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Data and government transparency in the Trump era - Can data-driven technologies help?

This article appears in the issue February 2017 [Volume 26, Issue 2]
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Historically, the federal government has been regulated by a series of carefully constructed checks and balances exemplified by the executive, judicial and legislative branches. That triad was designed to circumscribe individual authority, implement a degree of transparency and order and preserve the democratic process upon which the country is based.

Yet with each new headline surrounding security breaches, social media, email servers, big data and its impact upon the public sector, it has become ever more difficult to deny the emergence of what well could be a fourth “branch” of checks and balances, an unpredictable maverick which, if properly controlled, could possibly provide the sort of transparency vital to 21st century democracy: data.

The utility of data-centered practices in rendering transparent accountability of the public sector within this decade alone is staggering. Three codifications, each with varying degrees of conviction and resonance within political circles, are the forerunners for the substantiation of this claim:carefully constructed checks and balances exemplified by the executive, judicial and legislative branches. That triad was designed to circumscribe individual authority, implement a degree of transparency and order and preserve the democratic process upon which the country is based.

Yet with each new headline surrounding security breaches, social media, email servers, big data and its impact upon the public sector, it has become ever more difficult to deny the emergence of what well could be a fourth “branch” of checks and balances, an unpredictable maverick which, if properly controlled, could possibly provide the sort of transparency vital to 21st century democracy: data.

The utility of data-centered practices in rendering transparent accountability of the public sector within this decade alone is staggering. Three codifications, each with varying degrees of conviction and resonance within political circles, are the forerunners for the substantiation of this claim:

open data—The most prominent is likely the open data movement, buttressed by the growing interest in the accessibility of public sector data as a means of reinforcing compliance with public policy. Typified by the site data.gov (implemented during the Obama administration), this movement was engendered to facilitate transparency.

revelatory data—The numerous revelations regarding illicit activities substantiated by data technologies are possibly the most convincing examples of the need for greater transparency within the public sector. In most of those instances, data-driven practices were instrumental in determining the extent of impropriety and its exposure to the general population. Former Secretary of State Hillary Clinton’s private email servers and the Panama Papers are just some of the many examples of how data technologies are invaluable to increasing transparency in the public sector.

security breaches—Employing security breaches as a means of using data to enhance transparency in the public sector is dichotomous, at best. On the one hand, they highlight data’s innate vulnerabilities to intruders, as indications of Russia’s attempts to compromise Democratic and Republican servers prior to the 2016 presidential election reveal. Nonetheless, security breaches also demonstrate data’s propensity to affect accountability even when it’s undesired by the violated party, as demonstrated by the 2015 data breach of Ashley Madison, which resulted in substantial reforms to the dating website’s policies.

Each of those stratifications for data’s potential to increase governmental transparency demonstrates a marked effect on the public sector. Still, data’s longstanding utility in that regard—the penchant for reinforcing checks and balances as opposed to reinforcing criminal activity—depends on the ability to solve a pivotal conundrum: Can they do so more advantageously than disadvantageously? More holistically than individually? And most importantly, can they reinforce transparency in a controlled, sustainable way that is transparent itself?

Political influence

The political influence of data technologies was inestimable in the most recent presidential elections. Many have characterized the 2008 election outcome as highly influenced by social media, whereas the 2012 outcome is almost universally renowned as an affirmation of big data’s sway in the electoral process. Data’s virtue in increasing public sector transparency is also partially evinced by the 2016 rendition in which the newly elected president allegedly spent millions on an overseas big data analytics firm. Big data analytics are predicated on aggregation: The more sources and amounts of data involved, the better they are.

Aggregating everything from voter turnout ratios by location to consumer spending habits enables those analytics, which also encompass social media activity, to determine who is likely to vote for a particular candidate and which issues are the most influential for doing so. Those digital behavioral tracking analytics provide targeted campaign efforts via emails (with differing campaign contribution amounts), social media interaction and browser-based or television advertising centered around the issues most meaningful to voters.

Some of the same methodology can be used to reinforce government transparency for the current presidential administration—particularly the involvement of social media, which is significant as both an analytics source and medium for targeted segmentation responses. As president-elect at the time of this writing, Donald Trump has evidenced few signs of abating his continual Twitter (twitter.com) usage, a real-time mechanism for not only gleaning current administration developments but also responding to them for greater public awareness. Aggregating such data with tweets from his election campaign (campaign promises, stances on social/political issues), data from his diversity of private sector interests, relevant public open data and contemporary public sector news provides a rich array of sources similar to those of the habits of individual voters. Technologies such as graph-based analytics can showcase discreet relationships between data elements in a visual manner, which could potentially elucidate developments in the executive branch and their correlation to contemporary events, which might otherwise elude public notice.

Data-driven investigations

That premise becomes even more palpable when one considers the investigative potential of data-driven practices, especially when used to parse through acts of impropriety in the public sector. There are several ways in which data-driven technologies can underscore transparency, if by no other means than functioning as deterrents for potential illicit actions. Clinton’s deployment of private email servers for government communication illustrates a wide range of data capabilities in that regard. Although data technologies weren’t responsible for the initial discovery of those private servers—which became known when, in accordance to public policy, federal officials reviewed Clinton’s email records following her term as Secretary of the State—they’re invaluable for determining the extent of any unsanctioned actions. Semantic graph technologies can swiftly trace data provenance to determine the point of origination of emails and other classified data from an innumerable amount and variety of sources, supporting analytics ascertaining which records contained sensitive government information and who accessed them.

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