Algorithms for the People Audiobook By Josh Simons cover art

Algorithms for the People

Democracy in the Age of AI

Preview

Try for $0.00
Prime logo Prime members: New to Audible?
Get 2 free audiobooks during trial.
Pick 1 audiobook a month from our unmatched collection.
Listen all you want to thousands of included audiobooks, Originals, and podcasts.
Access exclusive sales and deals.
Premium Plus auto-renews for $14.95/mo after 30 days. Cancel anytime.

Algorithms for the People

By: Josh Simons
Narrated by: Teri Schnaubelt
Try for $0.00

$14.95/month after 30 days. Cancel anytime.

Buy for $23.36

Buy for $23.36

Confirm purchase
Pay using card ending in
By confirming your purchase, you agree to Audible's Conditions of Use and Amazon's Privacy Notice. Taxes where applicable.
Cancel

About this listen

This audiobook narrated by Teri Schnaubelt explains how to put democracy at the heart of AI governance

Artificial intelligence and machine learning are reshaping our world. Police forces use them to decide where to send police officers, judges to decide whom to release on bail, welfare agencies to decide which children are at risk of abuse, and Facebook and Google to rank content and distribute ads. In these spheres, and many others, powerful prediction tools are changing how decisions are made, narrowing opportunities for the exercise of judgment, empathy, and creativity. In Algorithms for the People, Josh Simons flips the narrative about how we govern these technologies. Instead of examining the impact of technology on democracy, he explores how to put democracy at the heart of AI governance.

Drawing on his experience as a research fellow at Harvard University, a visiting research scientist on Facebook’s Responsible AI team, and a policy advisor to the UK’s Labour Party, Simons gets under the hood of predictive technologies, offering an accessible account of how they work, why they matter, and how to regulate the institutions that build and use them.

He argues that prediction is political: human choices about how to design and use predictive tools shape their effects. Approaching predictive technologies through the lens of political theory casts new light on how democracies should govern political choices made outside the sphere of representative politics. Showing the connection between technology regulation and democratic reform, Simons argues that we must go beyond conventional theorizing of AI ethics to wrestle with fundamental moral and political questions about how the governance of technology can support the flourishing of democracy.

PLEASE NOTE: When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.

©2023 Princeton University Press (P)2023 Princeton University Press
Machine Learning Data Science Artificial Intelligence Politics Democracy Technology
activate_Holiday_promo_in_buybox_DT_T2

Critic reviews

“A timely, thought-provoking, and distinct contribution to a fast-growing and crowded debate. It does an admirable job of bridging several disciplinary divides while maintaining a clear perspective.”—Reuben Binns, University of Oxford
“A sophisticated, politically, technologically, and economically informed manifesto for how to regulate big tech.”—John Zerilli, University of Oxford, author of A Citizen’s Guide to Artificial Intelligence

“If you have any concerns about the growing and pervasive impact of algorithms on society—and you should be concerned about how machine learning tools amplify and perpetuate unfairness, surveillance, and distrust—this is the book you need. Cogent and wise, bridging computer science, law and politics, it reveals human choices within machine learning used by public and private bureaucracies and dominant social media. And it identifies feasible approaches to reclaim accountability and public good.”—Martha Minow, Harvard University, author of When Should Law Forgive?

What listeners say about Algorithms for the People

Average customer ratings
Overall
  • 4 out of 5 stars
  • 5 Stars
    1
  • 4 Stars
    1
  • 3 Stars
    1
  • 2 Stars
    0
  • 1 Stars
    0
Performance
  • 3.5 out of 5 stars
  • 5 Stars
    1
  • 4 Stars
    0
  • 3 Stars
    0
  • 2 Stars
    1
  • 1 Stars
    0
Story
  • 4.5 out of 5 stars
  • 5 Stars
    1
  • 4 Stars
    1
  • 3 Stars
    0
  • 2 Stars
    0
  • 1 Stars
    0

Reviews - Please select the tabs below to change the source of reviews.