Indistinguishability: The Stuff of Magic

What do encryption, blockchain, password generation, and privacy-preserving data analysis have in common? At a keynote address at the 2026 INFORMS Annual Meeting in San Francisco, Cynthia Dwork explored how these seemingly unrelated technologies are connected through a fundamental concept in theoretical computer science: indistinguishability.

Dwork, the Gordon McKay Professor of Computer Science at Harvard University and Affiliated Faculty at Harvard Law School and Department of Statistics, explored during her keynote how a concept rooted in computational limitations has become an essential foundation for modern computing. Her presentation explored the surprising relationship between mathematical impossibility and practical algorithmic innovation.

A Common Thread Across Technologies

Dwork opened her presentation with examples ranging from encryption and blockchain to digital games, smart machines, and smartphone suggestions. She challenged the audience with a simple question: “What do these things have in common?”

Dwork said the answer lies in indistinguishability, a core concept in complexity theory that describes situations in which two outcomes cannot be reliably distinguished by an observer under specified computational limitations.

Mathematical guarantees about what cannot be learned can provide the foundation for protecting sensitive information.

For example, explained Dwork, a secure encryption system should prevent an unauthorized observer from distinguishing an encryption of zero from an encryption of one. Similarly, privacy-preserving data analysis aims to ensure that the results obtained from a dataset containing an individual’s information are nearly indistinguishable from those obtained without that individual’s data.

These examples illustrate how mathematical guarantees about what cannot be learned can provide the foundation for protecting sensitive information.

Turning Impossibility into Innovation

One of the central insights of Dwork’s presentation is the remarkable relationship between impossibility and constructive algorithm design. Although indistinguishability is defined through what computational methods cannot accomplish, it has enabled researchers to develop powerful tools with wide-ranging applications.

Dwork highlighted several important concepts, including zero-knowledge proofs, pseudo-randomness, privacy-preserving data analysis, and public-key cryptography. Despite their different purposes, she said, these concepts share a common mathematical foundation based on indistinguishability.

Zero-knowledge proofs, for example, allow one party to demonstrate the validity of a statement without revealing additional information. Pseudo-randomness enables efficiently generated sequences to appear random to computationally limited observers.

Dwork said that these developments demonstrate how theoretical computer science can transform computational limitations into practical capabilities, providing rigorous foundations for security, privacy, and trustworthy computation.

The Future of Responsible Computing

Dwork also considered the broader implications of indistinguishability for modern computer systems. As computational technologies increasingly influence communication, decision-making, and access to information, questions about privacy, fairness, and societal values become increasingly important.

Indistinguishability offers a mathematical perspective for examining these challenges, particularly when considering what information computational systems should reveal or conceal.

Dwork’s presentation illustrated the continuing importance of theoretical computer science in shaping technological progress. By transforming a notion of computational impossibility into a powerful tool for algorithmic construction, indistinguishability demonstrates how fundamental mathematical ideas can contribute to developing technologies that are secure, privacy-conscious, and responsive to important societal values.