Publications
Publications
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privacy
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- September 2022 (Revised July 2023)
- Case
Data Privacy in Practice at LinkedIn
- August 2022
- Article
The Bulletproof Glass Effect: Unintended Consequences of Privacy Notices
By: Aaron R. Brough, David A. Norton, Shannon L. Sciarappa and Leslie K. John
Drawing from a content analysis of publicly traded companies’ privacy notices, a survey of managers, a field study, and five online experiments, this research investigates how consumers respond to privacy notices. A privacy notice, by placing legally enforceable limits... View Details
- 2022
- Chapter
Measuring Compliance Risk and the Emergence of Analytics
By: Eugene F. Soltes
Corporate compliance manages a diverse set of regulatory and reputational concerns ranging from fraud to privacy to discrimination. However, effectively managing such risks has often been hampered by a lack of adequate information about when, where, and why misconduct... View Details
- Article
Adaptive Machine Unlearning
By: Varun Gupta, Christopher Jung, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi and Chris Waites
Data deletion algorithms aim to remove the influence of deleted data points from trained models at a cheaper computational cost than fully retraining those models. However, for sequences of deletions, most prior work in the non-convex setting gives valid guarantees... View Details
- October 19, 2021
- Article
The Facebook Trap
By: Andy Wu
Facebook has a clear mission: Connect everyone in the world. Clarity is good, but in Facebook’s case, it has also put the company in a bind because the mission—and the company’s vision for creating value through network effects—has also become the source of its biggest... View Details
- August 2021 (Revised November 2024)
- Case
Intenseye: Powering Workplace Health and Safety with AI (A)
By: Michael W. Toffel and Youssef Abdel Aal
Intenseye was a Turkey-based technology startup that deployed machine learning algorithms to workplace camera feeds in order to identify unsafe worker actions and unsafe working conditions, in order to help improve worker safety. The case describes how Intenseye’s... View Details
- 2021
- Working Paper
Equilibrium Effects of Pay Transparency
By: Zoë B. Cullen and Bobak Pakzad-Hurson
The public discourse around pay transparency has focused on the direct effect: how workers seek
to rectify newly-disclosed pay inequities through renegotiations. The question of how wage-setting
and hiring practices of the firm respond in equilibrium has received... View Details
- 2021
- Article
To Thine Own Self Be True? Incentive Problems in Personalized Law
By: Jordan M. Barry, John William Hatfield and Scott Duke Kominers
Recent years have seen an explosion of scholarship on “personalized law.” Commentators foresee a world in which regulators armed with big data and machine learning techniques determine the optimal legal rule for every regulated party, then instantaneously disseminate... View Details
Keywords: Personalized Law; Regulation; Regulatory Avoidance; Regulatory Arbitrage; Law And Economics; Law And Technology; Law And Artificial Intelligence; Futurism; Moral Hazard; Elicitation; Signaling; Privacy; Law; Governing Rules, Regulations, and Reforms; Information Technology; AI and Machine Learning
- 2023
- Working Paper
Data Governance, Interoperability and Standardization: Organizational Adaptation to Privacy Regulation
By: Sam (Ruiqing) Cao and Marco Iansiti
The increasing availability of data can afford dynamic competitive advantages among data-intensive
corporations, but governance bottlenecks hinder data-driven value creation and increase regulatory risks.
We analyze the role of two technological features of data... View Details
- April 2021 (Revised March 2024)
- Case
Social Media War 2021: Snap vs. Facebook vs. TikTok
By: David B. Yoffie and Daniel Fisher
This case explores the competitive war between Snap, Facebook, and TikTok in 2021. The strategic focus is on Snapchat: how should it respond to the emergence of TikTok, and how should it compete with the dominant competitor in its space—Facebook. The case examines... View Details
- March 2021
- Article
The Impact of the General Data Protection Regulation on Internet Interconnection
By: Ran Zhuo, Bradley Huffaker, KC Claffy and Shane Greenstein
The Internet comprises thousands of independently operated networks, where bilaterally negotiated interconnection agreements determine the flow of data between networks. The European Union’s General Data Protection Regulation (GDPR) imposes strict restrictions on... View Details
- February 2021
- Case
Apple: Privacy vs. Safety (A)
By: Henry McGee, Nien-hê Hsieh, Sarah McAra and Christian Godwin
In 2015, Apple CEO Tim Cook debuted the iPhone 6S with enhanced security measures that enflamed a debate on privacy and public safety around the world. The iPhone 6S, amid a heightened concern for privacy following the 2013 revelation of clandestine U.S. surveillance... View Details
