ACM, the Association for Computing Machinery, has named Avi Wigderson as recipient of the 2023 ACM A.M. Turing Award for foundational contributions to the theory of computation, including reshaping our understanding of the role of randomness in computation, and for his decades of intellectual leadership in theoretical computer science.

Wigderson is the Herbert H. Maass Professor in the School of Mathematics at the Institute for Advanced Study in Princeton, New Jersey. He has been a leading figure in areas including computational complexity theory, algorithms and optimization, randomness and cryptography, parallel and distributed computation, combinatorics, and graph theory, as well as connections between theoretical computer science and mathematics and science.

The ACM A.M. Turing Award, often referred to as the “Nobel Prize of Computing,” carries a $1 million prize with financial support provided by Google, Inc. The award is named for Alan M. Turing, the British mathematician who articulated the mathematical foundations of computing.

**Why is Randomness Important?**

Fundamentally, computers are *deterministic* systems; the set of instructions of an algorithm applied to any given input uniquely determines its computation and, in particular, its output. In other words, the deterministic algorithm is following a predictable pattern. *Randomness*, by contrast, lacks a well-defined pattern, or predictability in events or outcomes. Because the world we live in seems full of random events (weather systems, biological and quantum phenomena, etc.), computer scientists have enriched algorithms by allowing them to make random choices in the course of their computation, in the hope of improving their efficiency. And indeed, many problems for which no efficient deterministic algorithm was known have been solved efficiently by probabilistic algorithms, albeit with some small probability of error (that can be efficiently reduced). But is randomness essential, or can it be removed? And what is the quality of randomness needed for the success of probabilistic algorithms?

These, and many other fundamental questions lie at the heart of understanding randomness and pseudorandomness in computation. An improved understanding of the dynamics of randomness in computation can lead us to develop better algorithms as well as deepen our understanding of the nature of computation itself.

**Wigderson’s Contributions**

A leader in theoretical computer science research for four decades, Wigderson has made foundational contributions to the understanding of the role of randomness and pseudorandomness in computation.

Computer scientists have discovered a remarkable connection between randomness and computational difficulty (i.e., identifying natural problems that have no efficient algorithms). Working with colleagues, Wigderson authored a highly influential series of works on trading hardness for randomness. They proved that, under standard and widely believed computational assumptions, every probabilistic polynomial time algorithm can be efficiently derandomized (namely, made fully deterministic). In other words, randomness is not necessary for efficient computation. This sequence of works revolutionized our understanding of the role of randomness in computation, and the way we think about randomness.

Read more about Avi Wigderson receiving the ACM A.M. Turing Award in *Communications of the ACM*.

**About the ACM A.M. Turing Award**

The A.M. Turing Award was named for Alan M. Turing, the British mathematician who articulated the mathematical foundation and limits of computing, and who was a key contributor to the Allied cryptanalysis of the Enigma cipher during World War II. Since its inception in 1966, the Turing Award has honored the computer scientists and engineers who created the systems and underlying theoretical foundations that have propelled the information technology industry.