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Show Results For
- All HBS Web
(528)
- News (110)
- Research (229)
- Events (3)
- Multimedia (12)
- Faculty Publications (148)
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- 22 Apr 2013
- Working Paper Summaries
Competing with Privacy
- 19 May 2020
- Research & Ideas
Why Privacy Protection Notices Turn Off Shoppers
make you feel less safe by making you conscious of just how much you are giving away? A new working paper finds that it’s more likely to be the latter. “Even if a privacy policy is meant to be assuaging, it can prime you to think about... View Details
- Research Summary
An Empirical Approach to Understanding Privacy Valuation
The purpose of this research is to detect the presence of sophisticated economic motives behind individual concerns for privacy. Recent theories of privacy demands in commercial contexts have assumed an economically aware and sophisticated consumer, capable of... View Details
- 13 Feb 2024
- Cold Call Podcast
Apple’s Dilemma: Balancing Privacy and Safety Responsibilities
Keywords: Re: Nien-he Hsieh & Henry W. McGee
- Article
How to Use Heuristics for Differential Privacy
By: Seth Neel, Aaron Leon Roth and Zhiwei Steven Wu
We develop theory for using heuristics to solve computationally hard problems in differential privacy. Heuristic approaches have enjoyed tremendous success in machine learning, for which performance can be empirically evaluated. However, privacy guarantees cannot be... View Details
Neel, Seth, Aaron Leon Roth, and Zhiwei Steven Wu. "How to Use Heuristics for Differential Privacy." Proceedings of the IEEE Annual Symposium on Foundations of Computer Science (FOCS) 60th (2019).
- 13 Apr 2020
- Working Paper Summaries
The Bulletproof Glass Effect: When Privacy Notices Backfire
- 02 Mar 2016
- What Do You Think?
Is Apple’s Real Privacy Challenge Technology Innovation Itself?
Is the Discussion of Infotech Security versus Privacy a Waste of Time? Summing Up Discussion of this month’s question devolved into a debate about the usual issues: privacy versus security, Apple versus the... View Details
- Article
The Role of Interactivity in Local Differential Privacy
By: Matthew Joseph, Jieming Mao, Seth Neel and Aaron Leon Roth
We study the power of interactivity in local differential privacy. First, we focus on the difference between fully interactive and sequentially interactive protocols. Sequentially interactive protocols may query users adaptively in sequence, but they cannot return to... View Details
Joseph, Matthew, Jieming Mao, Seth Neel, and Aaron Leon Roth. "The Role of Interactivity in Local Differential Privacy." Proceedings of the IEEE Annual Symposium on Foundations of Computer Science (FOCS) 60th (2019).
- Article
Facebook Knows It Can't Offer More Privacy
Kominers, Scott Duke. "Facebook Knows It Can't Offer More Privacy." Bloomberg View (April 26, 2018).
- October 1991 (Revised October 1993)
- Case
Equifax: Privacy in the Information Age
By: Lynn S. Paine
Paine, Lynn S. "Equifax: Privacy in the Information Age." Harvard Business School Case 392-028, October 1991. (Revised October 1993.)
- 2023
- Article
MoPe: Model Perturbation-based Privacy Attacks on Language Models
By: Marvin Li, Jason Wang, Jeffrey Wang and Seth Neel
Recent work has shown that Large Language Models (LLMs) can unintentionally leak sensitive information present in their training data. In this paper, we present Model Perturbations (MoPe), a new method to identify with high confidence if a given text is in the training... View Details
Li, Marvin, Jason Wang, Jeffrey Wang, and Seth Neel. "MoPe: Model Perturbation-based Privacy Attacks on Language Models." Proceedings of the Conference on Empirical Methods in Natural Language Processing (2023): 13647–13660.
- September 2022 (Revised July 2023)
- Case
Data Privacy in Practice at LinkedIn
Bojinov, Iavor, Marco Iansiti, and Seth Neel. "Data Privacy in Practice at LinkedIn." Harvard Business School Case 623-024, September 2022. (Revised July 2023.)
- 04 Jun 2024
- Research & Ideas
Navigating Consumer Data Privacy in an AI World
Being proactive about how you handle data and run your models to protect privacy isn't just smart—it's essential. It’s really the best way to go about it. “There's a growing awareness among customers and users about how their data is... View Details
- 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
Keywords: Organizations; Information Technology; Performance Productivity; Growth and Development; Transformation
Cao, Sam (Ruiqing), and Marco Iansiti. "Data Governance, Interoperability and Standardization: Organizational Adaptation to Privacy Regulation." Harvard Business School Working Paper, No. 21-122, May 2021. (Revised November 2023.)
- March – April 1975
- Article
Personal Privacy versus the Corporate Commuter
By: K. Goldstein and R. L. Nolan
Goldstein, K., and R. L. Nolan. "Personal Privacy versus the Corporate Commuter." Harvard Business Review 53, no. 2 (March–April 1975).
- October 2016 (Revised March 2018)
- Teaching Note
Apple: Privacy vs. Safety? (A) and (B)
By: Nien-hê Hsieh, Henry McGee and Sarah McAra
Teaching Note for HBS No. 316-069. View Details
- 2007
- Working Paper
An Empirical Approach to Understanding Privacy Valuation
By: Luc Wathieu and Allan Friedman
Wathieu, Luc, and Allan Friedman. "An Empirical Approach to Understanding Privacy Valuation." Harvard Business School Working Paper, No. 07-075, April 2007.
- 19 May 2014
- Research & Ideas
Why Companies Should Compete for Your Privacy
Consumers are increasingly wary about sharing personal information with firms. Yet when they benefit from providing information in exchange for lower prices or better services, many consumers will gladly make the privacy trade-off. But... View Details