Trading Federal Data - Ethical and Transparency Considerations

Trading Federal Data:

Ethical and Transparency Considerations

By Alon Peled

Department of Political Science and Public Administration The Hebrew University of Jerusalem

Mt. Scopus Jerusalem 91905

Israel [email protected]

Abstract1

Can we develop an ethical and transparent system which will incentivize self-centered Federal agencies to expand electronic information sharing? I provide data to demonstrate the Obama Administration's Open Data program (designed to address this question) had failed. I argue that Open Data architects failed because they did not understand the inherent contradiction between their transparency vision ("free all data to the web") and the way Federal departments and agencies collaborate via information trading. Senior bureaucrats, I explain, remain unwilling to "free" information assets that define their political status. Hence, these bureaucrats adopted a passive-aggressive behavior toward Open Data. They released minimal amount of information in order to "comply" with the Open Government Directive (OGD) and have been sitting idle thereafter. I propose an alternative approach to increase information sharing in the US Federal government by erecting an internal Federal Information Marketplace (FIM) within which agencies will trade information assets vis-à-vis each other for profit. FIM's opponents will utilize the first amendment and the Freedom of Information Act to argue that Federal data ought to remain free of charge, that FIM will expand greed and egotism in governmental work, and that, if successful, FIM will pave the way to an irreversible Big Brother government. I provide some solutions to these ethical and transparency challenges and argue that has the potential to complement the FOIA-based information ecology, to thicken trust among trading-agencies, and to create new defense mechanisms against Big Brother government.

1 Portions of this paper are included in three other manuscripts and are currently under review for publication by the American Political Science Review, Public Administration Review, and Public Administration

Alon Peled, "Trading Federal Data," Paper presented at the "Organizational Transparency and Ethics" conference, Tel Aviv University, December 29 2010

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Trading Federal Data: Ethical and Transparency Considerations

Can we develop an ethical and transparent system which will incentivize self-centered Federal

agencies to expand electronic information sharing? Immediately after his election, President Obama

launched an Open Data campaign to address this challenge by mandating that Federal departments and

agencies publish all data on www.data.gov. I provide here data to argue that the Open Data program had

failed. I argue that Open Data architects failed because they did not understand the inherent contradiction

between their vision of transparency ("free all data to the web") and the way Federal departments and

agencies collaborate via information trading. Senior bureaucrats, I explain, remain unwilling to "free"

information assets that define their political status in Washington, DC. Hence, these bureaucrats adopted a

passive-aggressive behavior toward Open Data. They released minimal amount of information in order to

"comply" with the Open Government Directive (OGD) and have been uploading virtually nothing since

making this initial contribution. In contrast to its glitzy public relations image, the public already

discovered the poor value of data.gov and the number of downloads from data.gov has remained abysmal.

I propose an alternative marketplace-based approach to improving inter-agency electronic

information exchanges. This approach is based on the erection of a new internal Federal Information

Marketplace (FIM) in which Federal departments and agencies will buy and sell datasets from and to each

other. I highlight three ethical and transparency critiques of this marketplace approach. First, critics may

argue that citizens must not pay twice for Federal data and that the dictates of the Freedom of Information

Act (FOIA 1966) are incompatible with this marketplace approach. Second, critics may suggest that the

proposed marketplace approach will expand greed in governmental work by teaching bureaucrats that

everything is for sale. Finally, critics may suggest that an efficient marketplace approach would give birth

to a Big Brother government. In response to these challenges, I suggest how FIM might complement

FOIA, how FIM will increase and thicken (via trade) inter-agency trust, and how FIM might create new

powerful mechanisms to defend citizens from the danger of Big Brother government.

The most transparent White House in history?

Already while campaigning, candidate Obama promised to create the most transparent White House

in history (Roberts 2006 19). During the 77 days between election-day and inauguration-day, the Obama-


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Biden Transition Project commissioned a Technology, Innovation, and Government Reform (TIGR) team

to prepare the Open Government program (Noveck 2009). Federal agencies had much to lose to this

openness onslaught (Weber et al. 1991 ; Henschen 2010). Senior officials feared that the new 'fishbowl

transparency' policy will be costly, discourage their troops from holding frank internal discussions, and

chase away private sector actors who will no longer agree to share data with government (Coglianese

2009 ; Crozier and Friedberg 2009 ; Meier and Bohte 2007 ; Stiglitz 2003).

