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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. 

Automation and Algorithms in the Digital Age

I want to think more broad­ly about the future of cyber state, and think about accu­mu­la­tions of pow­er both cen­tral­ized and dis­trib­uted that might require trans­paren­cy in bound­aries we wouldn’t be used to.

Marika Cifor at Biased Data

What I’m argu­ing pri­mar­i­ly today is that focus­ing on ped­a­gogy is a key aspect of social jus­tice work, and that teach­ing crit­i­cal data lit­er­a­cy along with oth­er dig­i­tal lit­er­a­cy skills is a key part of what we need to do.

Biased Data Panel Q&A

We’re los­ing our abil­i­ty to for­get the things that should be for­got­ten. Wait until you try to run for Senate or Congress, some of you in this room, and some pic­tures or text roll up.

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