Data Science and AI Lab

The Data Science and AI Lab is interested in modeling, simulating, and analyzing social phenomena using computational methods. The research involves analyzing datasets on diverse topics such as scientific collaborations, police checkpoints, transportation patterns, energy consumption rates, AI ethics, human-bot interactions, and algorithmic privacy.

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Researchers

Talal Rahwan

Principal Investigator and Associate Professor of Computer Science

Team Members

Name	Title
Marcin Waniek	Postdoctoral Associate
Bedoor AlShebli	Postdoctoral Associate
Abbas Raza Ali	Postdoctoral Associate
Sid Benabderrahmane	Research Associate
Russell Coke	Research Engineer
Fengyuan Liu	PhD Student
Maria Sahakyan	PhD Student

Selected Publications

Raman, B AlShebli, M Waniek, T Rahwan, JCH Peng (2020). "How weaponizing disinformation can bring down a city's power grid". PLOS ONE. Media coverage: Fast Company.

F. Ishowo-Oloko, J. Bonnefon, Z. Soroye, J. Crandall, I. Rahwan, T. Rahwan. "Behavioural evidence for a transparency–efficiency tradeoff in human–machine cooperation.". Nature Machine Intelligence, 1, no. 11 (2019): 517-521. (November Cover). Media coverage: Boston Globe, Nature Middle East, Khaleej Times, WIRED, Psychology Today, New Statesman, Scientific American.

M. Waniek, K. Zhou, Y. Vorobeychik, E. Moro, T. Michalak, T. Rahwan (2019). "How to Hide One’s Relationships from Link Prediction Algorithms". Scientific Reports, 9(1), 1-10. Media coverage: El País Technología.

B. AlShebli, T. Rahwan, W. Woon. “The preeminence of ethnic diversity in scientific collaboration”. Nature Communications, 9 5163 (2018). Media coverage: Nature News, Physics World.

M. Waniek, T. Michalak, M. Wooldridge, T. Rahwan. "Hiding individuals and communities in a social network.". Nature Human Behaviour, 2, no. 2 (2018): 139. Media coverage: Vice's Motherboard.

Contact Us

Talal Rahwan
Principal Investigator
Email: talal.rahwan@nyu.edu

Media Coverage

Research conducted at the Data Science and AI Lab was covered by major news outlets worldwide.

Hackers could take down the power grid—by telling everyone it was a good time to turn things on
As power companies learn to manage demand by offering incentives to get people to use appliances or charge cars at off-peak hours, they also leave themselves open to some simple sabotage.
Fast Company | August 21, 2020

Ethics, efficiency, and artificial intelligence
Should we allow machines to impersonate humans?
Boston Globe | January 30, 2020

People Don’t Learn to Trust Bots
AI elicits better cooperation through deception.
Scientific American | February 1, 2020

Human bias burdens bots
People cooperate less when they believe they are interacting with a bot.
Nature Middle East | November 22, 2019

Can Artificial Intelligence Increase Our Morality?
Just as we define our technologies, they define us.
Psychology Today | December 9, 2019

Cómo engañar al algoritmo y evitar que Facebook sepa a quién conoces
Una nueva investigación revela un truco para confundir a una función clave de las redes sociales.
El País | September 19, 2019

These labs are remarkably diverse — here’s why they’re winning at science
Being inclusive gives research groups a competitive edge. It also happens to be the right thing to do.
Nature | June 6, 2018

Ethnic diversity boosts scientific impact
The impact of scientific work is boosted when it features co-authors who have a diverse range of ethnicities.
Physics World | March 21, 2018

How to Hide Within a Social Network
New graph theory research offers good news for privacy advocates, bad news for the FBI.
Motherboard | January 30, 2018