Impact and questions: An AI reading list

As part of some research into artificial intelligence (AI) and machine learning (ML) over the past few months, I’ve come across a lot of reading material.

Here’s some that stood out to me and that I can recommend looking into. Please note that this is very much on the non-technical end of the spectrum: Primers, as well as pieces focusing on societal impact, ethics, and other so-called “soft” aspects, i.e. societal, political, humanitarian, business-related ones. These are the types of impact I’m most interested in and that are most relevant to my work.

The list isn’t comprehensive by any means—if you know of something that should be included, please let me know!—but there’s a lot of insight here.

Enjoy!

Basics, primers:

Resources, reading lists, content collections:

Books:

Articles:

Reports, studies:

Presentations, talks:

Fiction:

For completeness’ sake (and as a blatant plug) I include three recent blog posts of my own:

1 Comment

It’s not strictly about AI, and more the effects of algorithmic decision and machine learning, but I’d also suggest Weapons of Math Destruction by Kathy O’Neil. It provides a good background to the debate, even before you introduce AI.

Official site: https://weaponsofmathdestructionbook.com/

Podcast interview from NPR: http://www.npr.org/2016/09/12/493654950/weapons-of-math-destruction-outlines-dangers-of-relying-on-data-analytics

Her blog: https://mathbabe.org/

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