Tom Griffiths (cognitive scientist)

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Tom Griffiths
Born
London, England
Alma materUniversity of Western Australia
Stanford University
Scientific career
FieldsPsychology
Cognitive science
InstitutionsUniversity of California, Berkeley
Princeton University[1]
ThesisCauses, coincidences, and theories (2005)
Doctoral advisorJoshua Tenenbaum

Thomas L. Griffiths is an Australian academic who is the Henry R. Luce Professor of Information Technology, Consciousness, and Culture at Princeton University. He studies human decision-making and its connection to problem-solving methods in computation. His book with Brian Christian, Algorithms to Live By: The Computer Science of Human Decisions, was named one of the "Best Books of 2016" by MIT Technology Review.

Biography[]

Fencing with longswords, from a fifteenth-century manual of fencing

Griffiths was born in London but moved with his family when he was eight to Perth, Australia.[2][3]

Growing up, Griffiths enjoyed computer programming and online role-playing games. At twelve, he started fencing, which he says involves "interesting computational problems",[4] becoming "an avid fencer".[3] He developed a method to break down complex fencing moves into simpler ones that could be performed in sequence, but gave up on the theory after, he says, "I messed up the math and a longsword broke my right wrist."[4]

Griffiths received his undergraduate degree in psychology from the University of Western Australia.[5][2]

He applied to Stanford University for graduate school in psychology, hoping to work on mathematical models of human cognition with David Rumelhart or Roger Shepard, not realizing that both had just retired.[5] Instead, Joshua Tenenbaum, who was working on Bayesian cognitive science, became his thesis advisor. His work with Tenenbaum used Bayesian statistics as well as principles from AI and machine learning and to explore topics in cognitive psychology, such as learning, memory, and categorization.[4] When Tenenbaum left Stanford for MIT, Griffiths accompanied him, becoming an exchange student there.[3] Griffiths earned master's degrees in both psychology and statistics from Stanford, as well as a Stanford Ph.D. in psychology in 2005.[5]

After teaching briefly at Brown University, he moved to Berkeley in 2006 as an assistant professor in the Department of Psychology and Cognitive Science Program. In 2010, he became an associate professor and the director of Berkeley's Institute of Cognitive and Brain Sciences.[1][6] He became a full professor at Berkeley in 2015.[1][7]

In 2018, Griffiths was hired by Princeton, as a joint appointment by the Department of Computer Science and the Department of Psychology.[8] At Princeton, he is the Henry R. Luce Professor of Information Technology, Consciousness, and Culture.[1] On his Princeton webpage, Griffiths explains that his research explores the connection between human problem solving and related methods in computation and logic: "People solve challenging computational problems every day, making predictions about future events, learning new causal relationships, or discovering how objects should be divided into categories. My research investigates how this is possible, first identifying the nature of the underlying computational problems, and then examining whether we can explain aspects of human behavior as the result of approximating optimal solutions to those problems."[9]

Awards[]

In 2011 the Association for Psychological Science awarded Griffiths its Janet Taylor Spence Award for Transformative Early Career Contributions, recognizing his work exploring "mathematical models of human cognition".[5][10]

In 2012 he won American Psychological Association's Award for Distinguished Scientific Early Career Contributions to Psychology "for bringing mathematical precision to the deepest questions in human learning, reasoning, and concept formation."[11]

In 2014, Griffiths received a Cognitive Science Society Award.[12] At that time, he was "director of the Computational Cognitive Science Lab and the Institute of Cognitive and Brain Sciences at the University of California, Berkeley." In 2019, the National Academy of Sciences awarded Griffiths its $75,000 Troland Research Award "for his research into how people and machines make decisions."[13]

In 2017, while at Berkeley, Griffiths was awarded a John Simon Guggenheim Memorial Foundation fellowship, an award given "on the basis of prior achievement and exceptional promise." Berkeley described his work at that time as follows: "His research explores connections between human and machine learning, using ideas from statistics and artificial intelligence to understand how people solve the challenging computational problems they encounter in everyday life."[6]

Publications[]

In 2016, Griffiths co-authored a book, Algorithms to Live By: The Computer Science of Human Decisions, with Brian Christian. Kirkus Reviews described it as "An entertaining, intelligently presented book for the numerate and computer literate."[14] David DiSalvo, author of "What Makes Your Brain Happy and Why You Should Do the Opposite, called Algorithms to Live By a "surprisingly useful book that travels from computer science to human decision-making ... a dense primer on the algorithms of decision-making and a tip-filled guide for making better decisions."[15]

In The Guardian, Oliver Burkeman wrote that he "wasn’t predisposed to love Algorithms To Live By" but by the end of the book was convinced that "computing algorithms could be a surprisingly useful way to embrace the messy compromises of real, non-Vulcan life."[16] MIT Technology Review listed it as one of their "Best Books of 2016."[17]

References[]

