AT THE TIME of finishing this manuscript (June 2017), Donald Trump has been in the White House for only five months. Exactly how his administration will deal with open and closed data and the surveillant capacities of the state is still unfolding. With regard to dataveillance, Trump chose a CIA director (Mike Pompeo) and an attorney general (Jeff Sessions) sympathetic to the restoration of Section 215 of the USA PATRIOT Act that, among other things, allowed for the bulk collection of Americans’ phone data (see Sherfinski 2015). Moreover, Trump has expressed a general commitment to increased securitization. In an interview with Yahoo! News, for example, Trump warned, “We’re going to have to do things that we never did before. . . . And certain things will be done that we never thought would happen in this country in terms of information and learning about the enemy. And so we’re going to have to do certain things that were frankly unthinkable a year ago” (quoted in Walker 2015). Ironically, Trump and his associates are also experiencing the glare of the surveillant state in the form of intelligence suggesting some form of collaboration with Russia during the presidential election campaign. With respect to open government data, Trump has not explicitly denounced it, but given that, on the campaign trail, he promised to rescind “every single Obama executive order” (quoted in Kopan 2016), the existence of the executive order of 2013 making open and machine readable the new default for government information is precarious.
The uncertain future of both Data.gov and the principle of openness that informs it leads to the possibility that a neoliberal data-driven transparency that contributes to shareveillant subjectivity is better than no transparency at all. In response to this, I would argue that Trump’s style of politics means that calling for more (of the same) transparency in the form of open data might miss the point. The case of Trump’s nondisclosure of tax returns illustrates this. According to a poll conducted by Quinnipiac University in August 2016, 62 percent of Republicans wanted to see Trump release his tax returns during the presidential race. However, his continued nondisclosure did not turn out to be a deal breaker for that demographic. Routine transparency measures would have necessitated the publication of Trump’s taxes; but even if such a provision had been in place, Trump’s claim during the first presidential debate in September 2016 that not paying federal income tax “just made [him] smart” seemed to chime with a prevailing anticommunitarian, antistate, and survival-of-the-fittest spirit. Perhaps this pertains to Judith Butler’s comment that Trump “lives above the law, and that is where many of his supporters also want to live” (quoted in Salmon 2016). It certainly does not feel as though open data-driven transparency will be up to the job of keeping a Trump administration in check, because Trump seems unconcerned if his worst excesses are revealed. Often, he is the source of those “revelations.”
All kinds of misdemeanors and malfeasance came to light during Trump’s campaign (sexism, racism, “ableism”), hardly any of which affected his popularity among core supporters. In response to new evidence of bad behavior, Trump was praised for “straight talking” beyond establishment political correctness, for “telling it like it is,” even if that meant using “post-truth” tactics that require neither logic nor evidence. His candid and undiplomatic tweets are exemplary in this regard. It is easy to cast this populist rhetorical strategy as itself an obfuscating performance of openness. The relationship here between concealment and revelation is complex. As Geoffrey Bennington (2011, 26) comments, “uncovering secrets always might unveil the fact that the truth this revealed is part of a greater system of secrecy, and merely a supplementary fold in the structure of veiling itself. Enlightenment always might in fact be the dupe of apparent transparency, and transparency might still be a kind of veil.” Such logic pertains as much to shareveillant transparency as it does to Trump’s “frank” mode of commentary.
What of the data that has already been shared with its public? In early 2017, transparency advocates, political historians, archivists, and environmental activists were busy backing up federal data sets and Web pages for fear that a Trump administration will take down what is available (Gerstein 2016). For example, the End of Term Web Archive called for assistance with its “End of Term Presidential Harvest.” This was a collaboration between a group of university, nonprofit, and government libraries. It called on technologically competent researchers to identify federal Web pages in need of preservation for the record. Because of the technological restrictions sometimes placed on downloading data even while that data can be searched in multiple ways online, data sets present a particular problem for archivists; much open data is therefore still vulnerable, despite Web archiving.
Concern about loss of data (a move not from “open” to “closed” in the terms that I have been discussing, but “open” to “erased”) extends beyond the library community. This has prompted Abbie Grotke of the Library of Congress to comment, “This year, we’ve seen a lot of these activities just sprout up. We are losing control a little bit” (quoted in Gerstein 2016). She could be referring to events such as the University of Toronto’s “Guerrilla Archiving Event: Saving Environmental Data from Trump” on December 17, 2016: an organized hackathon intended to assist the efforts of the End of Term Web Archive to preserve information and data from the Environmental Protection Agency, especially data relating to climate change and water, air, and toxics programs. Grotke might, however, also be thinking of lone operators like Maxwell Ogden, a programmer for the open data sharing project Dat Project, who decided to archive all nine gigabits of the data on the Obama administration’s open.whitehouse.gov pages on Inauguration Day (see Lynch 2017), or Russ Kick, who established the Memory Hole, which archives deleted Web pages and social media feeds relating to Trump. Kick’s endeavor is obviously concerned with preserving a different form of content to that contained by data sets but is nevertheless prompted by concerns regarding accountability and the public record that also shape a desire to preserve statistical data.
Once Trump came into office, any indication that data was going missing or being displaced was met with concern. For example, Meritalk, a public–private news outlet focused on government information technology, ran an article reflecting the unease in transparency quarters that data on open.whitehouse.gov had been badly archived in formats that meant data was compromised in terms of usability (Lynch 2017). In fact, deleting federal records is against the law, and because of the multiple copies made of key data such as that recorded by NASA’s Lunar Reconnaissance Orbiter, it is almost impossible for some data sets to disappear. Consequently, science journalist Megan Molteni (2017) comments that citizens should be less worried about archiving existing data and more concerned about making sure that data sets are renewed, something that the Trump administration has not committed to: “Archiving is inherently static. . . . Datasets, on the other hand, are dynamic. And keeping open data pipelines, and the funding that makes them possible, is what scientists and concerned citizens should really be worried about.” A commitment to feeding data sets with new content is in the balance. Although the Senate passed the Open Government Data Act at the end of the 114th congress, the act has yet to pass in Congress. Though traditionally a bipartisan issue, open government data may well feel overly associated with the Obama administration to pass during Trump’s presidency.
Despite clear limitations, guerilla archiving practices could still constitute examples of “commoning.” Of preserving data and information for future, unanticipated, and as yet unknown forms of sharing, which transcend the sometimes shareveillant origin and context of the data concerned? This uncontrolled dissemination and use of open data that operates without reference to the data economy is one response to the present political climate in the United States. I suspect a tactical opacity will also be an important tool when closed data practices like dataveillance are put in the service of “post-truth” discursive formations that trade in fear to demarcate insiders and outsiders on the basis of apparently legible, “transparent,” and knowable identities like “the Muslim” or “the illegal immigrant.” Sharing and veillance may well have a different relationship in this new distribution, and we will have to intervene accordingly.