Event

The Science of the Predicted Human Talk Series: Professor César Hidalgo

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How time, technology, and language impact collective memory and attention

Abstract

From writing to the web, humans have used communication technologies to enhance our collective memory. Yet, much of what was once popular is now forgotten. In this talk, I will present research exploring the roles played by time, language, and technologies on the dynamics of collective memory and attention. Using data on the attention received by biographies, scientific papers, songs, and movies, we will explore the universal decay of collective memory, the role played by languages in global fame, and the biases in attention and collective memory introduced by changes in technology.
 

About César A. Hidalgo

César A. Hidalgo is a Chilean-Spanish-American scholar known for his many contributions to economic complexity, data visualization, and applied artificial intelligence. Hidalgo leads the Center for Collective Learning at the Artificial and Natural Intelligence Institute (ANITI) of the University of Toulouse. He is also an Honorary Professor at the University of Manchester and a Visiting Professor at Harvard’s School of Engineering and Applied Sciences. Between 2010 and 2019 Hidalgo led MIT’s Collective Learning group. Prior to working at MIT, Hidalgo was a research fellow at Harvard’s Kennedy School of Government. Hidalgo is also a founder of Datawheel, an award-winning company specializing in the creation of data distribution and visualization systems. He holds a Ph.D. in Physics from the University of Notre Dame and a Bachelor’s in Physics from Universidad Católica de Chile. His contributions have been recognized with numerous awards, including the 2018 Lagrange Prize and three Webby Awards. He is also the author of three books: Why Information Grows (Basic Books, 2015),  The Atlas of Economic Complexity (MIT Press, 2014), and How Humans Judge Machines (MIT Press, 2021).

Suggested readings

Candia, Cristian, et al. “The universal decay of collective memory and attention.” Nature human behaviour  (2019)
Ronen, Shahar, et al. “Links that speak: The global language network and its association with global fame.” Proceedings of the National Academy of Sciences  (2014)
Jara-Figueroa, C., Amy Z. Yu, and César A. Hidalgo. “How the medium shapes the message: Printing and the rise of the arts and sciences.” PloS one (2019)
Yu, Amy Zhao, et al. “Pantheon 1.0, a manually verified dataset of globally famous biographies.” Scientific data 3.1 (2016)
 

The Predicted Human

Being human in 2023 implies being the target of a vast number of predictive infrastructures. In healthcare, algorithms predict not only potential pharmacological cures to disease but also their possible future incidence of those diseases. In governance, citizens are exposed to algorithms that predict – not only their day-to-day behaviors to craft better policy – but also to algorithms that attempt to predict, shape and manipulate their political attitudes and behaviors. In education, children’s emotional and intellectual development is increasingly the product of at-home and at-school interventions shaped around personalized algorithms. And humans worldwide are increasingly subject to advertising and marketing algorithms whose goal is to target them with specific products and ideas they will find palatable. Algorithms are everywhere – as are their intended as well as unintended consequences. The series is arranged with generous support by the Villum Foundation and the Pioneer Center for Artificial Intelligence.