Helen Nissenbaum
Professor at Cornell Tech; originator of contextual integrity
Helen Nissenbaum's theory of contextual integrity reframed privacy: what matters is not secrecy but whether information flows match the norms of the context it was shared in. Privacy in Context (2010) underpins much current thinking on data use, and Obfuscation (2015, with Finn Brunton) is a practical guide to resistance.
Key arguments & positions
- Argues privacy is about appropriate information flow in context, not secrecy — her theory of contextual integrity.
- Holds that consent to share data in one setting is not consent to reuse it in another, which undercuts most "it was public" defenses of training-data collection.
- Argues obfuscation — deliberate noise — is a legitimate tool for people with little power over data collection.
Accomplishments
- Professor of information science at Cornell Tech; director of the Digital Life Initiative.
- Originated contextual integrity, now widely used in privacy law and policy analysis.
- Author of Privacy in Context (2010) and, with Finn Brunton, Obfuscation (2015).
Papers & key writings
Links
In the library
Nothing of theirs is filed in the hub yet. Browse the full library.
Recommended next
Hand-picked from the hub based on what Helen Nissenbaum covers.
Decoded Futures Prompt Cookbook V.2
A free, no-code recipe book of practical AI prompts built for nonprofit teams. Turn existing reports, events, and materials into slide decks, web pages, plain-language translations, social copy, and repeatable workflows. Every recipe includes a privacy badge so you know what stays on your computer, what goes public, and what connects to a vendor account.
Why this: Covers privacy and AI ethics too
Meta's Latest AI Product Is A Terrifying And Hilarious Mess (Karl Bode)
A column by tech and telecom writer Karl Bode criticizing a new Meta AI product over surveillance and privacy concerns.
Why this: Covers privacy and AI ethics too
Carissa Véliz: Privacy Is Power in the Age of AI (Thinking On Paper)
A Thinking On Paper podcast episode with Carissa Véliz, an Oxford associate professor working on AI ethics. She describes privacy as an ability, a right and a duty, explains what companies can infer from location data, and discusses algorithmic decisions that cannot be explained or appealed, decentralized identity, and choosing tools such as Signal and DuckDuckGo. Free to listen or watch.
Why this: Covers privacy and AI ethics too
Apple's AI Can Go Where Yours Isn't Allowed (RaLHF)
RaLHF essay on companies holding your personal data letting AI bots in, and why Apple's approach gets access others don't.
Why this: Covers privacy and AI ethics too