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Data Feminism

(Strong Ideas)

4.42  ·  Rating details ·  451 ratings  ·  77 reviews
A new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism.

Today, data science is a form of power. It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, make
Hardcover, 328 pages
Published March 10th 2020 by MIT Press
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Jan 08, 2021 rated it liked it
The authors of this book want us to be aware of our positionality, so I'll tell you that I've been a scientist in the field of genetics for over 20 years, more recently as a curator and manager of delivering data to the public. I'm also a woman of color who thinks a lot about ethics and equity. Which is to say, I really try to think critically about data, scientific and otherwise.

I take this book literally. I fully agree that we need to look at what biases lay behind the hypotheses and interpre
Nov 05, 2020 rated it it was amazing
Let me begin this review by paraphrasing something the authors express early on in the book: don’t let the title dissuade you; this is a book that everyone should pick up (and the authors facilitate this by making it freely available online). A true understanding of feminism and the values that define it has become distorted by contesting voices or is resisted by the uninitiated for various subjective reasons (often due to misunderstanding). With this in mind, this book proved to be a very helpf ...more
Jun 02, 2020 rated it it was amazing
4.5* stars but rounding to 5 because this is an essential read nowadays.

It was a pleasurable read. I learnt a lot along the way. And having synchronised the reading with the weekly video seminars with the authors made it a much pleasant experience than I had before with a more "academic" book.

Having experienced data science from my studies and as a job, I could relate myself a lot in this book. I learnt what is really behind data cleaning, why more women are hired as a data analyst (like myself
Sep 14, 2020 rated it it was ok
This book ignores the ideology that fuels data today. In a flawless feminist liberal approach, structural oppression is characterized like a "privilege hazard," ignoring a serious analysis of the economic framework where technology is situated today to fortress those oppressions. ...more
May 10, 2021 rated it really liked it
This is a great read, overall -- thoughtful conceptual framework, well-used theory, a great message and a lively tone. I certainly found some beautiful lines/quotations and great new formulations for how to think & speak about these topics in my workplace --

My main question mark about it is that I'm not entirely sure who the audience is. If it's people with a background in feminist/intersectionality theory, it's fundamentally pretty basic info (although the examples used to illustrate them are
Nov 25, 2020 rated it did not like it
A book called "Data Feminism" that suggests collecting data on sex can be and often is inappropriate...🥴. If you like to hem and haw and not land anywhere firm that might require you to say what you think this is absolutely the book for you. ...more
Nikki Sojkowski
This is a fantastic introductory text for several fields— most notably intersectional feminism, data ethics/justice, and visual cultures. D'Ignazio and Klein dive into the highly relevant dangers that unmonitored data can cause, and use concrete and timely examples to ground their theories in reality. Instead of pointing out a problem and despairing, they delineate actionable steps relevant to anyone using digital technologies, even for the average "layperson" who just use sites such as Facebook ...more
Jul 07, 2021 rated it really liked it
I gained an education on how data is used and abused in service of power, and how to think clearly enough about it to do things right and better. Really enjoyed this book and will use its lessons to design more ethical, inclusive, and just systems, products, processes, and companies.
Jul 17, 2020 added it
Shelves: 2020, non-fiction
I have published a long text on data feminism in my blog post which you can find here.
Also, you can find a much shorter version here. Just expect some spoilers (if you can spoil non-fiction) :)

