August 26, World Economic Forum, Marc Benioff)

Artificial Intelligence Will Be as Biased and Prejudiced as Its Human Creators (September 01, Pacific Standard, Nathan Collins)

How algorithms rule our working lives (September 01, The Guardian, Science, Cathy O’Neil)

Building human-assisted AI applications (August 25, O’Reilly Radar, Data Show Podcast, Ben Lorica,Adam Marcus)

As a cosmologist, some of the questions I hear most frequently after a lecture include: What lies beyond our universe? What is our universe expanding into? Will our universe expand forever? These are natural questions to ask. But there is an even deeper question at play here. Fundamentally what we really want to know is: Is there a boundary to our knowledge? Are there fundamental limits to science?

The answer, of course, is that we don’t know in advance. We won’t know if there is a limit to knowledge unless we try to get past it.

Dmitry Malioutov can’t say much about what he built.

As a research scientist at IBM, Malioutov spends part of his time building machine learning systems that solve difficult problems faced by IBM’s corporate clients. One such program was meant for a large insurance corporation. It was a challenging assignment, requiring a sophisticated algorithm. When it came time to describe the results to his client, though, there was a wrinkle. “We couldn’t explain the model to them because they didn’t have the training in machine learning.”

A 100-year project conceived by Microsoft Research’s Eric Horvitz to trace the impacts of artificial intelligence has issued its first report: a 28,000-word analysis looking at how AI technologies will affect urban life in 2030.

The bottom line? Put away those “Terminator” nightmares of a robot uprising, at least for the next 15 years – but get ready for technological disruptions that will make life a lot easier for many of us while forcing some of us out of our current jobs.

Deborah Estrin, Professor of Computer Science and Director at the Small Data Lab at Cornell Tech, chats about how “small data” — our digital patterns and interactions — can help physicians by creating a more meaningful representation of our personal health. [video, 17:52]

Houston, TX “The conference, organized by Moshe Vardi and co-sponsored by The Computing Research Association, will bring together members of computing, economics, and social sciences to discuss the possible impact of advances in computing on the future of work.” — Monday-Tuesday, December 5-6 at Rice University.

Deadline to submit posters is Monday, September 5.

“We are now accepting proposals for the fourth OptaPro Analytics Forum. The invite-only OptaPro Forum connects professional football clubs from around the globe with some of the most innovative analytical minds operating outside of clubs.” Date and venue have not been announced.

The deadline to submit proposals is Sunday, October 9.

Palo Alto, CA “This symposium aims to bridge the worlds of user experience design, service design, HCI, HRI and AI to discuss common challenges, identify key constituencies, and compare approaches to designing such systems.” — Monday-Wednesday, March 27–29 at Stanford University.

Deadline for submissions is Friday, October 28.

“In collaboration with the IEEE Signal Processing Society we propose a research data challenge for you to create a robust and scalable bird detection algorithm. We offer new datasets collected in real live bioacoustics monitoring projects, and an objective, standardised evaluation framework – and prizes for the strongest submissions.”

Deadline for submissions will be in December, exact date yet to be finalized.