Open Data architects launched a blitzkrieg-style campaign to enforce the new program. On his first

full day in office (January 21 2009), at the height of the worst economic crisis America had experienced

since the Great Depression, President Obama signed three memorandums and two executive orders. Four

of these five documents promoted open government (The White House - Office of the Press Secretary

2009). In March 2009, Vivek Kundra was appointed as the first-ever Federal Chief Information Officer

(CIO). On March 19 2009, Holder, the new Attorney General reversed the Ashcroft memorandum of

October 12 2011 and declared that "in the face of doubt, openness prevails" (Ashcroft 2001 ; Holder 2009).

A barrage of new open government initiatives surfaced including eRulemaking, IT Dashboard,

Revovery.gov, and USASspending.gov. On May 21st 2009, the 120-day anniversary of the President's

Open Government Memorandum, a team headed by the CIOs of the Department of Interior and the

Environmental Protection Agency (EPA) launched www.data.gov (OMB 2009)

Then, on December 8 2009, OMB published the Open Government Directive (OGD). OGD ordered

Federal agencies to make available online as much information as possible (Economist 2010a). The

directive provided a list of concrete deadlines and milestones that each agency had to comply with.

Agencies were instructed, each, to publish at least three high-value datasets on the web. High value

datasets were defined as ones that increased an agency's accountability and responsiveness, improved the

public knowledge of the agency, furthered the core mission of the agency, created economic opportunity,

or responded to a need identified through public consultation (OMB 2009 7-8). These datasets also had to

be ones never before made available online and be published in a downloadable and open format

accessible to anyone. OGD also commanded each agency to publish an Open Government plan and web

site (The White House 2009). Through these executive acts, senior level appointments and "bully pulpit"

evangelism, Open Data grew rapidly from an abstract idea to become a powerful doctrine.


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The Failure of Open Data in Numbers

Critics have argued that Open Government has failed to deliver. For example, only one bill (barely)

out of Obama's first eleven signed bill saw sunlight before signing (Harper 2009 ; Henry 2009). The new

administration also blocked the court-ordered release of photographs depicting the abuse of detainees held

by US authorities abroad and continued to support the former administration's eavesdropping program.

Frustrated, several critics even suggested that, in practice, the Obama Administration surpassed the radical

secrecy and immunity claims of the previous Bush administration (Greenwald 2009 ; Wilson 2009). Other

critics argued that programs like recovery.gov provided little beyond news releases, general breakdowns of

spending, and acronym-laden spreadsheets. Two critics concluded that the Open Government program

promised more than it could deliver and raised unrealistic "openness" expectations (Coglianese 2009;

MacGillis 2009). Yet, until now, Open Data remained the universally non-criticized alleged successful

crown jewel in the Obama Administration's Open Government program.

It has been tricky to develop an independent 'back door' methodology to measure empirically the

impact of Open Data. Open Data architects created a public relations buzz that continues to characterize

this program to date. Scholars uncritically publish facts released to them by Open Data (Lakhani et al.

2010). Only one scholar actually examined the first batch of released datasets and concluded that there was

little high value in these data sets (Harper 2010). Open Government architects also converted the OGD into

a self-assessment questionnaire that agencies had to complete in order to publish an "Open Government

Dashboard" (The White House 2010; The White House 2010). Unsurprisingly, most agencies awarded

themselves with the highest marks. Data.gov actually neither responded to this author's inquiries to release

data about itself nor to pleas of its most ardent fans to respond to their suggestions.