(view spoiler)
Jun 15, 2020 rated it it was amazing
This needs to be required reading for anyone working with or making decisions from data (yes that likely includes you). The authors not only construct an intersectional lens through which to view data science projects but also reflect on their work through the same lens to hold themselves accountable and to grow for the future. Numerous examples throughout the book illustrate seven clear principles that build a framework through which to design and conduct more empathetic, conscious and responsi ...more
Sep 24, 2020 rated it it was amazing
i think everyone (especially those in research) should read this book. it's a great overview on the situated nature of data and what we can do to fight back against and avoid perpetuating injustices in data work. it's, of course, not comprehensive of all the ways systemic oppression shows up in data science, but I think this would pair nicely with further reading on decolonizing science/indigenous science. ...more
Serena Canu
Feb 17, 2021 rated it it was amazing
I've found this book as a very good starting point to get an overview of the issues that might arise when we deal with data. I agree with other comments saying that it is not comprehensive, but I think it does its part ib suggesting new perspectives. It is well written and clear. I would've loved to have it as a text book during my Master courses. ...more
Feb 20, 2021 rated it really liked it  ·  review of another edition
"Data feminism is about power - about who has it and who doesn't."
4.5 stars
Super interesting book! Focuses on really important issues in data science (as well as important issues overall) today and changed my way of thinking about data.
Highly recommend! (and it is even freely available online!) (:
Taliesin Blue
Jan 22, 2021 rated it really liked it
Shelves: activism, nonfiction
An incredibly interesting read for people across all fields and identities. The authors try their best to be inclusive in language and content, but unfortunately, they still fall into some traps. For example, throughout the book they are complicit in making the struggles and challenges of transgender men invisible by lumping them in with cis men as though they had the same kind of privilege.
Therefore only 4 stars. Still, I can't recomment this enough.
(review updated 2021-04-10)

'data feminism' is an important book that has the potential to open many eyes to harms that can be perpetuated by data work. it opens with a clear and concise introduction to intersectional feminism, using numerous concrete examples that data scientists will easily grasp. the writing is fairly dense, but it is engaging, and i learned a lot.

in my mind there are two issues that keep the treatment in 'data feminism' from being definitive. the first has to do with the larg
Aug 30, 2020 rated it it was amazing
Data Feminism is a very interesting book and one that explores a more just, humane way to look and relate with data. I work with data in my day to day (as do an increasing number of people) and I really think the values explored in chapter 3 and beyond open new possibilities to working with data. I didn't include the first 2 since those 2 chapters while interesting in their own, were not as revolutionary to me.

I really like how the authors how the book practice what they preach and the documente
Kathleen Kernan
Aug 31, 2020 rated it liked it
This is a difficult book to read. It is difficult because the line length is too long. This might seem to be petty but line length is a 100-level data design concept. The authors have proposed to operate at the 400 or graduate level without an understanding of fundamental concepts. This is the most obvious but not the only instance of this in their work.

The ideas they raise should be considered by data designers. They are interesting and important. However, lenses can both clarify and obscure. T
The authors stand from an intersectional view of feminism, that is so ample, that sometimes it deals more with general social issues than with probles attaining women. So much so that these general problems are explaind for it general consequences, and not in how each particular problem affects women. Though it is interesting and well documented, I was looking for something more specific to women. I believe that trying to make feminism the mother of all lost causes can sometimes, at the end, inv ...more
Apr 11, 2021 rated it it was amazing
Shelves: 50book-2021, infodes
1: Black Feminist Thought, first published in 1990, Collins proposes the concept of the matrix of domination to explain how systems of power are configured and experienced.

As “data analysts” (low-status number crunchers) have become rebranded as “data scientists” (high status researchers), women are being pushed out in order to make room for more highly valued and more highly compensated men.

When data teams are primarily composed of people from dominant groups, those perspectives come to exert o
Mar 22, 2021 rated it did not like it
Ironically, this book is potentially more harmful than something which is less correct in its diagnosis of the problems associated to data science and data collection writ large.

This book repeatedly gets lots of things right, in terms of describing the problems that we see: the biases associated to data collection, the biases inherent in having machine learning systems developed by unrepresentative groups, the ways in which systems and data collection can reinforce existing (malicious) power str
Jun 24, 2021 rated it really liked it
It's an enjoyable and worthwhile book - but I'm going to have to echo the thoughts that Sanjida put in her excellent review ( )

So to state my position: I'm a programmer with no training in data science who sometimes deals with large and varied data sets. I live in the UK. I'm middle aged and middle income. I'm non-white and non-conforming in terms of gender expression and sexuality.

I found the book to be interesting and informative. Many of the examples g
Hasheemah Afaneh
Jan 26, 2021 rated it it was amazing
There is truly something for everyone in this book.

