Latanya Sweeney

Daniel Paul Professor of Practice at Harvard & Inventor of k-Anonymity

Lifespan 1959–

Technical Depth intermediate

Key Breakthrough k-Anonymity Mathematical Data Privacy Model (1998) & Re-Identification Proofs

Focus Areas

data privacy cryptography public interest tech

Topic Keywords

#data-privacy #k-anonymity #algorithmic-bias #harvard #de-identification

Source: Historical Biographical Archive / Wikimedia Commons

Latanya Sweeney

Daniel Paul Professor of Practice at Harvard & Inventor of k-Anonymity

Biographical Overview

Daniel Paul Professor of the Practice of Government and Technology at Harvard University and Director of the Public Interest Tech Lab. Sweeney invented the k-anonymity mathematical privacy model and proved that 87% of Americans can be uniquely identified by only three attributes: 5-digit ZIP code, gender, and date of birth.

"Data has consequences. If you think data is anonymous just because you removed the name, you do not understand the power of linking."
— Latanya Sweeney

Lifespan 1959–

Technical Depth intermediate

Key Breakthrough k-Anonymity Mathematical Data Privacy Model (1998) & Re-Identification Proofs

Focus Areas

data privacy cryptography public interest tech

Topic Keywords

#data-privacy #k-anonymity #algorithmic-bias #harvard #de-identification

Source: Historical Biographical Archive / Wikimedia Commons

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Historical Context & Impact

In short

In 1997, Massachusetts Governor William Weld assured the public that state employee health records released to researchers were completely anonymous. To prove him wrong, Sweeney spent $20 for the Cambridge voter rolls, cross-referenced them with the health file, and hand-delivered the Governor's private medical diagnosis to his office.

Key Technical Breakthroughs & Inventions

k-Anonymity Privacy Formulation (1998–2002) Defined the mathematical framework requiring that any release of sensitive data must group individuals so each record is indistinguishable from at least k-1 others.

Re-Identification Proofs & Weld Demonstration Proved that "de-identified" public databases leak private identities by purchasing voter registration lists and linking them to supposedly anonymous hospital discharge records.

Federal Trade Commission Chief Technologist (2014) Audited commercial mobile apps, ad trackers, and data brokers, pioneering evidence-based technological enforcement of consumer protection laws.

Harvard Public Interest Tech Lab Founded the Public Interest Tech Lab and Data Privacy Lab, mentoring hundreds of researchers investigating algorithmic bias, voter registry vulnerabilities, and facial recognition.