  1. ^ Jump up to: a b c d "CURRICULUM VITAE THOMAS L. GRIFFITHS" (PDF). Princeton University. 2020. Retrieved 20 March 2021.
  2. ^ Jump up to: a b Griffiths, Tom (21 August 2017). "Aerodynamics For Cognition". Edge.org. Retrieved 26 January 2021. I grew up in Australia. I was born in London, and my parents moved to Australia when I was eight years old. I did my undergraduate degree at the University of Western Australia, in Perth, which has a reputation as being the most isolated capital city on earth. It's a long way from anything else, but it's also a great place to grow up.
  3. ^ Jump up to: a b c "WELCOME NEW GRADUATE STUDENTS" (PDF). MIT Brain and Cognitive Sciences. 2002. Retrieved 24 January 2021. Tom Griffiths an avid fencer from Perth, Western Australia, 'which is apparently the most isolated Western city on Earth.' He received a Bachelor’s degree in psychology from the University of Western Australia, and started a PhD at Stanford University, where he worked with Josh Tenenbaum. Tom will spend the next couple of years here as an exchange student, so they can continue to work together.
  4. ^ Jump up to: a b c Hutson, Matthew (18 November 2019). "Of Minds and Machines: Tom Griffiths combines psychology and artificial intelligence". Princeton University. Retrieved 24 January 2021. Griffiths’ earliest work as a graduate student, at Stanford, drew on the work of the 18th–century statistician Thomas Bayes, which involves updating prior estimates about the probability of an event or explanation based on incoming information...Griffiths and his Ph.D. adviser, Joshua Tenenbaum, helped pioneer the use of Bayesian methods to model cognition.
  5. ^ Jump up to: a b c d "2011 Janet Taylor Spence Award". Association for Pyschological Science. 2011. Retrieved 4 January 2021. I applied to Stanford for grad school hoping to work with Roger Shepard, Stanford University, and David Rumelhart, not knowing that neither was taking students. I was lucky enough to have my folder pulled from the stack by Josh Tenenbaum, Massachusetts Institute of Technology, who was a great advisor. Since then, Rich Shiffrin, Indiana University, and Rich Ivry, University of California, Berkeley, have been generous mentors and advocates.
  6. ^ Jump up to: a b "Seven at UC Berkeley awarded 2017 Guggenheim Fellowships, most of any university". UC Berkeley News. 7 April 2017. Retrieved 19 March 2021. Tom Griffiths is a professor of psychology and cognitive science and director of the Institute of Cognitive and Brain Sciences. His research explores connections between human and machine learning, using ideas from statistics and artificial intelligence to understand how people solve the challenging computational problems they encounter in everyday life.
  7. ^ "Tom Griffiths: Former BIDS Senior Fellow". Berkeley Institute for Data Science. Retrieved 18 February 2021. After a brief stint teaching at Brown University, he came to Berkeley in 2006, and his research resulted in awards from a number of organizations... His research focused on using mathematical and computational tools to study human cognition.
  8. ^ Hulette, Doug (26 September 2018). "Mind the gap: Griffiths on bridging the computer-human divide". Princeton University News. Retrieved 24 January 2021. His is the first joint faculty appointment of the Department of Computer Science and the Department of Psychology....Griffiths, who was born in the U.K., earned his bachelor’s degree in psychology at the University of Western Australia before moving to California to study at Stanford University, where he earned master’s degrees in psychology and statistics and his doctorate in psychology. He spent the second half of his doctoral work at the Massachusetts Institute of Technology’s Department of Brain and Cognitive Sciences as well as the Computer Science and Artificial Intelligence Laboratory.
  9. ^ "Department of Psychology: Tom Griffiths"". psych.princeton.edu.
  10. ^ "APS Janet Taylor Spence Award for Transformative Early Career Contributions". Association for Psychological Science – APS.
  11. ^ "Thomas L. Griffiths: Award for Distinguished Scientific Early Career Contributions to Psychology". The American Psychologist. National Institute of Health. 67 (8): 630–1. 2012. doi:10.1037/a0029945. PMID 23163442. Retrieved 24 January 2021. Thomas L. Griffiths won the award for bringing mathematical precision to the deepest questions in human learning, reasoning, and concept formation. In his pioneering work, Thomas L. Griffiths has used probabilistic models and Bayesian learning methods to illuminate an extraordinarily wide range of problems in areas including causal reasoning, high-level hierarchical thinking, cultural evolution, theory formation, and cognitive development while also showing that thinking probabilistically can provide a genuine resolution of the age-old tension between nativism and empiricism. His rigorous mathematical and computational abilities are accompanied by an immensely creative imagination, a sure sense of the important problem, and an unerring touch for the right experiment.
  12. ^ "2014 Cognitive Science Society Award Winner". Cognitive Science Society. 2014. Retrieved 4 January 2021. Thomas L. Griffiths has been at the heart of a set of ideas that have revolutionized cognitive science. He has used the Bayesian approach to provide deep, novel insights into core topics in cognitive psychology such as semantic memory, causal learning, similarity, and categorization. His work is distinctive in drawing on current work in machine learning, artificial intelligence, and statistics to provide new, formal tools for understanding human cognition.
  13. ^ Fuller-Wright, Liz (23 January 2019). "Griffiths receives Troland prize from the National Academy of Sciences". Princeton University. Retrieved 24 January 2021. The National Academy of Sciences announced today that Thomas Griffiths has received one of the two Troland Research Awards issued this year "for his research into how people and machines make decisions." The Troland awards recognize unusual achievement by young investigators (defined as no older than 40) working within the broad spectrum of experimental psychology.
  14. ^ "Algorithms to Live By". Kirkus Reviews. 15 February 2016. Retrieved 26 January 2021. The authors lead us into the labyrinth with lessons on such matters as improved search and sort—sorting being 'key to the human experience of information,' and thus a good thing to ponder... The procrastinators and untidy among us will rejoice in knowing that sometimes a mess is not just OK, but even “the optimal choice,” as long as your search mechanism is good enough.
  15. ^ DiSalvo, David (19 December 2016). "The Must-Read Brain Books Of 2016". Forbes.
  16. ^ Burkeman, Oliver (29 April 2016). "Why thinking like a computer scientist can help with big decisions". the Guardian.
  17. ^ "Best Books of 2016". MIT Technology Review. 23 December 2016. Retrieved 21 March 2021.

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