Sarah L. Fossheim

sarah@fossheim.io

Developer + Designer

Recommended reads on ethics, big data and equality in tech

Weapons of Math Destruction by Cathy O'Neil

I've always had a strong interest in both UX and everything data science related, but reading this book in 2017 helped me realize I really wanted to work at the intersection of the two, and it has been a great motivation to read more on the subject of ethical AI.

The book illustrates how algorithms can, intentionally or unintentionally, harm minoritized groups and provides plenty of examples - from teachers getting fired by automated systems that look at student performance, to incarceration of black people caused by using historical biased data, or payday loans targeting poor communities.

If you're directly or indirectly working on algorithms and big data, or just have an interest in the subject, this is a must-read. It's written in a really accessible and easy-to-understand format, but still goes into enough detail. You don't need much (or any) prior knowledge on the subjects she tackles to understand what it's about.

In short, it's one of my favorite books, and I actually go back to it quite often to re-read specific examples as context for the products I'm working on. It's definitely worth your time and money. Easy, relatively fast read that provides tons of insights by using concrete examples.

Technically Wrong by Sara Wachter-Boettcher

This one is very similar to Weapons of Math Destruction, in the sense that it's an easy and accessible intro to (in)equality and ethics in technology and design, using lots of real-life examples.

But where Weapons of Math Destruction focuses more on algorithms and big data, Technically Wrong takes a more general approach and also tackles diversity in the tech industry. She covers a broad range of issues, from racist and sexist apps, to the issue with blaming the lack of diversity in tech on a "pipeline problem".

You don't need to have a specific background to get value out of this book, there's a lot of useful insights for designers, engineers, managers and everyone else working in STEM fields.

Having read a lot on the topic already, there was not a lot of new ideas or principles I learned from Technically Wrong, but it did provide a lot of extra examples I wasn't aware of, and explained familiar concepts very thoroughly.

I think it provides the most value and insights to newbies, but even if you're not, it's definitely worth giving it a read.

Algorithms of Oppression by Dr Safiya Umoja Noble

Algorithms of Oppression is another book about how algorithms can further oppress already minoritized groups, but focuses more on one specific aspect of it: racism in search engines.

It's written by an associate professor in the departments of Information Studies and African American Studies at UCLA, and starts by describing a specific scenario: she wanted to entertain her nieces with content made for black girls one afternoon, but upon googling "black girls" the results only provided her with porn.

From that perspective she goes further in-depth on how the algorithms behind search engines enforce and often even encourage racism. Google is the main the focus in the book, but it also explains how for example Yelp's search and review algorithms have had a negative impact on communities.

While I thought the book was really interesting, and definitely recommend it, I did find the language a bit more difficult and specialized than the first two books I mentioned. I read the majority of Weapons of Math Destruction on a plane, and Technically Wrong during my commute to work, but for Algorithms of Oppression I needed to set aside focused reading time.

That's absolutely not a bad thing. But the fact that it requires a bit more brain power to read makes me believe it might be more suitable for those who are already interested and are motivated to read through something a bit more advanced, rather than those who are looking for a quick and easy first introduction to the subject.

To be read

I have more similar books in my backlog. It will take me a while to get through them all since I don't set enough time aside to read, and also have a huge list of fiction books I want to get through, but I'll probably do another write up once I finished a few more of them.

I also recommend checking out Mia Dand's monthly book chats on Twitter for more recommendations on ethics in AI.


Hi 👋 I'm Sarah, a multidisciplinary developer and designer, specialized in creating complex and data-heavy products that are accessible, ethical and user friendly. I also enjoy making art with CSS. On here, I frequently write about HTML/CSS, React, Python, UX design, accessibility and data visualizations.

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