“The debate over the terms and goals of accountability must not stop at questions like “Is the data processing fairer if its error rate is the same for all races and genders?” We must consider broader questions, such as whether these tools should be developed and deployed at all.”
“The dispute over how to reform or restrict algorithms is rooted in a conflict over to whom algorithmic processes should be accountable. If it’s to a community of engineers and technocrats, then accountability will usually mean more comprehensive data collection to produce less biased algorithms. If it is accountability to the public at large, there are broader issues to consider, such as what limits should be placed on these tools’ use and commercialization, if they should even be developed at all.”
It’s all too quotable.
Frank Pasquale also recommends reading Safiya Umoja Noble and Virginia Eubanks:
“Scholars like Noble and Eubanks need to be at the center of future conversations about algorithmic accountability. They have exposed deep problems at the core of the political economy of information, in data-driven social control. They diversify the forms of expertise and authority that should be recognized in the development of better socio-technical systems. And they are not afraid to question the goals — and not simply the methods — of powerful firms and governments, foregrounding the question of to whom algorithmic systems are accountable.”