Alessandro Acquisti is Trustees Professor of Information Technology and Public Policy at Carnegie Mellon University's Heinz College, and the co-director of the CMU Center for Behavioral Decision Research (CBDR). He is a fellow of the Ponemon Institute and a member of Carnegie Mellon CyLab and the CyLab Usability, Privacy, and Security (CUPS) lab.
Alessandro’s research investigates the economics and behavioral economics of privacy, and privacy in online social networks. His studies have been published in leading journals across diverse disciplines (such as Proceedings of the National Academy of Science, Journal of Consumer Research, Marketing Science, Information Systems Research, Journal of Comparative Economics, ACM Transactions on the Internet), as well as edited books, book chapters, conference proceedings, and numerous international keynotes.
Alessandro has been the recipient of the PET Award for Outstanding Research in Privacy Enhancing Technologies, the IBM Best Academic Privacy Faculty Award, the Heinz College’s School of Information Teaching Excellent Award, and various best paper awards. He has been awarded research grants from the National Science Foundation, Transcoop Foundation, Google, and Microsoft. He has been invited to be part of the Federal Trade Commission’s Privacy Roundtables and to co-chair the Cyber-Economics Track at the "National Cyber Leap Year Summit,” as part of the NITRD Program under guidance from the White House Office of Science and Technology Policy. He is a member of the National Academy of Science’s Committee on Public Response to Alerts and Warnings Using Social Media and Associated Privacy Considerations.
Prior to joining CMU Faculty, Alessandro Acquisti interned at the Xerox PARC labs in Palo Alto, CA and at RIACS, NASA Ames Research Center, in Mountain View, CA.
Alessandro’s findings have been featured in media outlets including the Economist, NPR, the New York Times and the NYT Magazine, the Wall Street Journal, the Washington Post, CNN, the New Scientist, the MIT Technology Review, and others. His 2009 study on the predictability of Social Security numbers was featured in the “Year in Ideas” issue of the NYT Magazine (two years after the publication of the study, the Social Security Administration changed the assignment scheme of Social Security numbers).
Alessandro holds a PhD from UC Berkeley and Master Degrees from UC Berkeley, the London School of Economics, and Trinity College Dublin.
Areas of Expertise (7)
Economics of Privacy
Media Appearances (5)
If It’s Advertised to You Online, You Probably Shouldn’t Buy It. Here’s Why.
New York Times print
Last year, Alessandro Acquisti and a team of researchers at Carnegie Mellon and Virginia Tech presented a study of the consumer welfare implications of targeted online ads. The results were so surprising they repeated the study to make sure their findings were correct. The new findings once again confirmed the results and found targeted ads shown to another set of nearly 500 participants were pitching more expensive products from lower-quality vendors than identical products that showed up in a simple web search. “Both studies consistently highlighted a pervasive problem of low-quality vendors in targeted ads,” wrote the authors.
Behavioral Ad Targeting Not Paying Off for Publishers, Study Suggests
The Wall Street Journal online
The online ad ecosystem is complex and opaque, said Alessandro Acquisti, a professor of information technology and public policy at Carnegie Mellon’s Heinz College, who conducted the study along with Veronica Marotta and Vibhanshu Abhishek. It is “hard to understand how much value each participant in the ecosystem is adding to the process, and whether the fees different intermediaries receive are commensurate to their value added,” he said.
Google’s brand-new AI ethics board is already falling apart
Of the eight people listed in Google’s initial announcement, one (privacy researcher Alessandro Acquisti) has announced on Twitter that he won’t serve, and two others are the subject of petitions calling for their removal — Kay Coles James, president of the conservative Heritage Foundation think tank, and Dyan Gibbens, CEO of drone company Trumbull Unmanned. Thousands of Google employees have signed onto the petition calling for James’s removal.
Google’s AI ethics council is falling apart after just a week
Los Angeles Times online
On Saturday, Alessandro Acquisti, a behavioral economist and privacy researcher, said he won’t be serving on the council. “While I’m devoted to research grappling with key ethical issues of fairness, rights and inclusion in AI, I don’t believe this is the right forum for me to engage in this important work,” Acquisti said on Twitter. He did not respond to a request for comment.
The case against behavioral advertising is stacking up
Last fall, at an FTC hearing on the economics of big data and personal information, Carnegie Mellon University professor of IT and public policy, Alessandro Acquisti, teased a piece of yet to be published research — working with a large U.S. publisher that provided the researchers with millions of transactions to study.
Industry Expertise (3)
IAPP SOUPS Privacy Award (professional)
Best IS Paper in Management Science (professional)
Management Science Best AE Award in IS (professional)
AIS College of Senior Scholars Best Paper Award (professional)
WISE Best Paper Award (professional)
University of California at Berkeley: M.I.M.S., Information Management and Systems
London School of Economics: M.S., Econometrics and Mathematical Economics
University of California at Berkeley: Ph.D., Information Management and Systems
Trinity College Dublin: M.Litt., Economics
University of Rome: B.S., Economics and Business
- Privacy Economics Experiments (PeeX) Lab : Director
- Master of Science in Information Security Policy & Management : Faculty Chair
- CMU Center for Behavioral and Decision Research (CBDR) : Steering Committee
- CMU Institutional Review Board (IRB) : Chair
Event Appearances (5)
The Economics of Privacy
Digital Information Policy Scholars Conference on Privacy George Mason University
Privacy in the Age of Augmented Reality: (Re)Framing the Debate
Presidential Lecture Singapore Management University
Privacy in the Age of Augmented Reality
Privacy Multistakeholder Meeting: Facial Recognition Technology National Telecommunications and Information Administration
Privacy and Behavioral Economics: From the Control Paradox to Augmented Reality
LARC Workshop on User Privacy and Security
Predicting Social Security Numbers from Public Data
Proceedings of the BlackHat US Conference
Learning to Live with Privacy-Preserving AnalyticsCommunications of the ACM
2023 Seeking to close the gap between research and real-world applications of PPAs.
Response to comment on “Policy impacts of statistical uncertainty and privacy”Science
2023 We offer our thanks to the authors for their thoughtful comments. Cui, Gong, Hannig, and Hoffman propose a valuable improvement to our method of estimating lost entitlements due to data error. Because we don’t have access to the unknown, “true” number of children in poverty, our paper simulates data error by drawing counterfactual estimates from a normal distribution around the official, published poverty estimates, which we use to calculate lost entitlements relative to the official allocation of funds.
The Impact of Apple's App Tracking Transparency Framework on the App EcosystemSSRN
2023 We study the impact of the implementation of Apple’s App Tracking Transparency (ATT) framework on the Apple App Store ecosystem. We use comprehensive data on every app available in both the Apple App Store and Google Play Store ecosystems in the eighteen-month period around the implementation of ATT, and a difference-in-differences analysis to investigate whether the introduction of the privacy transparency framework affected the incentives for developers in the Apple ecosystem to create new apps, update their existing apps, or withdraw from the market.
An empirical analysis of sentencing of “Access to Information” computer crimesJournal of Empirical Legal Studies
2023 There is a widespread perception that computer crime sentencing is too harsh. But this criticism has occurred in the absence of comprehensive, multi-year data on how computer crimes are actually sentenced and how those sentences compare to other, purportedly similar crimes, such as trespass, burglary, or fraud.