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.
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I’ve experienced first hand the challenges of trying to correct misinformation, and in part my academic research builds on that experience and tries understand why it was that so much of what we did at Spinsanity antagonized even those people who were interested enough to go to a fact-checking web site.
What is it about our brains that makes facts so challenging, so odd and threatening? Why do we sometimes double down on false beliefs? And maybe why do some of us do it more than others?
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.
In 2011, the cultural critic Emily Nussbaum reflected on the flowering of online feminism through new publications, social media conversations, and digital organizing. But Nussbaum worried, even if you can expand the supply of who’s writing, will that actually change the influence of women’s voices in society? What if online feminism was just an echo chamber?
We have to ask who’s creating this technology and who benefits from it. Who should have the right to collect and use information about our faces and our bodies? What are the mechanisms of control? We have government control on the one hand, capitalism on the other hand, and this murky grey zone between who’s building the technology, who’s capturing, and who’s benefiting from it.
We have increasingly smart, surveillant persuasion architectures. Architectures aimed at persuading us to do something. At the moment it’s clicking on an ad. And that seems like a waste. We’re just clicking on an ad. You know. It’s kind of a waste of our energy. But increasingly it is going to be persuading us to support something, to think of something, to imagine something.
It’s paramount that our society recognize the role of anti-black structural racism in the US. And that our 21st century multiracial social movements uplift and centralize the issues of those community members who are impacted and are living at the margins. We know that if we do, we’ll get closer to real justice for all of us. Moreover, it’s been widely documented that the gains made by and with the black community have always led to better standards of living for all of us.
I wouldn’t be surprised to find out that many of us here today like to see our work as a continuation of say the Tech Model Railroad Club or the Homebrew Computer Club, and certainly the terminology and the values of this conference, like open source for example, have their roots in that era. As a consequence it’s easy to interpret any criticism of the hacker ethic—which is what I’m about to do—as a kind of assault.
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.