They’re everywhere, but nobody wants to know about it.

Amazon.com Inc's  machine-learning specialists uncovered a big problem: their new recruiting engine did not like women.

While privacy and surveillance affect different populations in disparate ways, they are often treated as monolithic concepts by journalists, privacy advocates, and researchers. Achieving privacy is especially difficult for those who are marginalized in other areas of life. This special issue interrogates what privacy looks like at the margins, investigating a broad spectrum of issues, methodologies, and contexts. Many make an intervention into mainstream theories of privacy and surveillance, showing how examining the experiences of individuals outside the normative white, American, middle-class subject often complicates assumptions about how privacy operates. Others examine the mundane and the banal in order to analyze how power relations play out in everyday life. By incorporating research outside the canon of privacy research, and by advocating for projects that discuss more diverse conceptualizations of “the user” or the subject, we can envision a future for privacy scholarship that incorporates a wider set of harms and needs, and encompasses the concerns of a larger base of citizens.

When her win was announced, a search for Donna Strickland’s name on Wikipedia turned up nothing.

A few weeks ago, I declined to participate in a radio conversation on the topic of who “belongs” in computer science. This decision has…

It’s that time again. Regular like clockwork, it seems to happen each September. Something happens, and suddenly webdev twitter is taken over with a battle royale over the value of CSS. Time for half the front-end development world to dismiss the value of the other half.

This is the old version of these slides. The newer ones are at https://noidea.dog/glue Your job title says "engineer", but you seem to spend most of your time …

Michelle Moravec Millions of the sex whose names were never known beyond the circles of their own home influences have been as worthy of commendation as those here commemorated. Stars are never seen either through the dense cloud or bright sunshine; but when daylight is withdrawn from a clear sky...

Trigger warning: please note that this is a blog post about online abuse, and includes screen caps of tweets sent to me. Graphic threats and abusive, hateful language toward women appear therein.   A few weeks ago, I gave a keynote talk at World Domination Summit in Portland. The thesis: while we regard online misogyny and abuse…

Nature - Computer scientists must identify sources of bias, de-bias training data and develop artificial-intelligence algorithms that are robust to skews in the data.

Although every other major website manages somehow.

Maria O’Hara (Reading List Services Support Co-Ordinator) outlines why we need to question the existing structures of the Library, namely our classification system -Dewey Decimal – a sy…

This paper extends the scholarship on gender and scientific authorship by exploring women’s involvement in editorial decision-making. Prior to 1945, women scientists could submit their work to the journals of the Royal Society, but they were excluded from all editorial and evaluation roles: such gate-keeping roles were reserved for Fellows of the Society. We draw upon the Society’s archive to examine the experiences of female authors, referees, and communicators in the period after women were admitted to the Fellowship. We investigate the involvement of women in both anonymous roles (e.g. as referees), and in publicly visible positions of editorial responsibility (e.g. as communicators, and committee chairs). We reveal that women were better represented in both types of roles in the 1950s than in the 1970s and 1980s. These findings are pertinent to current debates about bias in the peer-review system, and the gendering of academic reward and recognition structures.

Makerspaces may be one of the most exciting elements on any school’s campus. But a lack of focus around culture and gender inclusiveness are stunting ...

The blind application of machine learning runs the risk of amplifying biases present in data. Such a danger is facing us with word embedding, a popular framework to represent text data as vectors...

The removal of an old joke from the GNU C Library manual might not seem like the sort of topic that would inspire a heated debate.  At times, though, a small action can serve as an inadvertent proxy for a more significant question, one which is relevant to both the developers and the users of the project.  In this case, that question would be:  how is the project governed and who makes decisions about which patches are applied?

Homophily sucks.

A remarkable new study documents the experiences of women in an open office designed by men.