Fortunately, Open Data architects left a small yet significant backdoor open to measure their

program empirically. Over the past year, I have downloaded and studied Open Data metrics regarding what

agencies publish on www.data.gov and how frequently the released data is downloaded by the public.2

Below are some of the main findings for the period between May and October 2010 (encompassing 94

Departments, Federal agencies and independent agencies over a period of 21 weeks):

2 The complete statistical analysis of these findings is part of another manuscript titled "Why Open Data Closes Doors" currently under review for publication by the American Political Science Review


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§ The vast majority of agencies uploaded a small number of high value data sets by the designated OGD deadline (January 22 2010) but have not uploaded additional high value data sets since then. About 77% of all departments and agencies did not add even a single new high value data set to www.data.gov after their initial minimal contribution to this site.

§ Only a handful of agencies created high end tools. 86% of all departments and agencies created no tools and a single agency (National Oceanic and Atmospheric Administration) accounted for 75% of all the 'high value tools' uploaded into www.data.gov. The same findings are true for departments and agencies uploading non high-value tools.

§ Only four agencies (National Oceanic and Atmospheric Administration, US Census Bureau, US Geological Survey and Farm Service Agency)—4.2% of all departments and agencies participating in data.gov--uploaded geodata sets and virtually all these datasets were published before www.data.gov came online on the web sites of these individual agencies.

§ The number of downloads from www.data.gov has been miniscule. 66% of all departments and agencies (62 entities) had less than 1,000 downloads each over this 21-week period. Another 31% of all departments and agencies (29 entities) had between 1,000 and 10,000 downloads each. Only 3% of all departments and agencies (3 entities) witnessed between 10,000 and 25,000 downloads each. These three agencies were the Centers for Medicare and Medicaid Services (CMS), the Internal Revenue Services (IRS), and the US Geological Survey (USGS). Most of these downloads are attributed to datasets these three agencies uploaded to their own web sites (long before www.data.gov came online).

§ 99% of all departments and agencies (93) experienced, on average, less than 1,000 downloads per an uploaded dataset. In fact, 40% of all departments and agencies (37) witnessed less than 100 downloads, on average, per an uploaded dataset. Only a single agency (US Food and Drug Administration [FDA]) witnessed slightly more than 1,000 downloads per each one of the three data sets it uploaded.

The Conflict Between Open Data Transparency and Collaboration-by-Trade

Why did significant external political pressure fail to convince Federal agencies to publish more

valuable data on www.data.gov? I argue that thoughtlessly and indiscriminately Open Data architects

tinkered with the ultimate source of bureaucratic power—information. Senior bureaucrats remain reluctant

to "free" the information resources that empower them vis-à-vis other agencies. Since direct confrontation

with the new administration was unwise, most agencies adopted a passive-aggressive behavior—appearing

as if they were cooperating with Open Data but, in fact, not cooperating at all.

The popular web culture itself has already grown from its infant "everything-for-free" phase to its

current for-profit condition. Successful companies such as Apple, Amazon and eBay developed

marketplaces where digital products are cheap but not free-of-charge. These companies do well because

even a cheap product when multiplied by billions of split-second transactions yields handsome profits. The

penalty for driving down the price of any commodity to $0 is immediate and harsh. For example,

Europeans failed in their first attempt to build an emissions marketplace because they printed too many


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allowances, to a point where trading in the valueless new commodity practically stopped (EU ETS 2010 ;

ECX 2010).

Federal agencies labor hard to mine their databases and are therefore reluctant to surrender their

prized information assets for free. For example, the Departments of State, Agriculture and Education are

utilizing business intelligence tools to detect fraud. The IRS uses data mining to distinguish between tax

evaders and those who make errors on their tax returns. The Navy and Marine Corps use business

intelligence tools to assess how many training personnel they need, what the failure rates of all parts on

deployed ships are expected to be, and what the uniformed personnel turnover might be. The Department

of Health and Human Services (HHS) built a data warehouse to watch out for potential national blood

supply shortages and the U.S. Marshals Service maintains a similar data warehouse to determine the

appropriate workforce level (White 2007).

As Open Data continued to pressure agencies to "free" data, a downwards spiral evolved. Agencies

adopted a passive-aggressive behavior and released huge quantities of useless data while locking inside

closed database gardens more valuable data sets. In the age of the GPS, nanotechnology and social

networking it is easy and cheap to generate abundant amounts of valueless data. However, software

developers are a shrewd crowd. Initially, they enthusiastically visualized the newly released Federal data.

