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Law and Cryptography: Coexistence and Collaboration for Privacy and Safety

This panel presentation explores the intersection of law and cryptography, highlighting their different disciplines and shared goal of providing mechanisms for humans to coexist, collaborate, and create safely. It discusses how differential privacy and multi-party computation can break the traditional notion of "either privacy or use" for data, enabling societal benefits such as exposing hidden trends and biases, transparency in legal processes, medical research, and data ownership empowerment. The presentation also emphasizes the need for developing legal frameworks and mathematical algorithms to match the evolving concepts and laws surrounding privacy.

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Law and Cryptography: Coexistence and Collaboration for Privacy and Safety

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  1. Differential Privacy and Multi-Party Computation in the eyes of the Law:Panel presentation, DPMPC, June ‘18 Ran Canetti (BU & TAU)

  2. Law and Cryptography • Very different disciplines (algorithms & mathematics vs. ethics, philosophy, history) • Same goal: Provide mechanisms that enable humans to co-exist, collaborate and create, with safety. (Law is of course much broader than crypto… but never mind that…) => A Lot to learn from each other.

  3. Law and Cryptography • Very different disciplines (algorithms & mathematics vs. ethics, philosophy, history) • Same goal: Provide mechanisms that enable humans to co-exist, collaborate and create, with safety. (Law is of course much broader than crypto… but never mind that…) => A Lot to learn from each other.

  4. Law and Cryptography • Very different disciplines (algorithms & mathematics vs. ethics, philosophy, history) • Same goal: Provide mechanisms that enable humans to co-exist, collaborate and create, with safety. (Law is of course much broader than crypto… but never mind that…) => A Lot to learn from each other.

  5. The Promise of DP & MPC(“for the social good”) Both enable breaking the age-old conditioning of “either privacy or use” for data.. E. g: • Exposing hidden societal trends and biases • Transparency and accountability of legal and regulatory processes • Medical research • Data ownership and empowerment of people

  6. The Promise of DP & MPC(“for the social good”) Both enable breaking the age-old conditioning of “either privacy or use” for data. E. g: • Exposing hidden societal trends and biases • Transparency and accountability of legal and regulatory processes • Medical research • Data ownership and empowerment of people

  7. Still, much work to do: • Develop legal encoding of basic technical concepts (probability,  knowledge vs data, computational hardness,  interactive proofs) • Extend legal thinking to provide meaningful boundaries for: • Data privacy • Data use • Data ownership and control • Develop algorithms and mathematical frameworks that match the legal ones.

  8. Still, much work to do: • Develop legal encoding of basic technical concepts (probability,  knowledge vs data, computational hardness,  interactive proofs) • Extend legal thinking to provide meaningful boundaries for: • Data privacy • Data use • Data ownership and control • Develop algorithms and mathematical frameworks that match the legal ones.

  9. Still, much work to do: • Develop legal encoding of basic technical concepts (probability,  knowledge vs data, computational hardness,  interactive proofs) • Extend legal thinking to provide meaningful boundaries for: • Data privacy • Data use • Data ownership and control • Develop algorithms and mathematical frameworks that match the legal ones.

  10. Case in point: Defining privacy The right to Privacy [Brendeis-Warren,1890]: Privacy is “the right to be let alone” Goal: Providing individuals with a safehaven for well-being and creativity. Traditionally interpreted as: -- Putting curbs on the disclosure of information -- An individual is the owner of her data But, with DP/MPC can use data without revealing it… This is a multi-edge sword: • Can make good use of data without “disclosing private information” • Can also invade privacy (safehaven) without disclosing private information… • Private information of different individuals are highly correlated, thus ownership of private data is not well defined…  Need to rethink these concepts and the laws surrounding them…

  11. Case in point: Defining privacy The right to Privacy [Brendeis-Warren,1890]: Privacy is “the right to be let alone” Goal: Providing individuals with a safehaven for well-being and creativity. Traditionally interpreted as: -- Putting curbs on the disclosure of information -- An individual is the owner of her data But, with DP/MPC can use data without revealing it… This is a multi-edge sword: • Can make good use of data without “disclosing private information” • Can also invade privacy (safehaven) without disclosing private information… • Private information of different individuals are highly correlated, thus ownership of private data is not well defined…  Need to rethink these concepts and the laws surrounding them…

  12. Case in point: Defining privacy The right to Privacy [Brendeis-Warren,1890]: Privacy is “the right to be let alone” Goal: Providing individuals with a safehaven for well-being and creativity. Traditionally interpreted as: -- Putting curbs on the disclosure of information -- An individual is the owner of her data But, with DP/MPC can use data without revealing it… This is a multi-edge sword: • Can make good use of data without “disclosing private information” • Can also invade privacy (safehaven) without disclosing private information… • Private information of different individuals are highly correlated, thus ownership of private data is not well defined…  Need to rethink these concepts and the laws surrounding them.

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