User Profile

Aaron

awmarrs@bookwyrm.social

Joined 1 year, 6 months ago

Historian of antebellum technology and contemporary diplomacy.

Mastodon: historians.social/@awmarrs

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Aaron's books

Currently Reading

2024 Reading Goal

97% complete! Aaron has read 39 of 40 books.

Melanie Mitchell: Artificial Intelligence (2020, Picador) 4 stars

AlphaGo was a great achievement for AI; learning largely via self-play, it was able to definitively defeat one fo the world’s best human players in a game that is considered a paragon of intellectual prowess. But AlphaGo does not exhibit human-level intelligence as we generally define it, or even arguably any real intelligence. For humans, a crucial part of intelligence is, rather than being able to learn any particular skill, being able to learn to think and to then apply our thinking flexibly to whatever situations or challenges we encounter. This is the true skill we want our children to learn when they play chess or Go. It may sound strange to say, but in this way the lowliest kindergartner in the school chess club is smarter than AlphaGo.

Artificial Intelligence by  (Page 171 - 172)

Cathy O'Neil: Weapons of Math Destruction (Paperback, 2017, Broadway Books) 4 stars

A former Wall Street quant sounds an alarm on the mathematical models that pervade modern …

Weapons of Math Destruction

5 stars

O'Neil is an excellent guide to the world of algorithms and how they impact our lives in ways large and small. To me one of the most depressing lessons of the book was that the people creating these systems which analyze data have almost no interest in the knock-on effects that their work has on people's lives. They are so focused on whatever particular goal they have that they have total blinders as to the damaging effects that their work might have. As with any book about technology the companies have changed a bit since O'Neil wrote the book, but the underlying problems have not changed; thus this continues to be a worthy guide to the challenges that our society will face as we continue to be enmeshed in algorithms which may not have our best interests at heart.

Ai Ai Weiwei, Gianluca Costantini, Elettra Stamboulis: Zodiac (2024, Potter/Ten Speed/Harmony/Rodale) 4 stars

Zodiac

4 stars

I've enjoyed Ai Weiwei's art whenever I have had the opportunity to view it, and so I picked up this book. It turns out that this graphic format is well-suited to the stories that he tells, since past, present, and the world of the animals of the Chinese zodiac can blend together seamlessly in art. The artwork in the book nods to some of Weiwei's artistic creations, but you don't need to know the artist to enjoy the book and understand the stories.

Charlton McIlwain, Charlton D. McIlwain: Black Software (2020, Oxford University Press, Incorporated) 4 stars

Activists, pundits, politicians, and the press frequently proclaim today's digitally mediated racial justice activism the …

Black Software

4 stars

McIlwain's book is unlike other history books that I've read. It incorporates McIlwain's own writing, long quotes from oral histories, and direct reproduction of some primary documents from the time period that McIlwain is covering. Yet while the writing style is idiosyncratic, the stories he tells are amazing. He has tracked down remarkable Black pioneers in computing and gotten them to share their stories. All aspects of computing get covered: retail, repair, programming, building online communities, and so on. In the concluding section of the book McIlwain explores how computers have been used against Black communities, thus giving us a comprehensive picture of computing and Black America at the dawn of this new technology.

Cathy O'Neil: Weapons of Math Destruction (Paperback, 2017, Broadway Books) 4 stars

A former Wall Street quant sounds an alarm on the mathematical models that pervade modern …

Big Data processes codify the past. They do not invent the future. Doing that requires moral imagination, and that’s something only humans can provide. We have to explicitly embed better values into our algorithms, creating Big Data models that follow our ethical lead. Sometimes that will mean putting fairness ahead of profit.

Weapons of Math Destruction by  (Page 204)

Sarah T. Roberts: Behind the Screen (2019, Yale University Press) 3 stars

Behind the Screen

3 stars

Roberts's book explores the world of content moderation, with some in-depth and revealing interviews with the people who actually view hours and hours of horrific content in order to keep it from populating the web. These moderators play a huge role in how we interact with the Internet -- literally determining what we are allowed to see -- yet are largely anonymous and treated as disposable by the corporations who employ them. The people she interviews are reflective: One muses that he was proud of flagging a potential suicide video, which helped save the potential victim, but did the social media site create the circumstances for such videos to happen in the first place? An engaging exploration of a difficult topic, and one that social media companies themselves would assuredly rather not have us think about.

reviewed Programmed inequality by Mar Hicks (History of computing)

Mar Hicks: Programmed inequality (2017, MIT Press, The MIT Press) 5 stars

Programmed Inequality

4 stars

Of all the books that I have been reading lately to better understand "how we got here" with respect to technology and AI, this is the one that is the most "traditional" history in terms of its aims and methodology. Hicks is a historian of technology at the University of Virginia, and in this, her first book, she charts the gendered nature of labor in computing in Great Britain after World War II. Great Britain provides an interesting case study because so much of the computer industry was driven by government involvement. The expanding state after the war required a lot of computing power, and many women were employed to program and operate computers. Interestingly, managers saw computer work as "women's work," since it was viewed as routine and unskilled (although using these complex machines certainly was not). Women who sought these jobs in the 1950s and 1960s might have, …