Keywords: Iphone; Encryption; Data Privacy; Customers; Customer Focus and Relationships; Decision Making; Ethics; Values and Beliefs; Globalized Firms and Management; Government and Politics; National Security; Law; Law Enforcement; Leadership; Markets; Safety; Social Issues; Corporate Social Responsibility and Impact; Civil Society or Community; Mobile and Wireless Technology; Technology Industry; Consumer Products Industry; Telecommunications Industry; Electronics Industry; United States; China; Hong Kong
- January 2021 (Revised May 2021)
- Case
Amazon Shopper Panel: Paying Customers for Their Data
By: Eva Ascarza and Ayelet Israeli
This case introduces a new Amazon program that has consumers upload their receipts from transactions outside of Amazon, in exchange for money. Through the discussion, the case aims to explore issues in customers’ privacy in the digital age, the value of customers’ own... View Details
Keywords: Data Analytics; Data Privacy; Data Management; ＂Marketing Analytics＂; Marketing Communication; Marketing Research; Data-driven Management; E-Commerce Strategy; Ethical Decision Making; CRM; Consumer Protection; Targeted Advertising; Targeted Policies; Data Ownership; Marketing; Research; Marketing Communications; Analytics and Data Science; Management; Customer Relationship Management; Ethics; E-commerce; Retail Industry; Technology Industry; United States
- Winter 2021
- Article
Dealmaking Disrupted: The Unexplored Power of Social Media in Negotiation
By: James K. Sebenius, Ben Cook, David A. Lax, Isaac Silberberg and Paul Levy
While social media has had profound effects in many realms, the theory and practice of negotiation have remained relatively untouched by this potent phenomenon. In this article, we survey existing research in this area and develop a broader framework for understanding... View Details
- Oct 2020
- Conference Presentation
Optimal, Truthful, and Private Securities Lending
By: Emily Diana, Michael J. Kearns, Seth Neel and Aaron Leon Roth
We consider a fundamental dynamic allocation problem motivated by the problem of securities lending in financial markets, the mechanism underlying the short selling of stocks. A lender would like to distribute a finite number of identical copies of some scarce resource... View Details
- September 2020 (Revised July 2022)
- Technical Note
Algorithmic Bias in Marketing
By: Ayelet Israeli and Eva Ascarza
This note focuses on algorithmic bias in marketing. First, it presents a variety of marketing examples in which algorithmic bias may occur. The examples are organized around the 4 P’s of marketing – promotion, price, place and product—characterizing the marketing... View Details
Keywords: Algorithmic Data; Race And Ethnicity; Promotion; ＂Marketing Analytics＂; Marketing And Society; Big Data; Privacy; Data-driven Management; Data Analysis; Data Analytics; E-Commerce Strategy; Discrimination; Targeting; Targeted Advertising; Pricing Algorithms; Ethical Decision Making; Customer Heterogeneity; Marketing; Race; Ethnicity; Gender; Diversity; Prejudice and Bias; Marketing Communications; Analytics and Data Science; Analysis; Decision Making; Ethics; Customer Relationship Management; E-commerce; Retail Industry; Apparel and Accessories Industry; United States
- September 2020 (Revised June 2023)
- Exercise
Artea: Designing Targeting Strategies
By: Eva Ascarza and Ayelet Israeli
This collection of exercises aims to teach students about 1)Targeting Policies; and 2)Algorithmic bias in marketing—implications, causes, and possible solutions. Part (A) focuses on A/B testing analysis and targeting. Parts (B),(C),(D) Introduce algorithmic bias. The... View Details
Keywords: Algorithmic Data; Race And Ethnicity; Experimentation; Promotion; ＂Marketing Analytics＂; Marketing And Society; Big Data; Privacy; Data-driven Management; Data Analytics; Data Analysis; E-Commerce Strategy; Discrimination; Targeted Advertising; Targeted Policies; Targeting; Pricing Algorithms; A/B Testing; Ethical Decision Making; Customer Base Analysis; Customer Heterogeneity; Coupons; Algorithmic Bias; Marketing; Race; Gender; Diversity; Customer Relationship Management; Marketing Communications; Advertising; Decision Making; Ethics; E-commerce; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; United States
- August 2020
- Article
Strategies for Managing the Privacy Landscape
By: Ramon Casadesus-Masanell and Andres Hervas-Drane
Firms use consumer personal information to improve their products and services. Personal information is open to misuse, however, and when exploited for undesired or unexpected purposes reduces consumer’s trust in the firm and their willingness to provide personal... View Details
- July 15, 2020
- Article
How to Get People to Actually Use Contact-Tracing Apps
By: Chiara Farronato, Marco Iansiti, Marcin Bartosiak, Stefano Denicolai, Luca Ferretti and Roberto Fontana
The broad adoption of contact-tracing apps would greatly help combat the spread of COVID-19. But a number of barriers—especially privacy concerns—have hindered progress in many countries that can’t or won’t mandate adoption. A solution is to start with small... View Details
- Article
Oracle Efficient Private Non-Convex Optimization
By: Seth Neel, Aaron Leon Roth, Giuseppe Vietri and Zhiwei Steven Wu
One of the most effective algorithms for differentially private learning and optimization is objective perturbation. This technique augments a given optimization problem (e.g. deriving from an ERM problem) with a random linear term, and then exactly solves it.... View Details