But these early applications were plucking the low hanging fruit. As soon as the low hanging fruit was

over, these developers lost interest in the harder task of sifting through mountains of valueless Federal

data. In New Zealand, a project like data.gov died prematurely precisely because software developers

discovered that lots of facts were dumped into cyberspace without purpose and refused to develop

applications for it (Economist 2010b). On their part, Federal Agencies were "disappointed" to discover that

nothing is done with the released data and cooperated less with Open Data.

In short, Federal agencies know all too well that their information assets are the ultimate source of

their political power; hence, they refused to surrender these assets. Open Data architects disdainfully called

this logic "the nasty, brutish, and short worldview of government" (Noveck 2009 190). But, senior

Washington bureaucrats understand that Open Data architects are demanding to empty their agencies from

that which defines their very being in the new millennium—information.


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An Alternative Marketplace-Based Approach to Increase Federal Information Sharing

Bureaucrats generate data elements while executing their daily routines. Later on, incidentally, they

discover that the data has independent value as a commodity. Above everything else, Federal data is a

contested commodity. Restricted commoditization governs contested commodities trading. Such restricted

arrangements can ban advertisement, curb market rhetoric, limit the number of potential buyers, decouple

demand and supply, mandate non-monetary payments, or set terms for the future removal of a contested

commodity from the marketplace (Agnew 2003 ; Schwindt and Vining 1986). Blood, for example, became

a tradable commodity through restricted commoditization arrangements (Cooper and Culyer 1968). Indeed,

commoditization and non-commoditization are but end points in a continuum that narrates the life cycles

of contested commodities. The interesting questions are found in the middle of this continuum: what

exchanges will be encouraged? What limits will be set on trading?

Restricted commoditization can govern FIM. Some Federal data would not be traded (ex: predictive

genetic data discovered via a routine blood test). Conversely, data such as vehicles' license numbers will be

tradable. In between these extremes, most Federal data would be traded as a contested commodity. By

manipulating the spirit of selfish calculation, exchange would set Federal data in motion and create new

supply zones in respond to demand. Just as trade opened the gates of medieval cities, agencies might

discover that opening up their databases to outsiders pays off (Appadurai 1986; Braunschvig 1998).

FIM might also be a good information sharing mechanism for a government of strangers. Today,

more outsiders execute Federal functions than ever before. For example, about a third of the estimated

854,000 intelligence employees are private sector contractors. FIM can solve problems that characterize

trading among strangers including the authentication and verification of data quality and property rights

(Heclo, 1977; Light, 1999; The Washington Post, 2010). Trading in the FIM could take place through

credits. Agencies would accumulate credits by allowing other agencies to download or browse their data.

Agencies that perform well would then exchange accumulated credits for dollars to be invested in new

information products. Less successful agencies would suffer penalties, such as freezing of their requests

for additional IT funds. Agencies would sell three types of information products. First, they would trade in

primary data which are observable facts such as a person's age. Some observable facts are generated (ex:

passport number), others are received from citizens (ex: place of residence) and still others are hybrid


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pieces of data (ex: social security benefits). Next, agencies would trade in secondary information products.

These products grant insights into the relationships among primordial data elements. FIM would provide

incentives to develop and sell secondary information products. For example, during the 2008 financial

crisis, the Federal government appeared baffled by the task of overseeing less regulated market

participants. An agency that creates an effective credit-scoring index to tackle this problem would profit

from selling it to other agencies (GAO 2009). Finally, agencies would sell tertiary information products.

These products are based on futures trading and seek to exhaust an inexhaustible series of variables that

affect data quality and pricing. Tertiary products are suitable for addressing complex problems. For

example, within FIM, an agency might find funding to build a new information system by selling to

another agency the rights to harvest its future click-streams.

