danah boyd at Points: “….Knowing how to use data isn’t easy. One of my colleagues at Microsoft Research — Eric Horvitz — can predict with startling accuracy whether someone will be hospitalized based on what they search for. What should he do with that information? Reach out to people? That’s pretty creepy. Do nothing? Is that ethical? No matter how good our predictions are, figuring out how to use them is a complex social and cultural issue that technology doesn’t solve for us. In fact, as it stands, technology is just making it harder for us to have a reasonable conversation about agency and dignity, responsibility and ethics.
Data is power. Increasingly we’re seeing data being used to assert power over people. It doesn’t have to be this way, but one of the things that I’ve learned is that, unchecked, new tools are almost always empowering to the privileged at the expense of those who are not.
For most media activists, unfettered Internet access is at the center of the conversation, and that is critically important. Today we’re standing on a new precipice, and we need to think a few steps ahead of the current fight.
We are moving into a world of prediction. A world where more people are going to be able to make judgments about others based on data. Data analysis that can mark the value of people as worthy workers, parents, borrowers, learners, and citizens. Data analysis that has been underway for decades but is increasingly salient in decision-making across numerous sectors. Data analysis that most people don’t understand.
Many activists will be looking to fight the ecosystem of prediction — and to regulate when and where prediction can be used. This is all fine and well when we’re talking about how these technologies are designed to do harm. But more often than not, these tools will be designed to be helpful, to increase efficiency, to identify people who need help. Their positive uses will exist alongside uses that are terrifying. What do we do?One of the most obvious issues is the limited diversity of people who are building and using these tools to imagine our future. Statistical and technical literacy isn’t even part of the curriculum in most American schools. In our society where technology jobs are high-paying and technical literacy is needed for citizenry, less than 5% of high schools offer AP computer science courses. Needless to say, black and brown youth are much less likely to have access, let alone opportunities. If people don’t understand what these systems are doing, how do we expect people to challenge them?
One of the most obvious issues is the limited diversity of people who are building and using these tools to imagine our future. Statistical and technical literacy isn’t even part of the curriculum in most American schools. In our society where technology jobs are high-paying and technical literacy is needed for citizenry, less than 5% of high schools offer AP computer science courses. Needless to say, black and brown youth are much less likely to have access, let alone opportunities. If people don’t understand what these systems are doing, how do we expect people to challenge them?
We must learn how to ask hard questions of technology and of those making decisions based data-driven tech. And opening the black box isn’t enough. Transparency of data, algorithms, and technology isn’t enough. We need to build assessment into any system that we roll-out. You can’t just put millions of dollars of surveillance equipment into the hands of the police in the hope of creating police accountability, yet, with police body-worn cameras, that’s exactly what we’re doing. And we’re not even trying to assess the implications. This is probably the fastest roll-out of a technology out of hope, and it won’t be the last. How do we get people to look beyond their hopes and fears and actively interrogate the trade-offs?
Technology plays a central role — more and more — in every sector, every community, every interaction. It’s easy to screech in fear or dream of a world in which every problem magically gets solved. To make the world a better place, we need to start paying attention to the different tools that are emerging and learn to frame hard questions about how they should be put to use to improve the lives of everyday people.
We need those who are thinking about social justice to understand technology and those who understand technology to commit to social justice….(More)”
Transparency has hit the headlines. In the wake of evidence that many research findings are not reproducible, the scientific community has launched initiatives to increase data sharing, transparency and open critique. As with any new development, there are unintended consequences. Many measures that can improve science — shared data, post-publication peer review and public engagement on social media — can be turned against scientists. Endless information requests, complaints to researchers’ universities, online harassment, distortion of scientific findings and even threats of violence: these were all recurring experiences shared by researchers from a broad range of disciplines at a Royal Society-sponsored meeting last year that we organized to explore this topic. Orchestrated and well-funded harassment campaigns against researchers working in climate change and tobacco control are well documented. Some hard-line opponents to other research, such as that on nuclear fallout, vaccination, chronic fatigue syndrome or genetically modified organisms, although less resourced, have employed identical strategies….(