Paul N. Edwards

I'm a Professor in the School of Information and the Dept. of History at the University of Michigan. My research explores the history, politics, and cultural aspects of computers, information infrastructures, and global climate science. I also direct (sometimes) the University of Michigan Science, Technology & Society Program. You can find out more about me, my background, and my current research at my personal website, pne.people.si.umich.edu. A little personal history: I went to graduate school in the 1980s, at the height of the Carter-Reagan Cold War. That was a very scary time, and not only because the risk of nuclear war reached heights unseen since the Cuban missile crisis. First acid rain, then the ozone hole, then the issue of "nuclear winter" -- a global climate catastrophe caused by the smoke and dust from a superpower nuclear war -- made it clear that human activity could seriously affect the global atmosphere. I wrote my dissertation about computers' central role in the American side of the Cold War. In the 1950s, military projects from hydrogen bomb design to continental air defense to nuclear strategy all spurred computer development, with massive government support. Computers became icons for that era's widespread technological hubris: the idea that technology could deliver panoptic surveillance, global control, and ultimate power. That story was the subject of my first book, The Closed World: Computers and the Politics of Discourse in Cold War America (MIT Press, 1996). It's also what led me to co-edit, with Peter Taylor and Saul Halfon, the cultural studies collection Changing Life: Geneomes, Ecologies, Bodies, Commodities (U. of Minnesota Press, 1997). The nuclear winter controversy arose from applying climate models to the effects of nuclear war. So it wasn't really a long step for me to begin studying how computer models interacted with the politics of climate change. Even before I finished The Closed World, I was deeply engaged in that research. For years I worked intensively with famed climate scientist Stephen Schneider, who died in 2010. I interviewed dozens of climatologists and computer modelers. I spent countless days at scientific meetings and visited climate labs around the world. Along the way I co-edited, with Clark Miller, a collection of Science & Technology Studies perspectives on climate science and politics: Changing the Atmosphere: Expert Knowledge and Environmental Governance (MIT Press, 2001). While I was researching climate science during the 1990s, climate politics exploded. But by around 2000, the main scientific controversies had settled out, and the concerted campaign to cast doubt on climate science--heavily funded by the coal and oil industries--seemed to be losing steam. Then George W. Bush's administration revived the false controversies. Political appointees doctored scientific reports and attempted to muzzle government scientists such as James Hansen. By the time I was finally wrapping up the manuscript of A Vast Machine in the summer of 2009, Barack Obama was president and carbon-pricing bills seemed likely to move swiftly through Congress. Once more, I thought the controversies had finally ended and that A Vast Machine would fizzle into obscurity. Instead, in November 2009 -- less than a month after I submitted the final page proofs -- "Climategate" made headlines and helped derail the Copenhagen climate talks. Someone -- probably a disaffected insider -- released climate data and thousands of private emails among scientists from the Climatic Research Unit in the United Kingdom. Climate change skeptics (or denialists, as most of them should really be called) made a lot of noise about what they call "manipulation" of climate data. Their allegations illustrated exactly the conundrum A Vast Machine reveals: as a historical science, the study of climate change will always involve revisiting old data, correcting, modeling, and revising our picture of the climatic past. This does not mean we don't know anything. (We do.) And it also does not mean that climate data or climate models might turn out to be wildly wrong. (They won't.) To find out why, well... you might want to read A Vast Machine.