How an Algorithmic World Can Be Undermined

All they have to do is write to jour­nal­ists and ask ques­tions. And what they do is they ask a jour­nal­ist a ques­tion and be like, What’s going on with this thing?” And jour­nal­ists, under pres­sure to find sto­ries to report, go look­ing around. They imme­di­ate­ly search some­thing in Google. And that becomes the tool of exploita­tion.

Algorithms of Oppression: How Search Engines Reinforce Racism

One of the things that I think is real­ly impor­tant is that we’re pay­ing atten­tion to how we might be able to recu­per­ate and recov­er from these kinds of prac­tices. So rather than think­ing of this as just a tem­po­rary kind of glitch, in fact I’m going to show you sev­er­al of these glitch­es and maybe we might see a pat­tern.

Data & Society Databite #101: Machine Learning: What’s Fair and How Do We Decide?

The ques­tion is what are we doing in the indus­try, or what is the machine learn­ing research com­mu­ni­ty doing, to com­bat instances of algo­rith­mic bias? So I think there is a cer­tain amount of good news, and it’s the good news that I want­ed to focus on in my talk today.

Forbidden Research: Why We Can’t Do That

Quite often when we’re ask­ing these dif­fi­cult ques­tions we’re ask­ing about ques­tions where we might not even know how to ask where the line is. But in oth­er cas­es, when researchers work to advance pub­lic knowl­edge, even on uncon­tro­ver­sial top­ics, we can still find our­selves for­bid­den from doing the research or dis­sem­i­nat­ing the research.