FIM would be self-regulated via an eBay-style reputational system to ensure that cheating does not

pay off. An independent infrastructure organization would support trading. A traders' forum would

encourage agencies to share best trading practices, similar to the International Carbon Action Partnership

(ICAP). A micro-transaction engine would aggregate the results of trillions of transactions. The system's

audit log would provide a rare opportunity to discover who inside government exchanges what

information, when and why. New search engines would evolve to support trading based on the

miscellaneous order concept (i.e. any topic of interest to anyone is available). Eventually, FIM might

empower State organizations to trade data vis-à-vis Federal agencies (Huijboom and Hoogwout 2004 ;

ICAP 2010 ; Mayer-Schönberger and Lazer 2007a ; Weinberger 2007).

Ethical and Transparency Challenges: FOIA, Expansion of Greed, and Big Brother Government

FIM's opponents will utilize the first amendment and FOIA to argue that Federal data ought to

remain free of charge, that FIM will expand greed and egotism in governmental work, and that, if

successful, FIM will pave the way to an irreversible Big Brother government. I address these concerns in

the next three sections

"Citizens Paying Twice [for data]" and Curtailing FOIA

Critics might claim that Federal data is an essential service for which the government cannot charge

twice (i.e. by collecting tax revenues and by paying agencies for trading data). FIM might outrage citizens


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who are already accessing free-of-charge Federal databases such as the SEC's EDGAR system. Yet FIM

would actually save taxpayer funds because it will eliminate numerous other information sharing computer

projects. Agencies could establish subsidiaries to sell some information products while granting free access

to other products. Such arrangements are already used today in the US and Europe. For example, by law,

the three credit bureaus grant free access to some data while selling other identity theft protection products.

FIM's expansion could yield even more creative solutions. For example, citizens might provide timely

personal data in return for credit that can be applied to reduce fees (such as a passport renewal fee).

Agencies would provide such discounts because they will package the fresh data and sell it to other

agencies.

Critics may also suggest that a potential collision exists between the proposed FIM (where data is

for sale) and FOIA (which dictates that Federal data is a public good). However, FIM can grow to become

a complimentary transparency mechanism to FOIA. FOIA provides transparency via an individualistic,

reactive, delayed, emergency-oriented, history-driven confrontational, judicial, do-it-yourself, and costly

(in terms of price and expertise required) mechanism. FIM will complement FOIA by providing an

aggregated, proactive, immediate, future-oriented, non-confrontational, business-like, agency-driven, and

cost-effective mechanism to increase inter-agency sharing of the vast Federal data troves that FOIA never

touches. One scholar defined the FOIA-based information ecology as a "loosely joined chain of leaders,

investigators, and advocates, [that] can be more robust in crises of fear and outrage" (Kreimer 2008 1075).

In an identical manner, the complementary FIM-based information ecology could become the "loosely

joined chain of bureaucrats who internally share information via trade in non-crisis times."

Expanding Federal Egotism

Next, ethicists may argue that FIM would teach agencies that everything is a fair game if one can

make a profit. Critics would then ask: Might some groups become more disadvantaged because agencies

exchange too little or too much information about them? But, like early medieval traders, agencies would

discover that success is based on the trader's reputation for honesty and fairness. Additionally, some data

would undergo a "cooling off" period before it becomes tradable in order to eliminate manipulative

trading. Like other solidarity-based national health insurance frameworks, trading agencies would sign


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pacts baring discrimination (Gerards and Janssen 2006). A portion of the profits would be diverted to

support projects that narrow social gaps. It should also be noted that contested commodities' trading rarely

harms weaker groups. For example, the voluntary military does not recruit the most disadvantaged because

they lack the qualifications to fight in a modern war (Bandt 1998 ; Becker and Elıas 2007 ; Premkumar

2003). In that sense, Federal data is akin to human organs that enter a distribution chain as a gift but

thereafter are transformed into a commodity (Mahoney 2000). A non-trading agency merely rewards less

accountable intermediaries who will find ways to profit from its data.