A central question to this book that the authors ask is, “How can we use data to remake the world?” The authors set out to answer this question by asking more questions (as researchers tend to do) about the way in which we deal with collecting, analyzing and interpreting data and how these actions are influenced by power structures, privilege hazard, data ethics and data justice. The book also centers the concept of intersectionality (which is w
Casey Browne
May 17, 2021 rated it really liked it  ·  review of another edition
Shelves: media-studies
This is a great read overall -- thoughtful, conceptual framework, well-used theory, a great message and a lively tone. I certainly found some beautiful lines/quotations and great new formulations for how to think & speak about these topics in my workplace.
My main question mark about it is that I'm not entirely sure who the audience is. If it's people with a background in feminist/intersectionality theory, it's fundamentally pretty basic info (although the examples used to illustrate them are cer
Steve Heitkamp
Dec 05, 2020 rated it it was amazing
Excellent book applying feminist concepts to the world of data. It is both well-written and interesting, with a host of examples emphasizing how thoughtful we need to be when thinking about getting and using data and how so much of the data we have is used for purposes it was not intended or fails to capture critical information.

As said in the book in the context of 'data for good' initiatives, "Doing good with data requires being deeply attuned to the things that fall outside the dataset and i
Roshni Sahoo
Dec 24, 2020 rated it it was amazing
i like chapter 2, chapter 5, chapter 6 the most. the book definitely made me think about 1) why certain objectives are prioritized in the machine learning community 2) the importance of the context of a dataset, and 3) made me realize HOW MUCH WORK good data science research for social impact requires.

Other tech + society books and articles I read focus a lot on the problems— gender data gaps or failure cases of automated systems but I liked that this group provided initial steps that we can tak
Feb 06, 2021 rated it it was amazing
Well-researched and engrossing. I loved how the authors highlighted various data science projects from underrepresented communities and showed projects that used nontraditional forms of data representation. The tables explaining the authors’ theoretical framework balance the narrative examples well, and the captions explaining the figures’ scope and the authors’ reason for including the figures are succinct and effective.

Lastly, the end of the book includes a refreshing audit of the project: Th
Aug 22, 2020 rated it it was amazing
I highly recommend this book to anyone who works with data (and really even to people who don’t). It looks as data analysis, visualization, reporting, documentation, etc. through the lens of intersectional feminism. The authors provide a framework for using data to help combat rather than reinforce structural oppression. Although the authors are white, they try to practice what they preach and ensure that diverse voices and view points are represented throughout. The book is published on glossy ...more
Eileen Breseman
Mar 15, 2021 rated it liked it
Point taken about how data can mislead. The authors lay out the premise in 5 segments and give examples and details to show who collects and distributes the data, in what form it is presented can easily skip marginalized groups (not just women as the title implies) that have not had a voice in it, and how it is collected and used. In some setups that are meant to be a blind unbiased AI algorithms, it can tend to skew the information further based on what is already in the system. Much is unconsc ...more
Soumya Suresh
Jun 06, 2021 rated it really liked it
Data Feminism is a book that primarily targets data scientists and those engaged in dealing with or using data. But as a student who has looked for data to understand things better or to prove my point or aid in research, this book has been an eye-opener. Sadly, I used to believe that numbers spoke for themselves and that numbers never lie. But not anymore. Now I can't look at visual representations of data without wondering I am seeing the real picture or not. Now I know that everything from wh ...more
Jan 07, 2021 rated it it was amazing
If you are familiar with the fields of data ethics and socially-responsible AI/data science, a lot of the discussions and projects within Data Feminism aren't going to be new to you. However, if you aren't familiar, this is an excellent introductory text. The book is well-outlined and clearly written and would probably be a great introductory textbook for a freshman-level or survey college course.

My only criticism is the lack of projects from beyond the US. There are a few in the book, as I reca
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“the privilege hazard: the phenomenon that makes those who occupy the most privileged positions among us—those with good educations, respected credentials, and professional accolades—so poorly equipped to recognize instances of oppression in the world.29” 1 likes
“I’m forced to choose ‘female’ over ‘male’ every single time, because that’s what my passport says, and ... being non-binary is still not legally recognised in the UK,” Munir explains.” 0 likes
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