Big Brother Government

Ethicists would be alarmed by the prospects of a big-brother government. By this argument, FIM

will empower agencies to link more data together. Informal privacy protections such as technical

incompatibilities would vanish overnight. More data about citizens would be collected with fewer

opportunities for citizens to opt out from such collection efforts. Agencies would have new incentives to

store everything and forget nothing. For example, the Dutch RINIS system made it impossible to obtain a

benefit on false grounds. However, scholars argued that RINIS exercises too much unaccountable

technocratic control (Snellen 2002). In an essence, critics would argue, FIM would reinvent the Total

Information Awareness Program that Congress stopped in 2003. There will be no place to hide for weaker

groups, such as illegal labor migrants, because information only about them would not be accessible.

During the mid-1930s, the Dutch government developed a new population registration system to

streamline administration. The Nazis utilized this system to apprehend and execute Jewish refugees who

were not registered in the system. Will FIM reinvent such a horrific database system? (Mayer-Schönberger

and Lazer 2007b ; White 2007)

Yet, old habits will still protect citizens' privacy after FIM becomes operational. Federal employees

will continue to print an obscene volume of non-tradable paper documents (Lexmark 2009). Existing

privacy protection mechanisms will still apply, including privacy advocates, ombudsmen, internal privacy

review boards, and data protection commissioners. True, FIM's data transactions will be exempted from

the dictates of the Privacy Act (1974) because this Act specifically allows such transactions if they are part

of agencies' "routine uses." However, the same exemption-logic applies to current inter-agency data-


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exchanges (GAO 2008). The most important privacy-protection mechanism will remain bureaucrats'

individual responsibility (Cate 1997).

FIM would also provide new privacy protections. Citizens' data will be scattered across databases

rather than stored in a central location. Privacy invaders ranging from Chinese hackers to insiders seeking

to tip organizations such Wikileaks would be forced to leave their electronic footprints in the audit logs of

many databases. With FIM, there will be no single "big brother" database to break into in order to steal

data. FIM would also reduce the number of bureaucrats involved in data exchanges. With FIM, there

would be less manual data processing and fewer opportunities to invade privacy. FIM would empower

investigators to continuously detect abuse via new metadata solutions that were proven effective during the

investigations of the Iran-Contra scandal and the space shuttle Columbia accident (Raul 2002). FIM would

also make it easier to remove some data assets from the marketplace or to require the consent of data-

subjects for trading in information about them. Moreover, FIM would encourage agencies to trade in large

volumes of data. Such trade frequently improves privacy because it diverts resources to the statistical

analysis of groups and away from individual cases. Agencies will also have economic incentive to develop

privacy protection mechanisms for their information assets. Eventually, a new contractual approach might

evolve whereby agencies and individuals trade explicitly in privacy rights.

Conclusion

This paper reveals for the first time the meager results of Open Data, the flagship of the Obama

Administration's Open Government program. Penetrating beneath the powerful public relations image of

Open Data, the analysis demonstrate how agencies adopted passive-aggressive behavior to bypass the

program's dictates while appearing as if they were cooperating with it. The paper argued that Open Data's

transparency edifice ("publish all data sets on the web") is not compatible with agencies' data-

collaboration-via-trade practice. Federal agencies, the article argued, will not free precious information

assets that define their bargaining power vis-à-vis other agencies.

Via the manipulation of the "zeitgeist of democratizing data", the "Open Data" program is still

growing and becoming a destructive dogma (Lakhani et al. 2010 5). The Open Data program has created

an imaginary and destructive world in which organizations and people can share data and applications if


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and only if they do so altruistically (Mahoney 2000). This "one-size-fits-all" monolithic approach ignores

both the nature of Federal agencies as bargaining 'political creatures' and the unique features of data as a

commodity. Adding insult to injury, Open Data had become a truism that can never be falsified. There is

always the next latest-and-greatest technological fix for whatever appears not to be working.

Agencies conceal information in order to barter data vis-à-vis other agencies. It is unwise and

politically non-feasible to demand that agencies free information products they labored so hard to create.

The Open Data dogma closes doors because it leaves no room for alternative marketplace approaches.

However, a marketplace approach such as the proposed Federal Information Marketplace can convince

even selfish bureaucratic actors to share more electronic data. Such a marketplace approach is compatible

with the highest ethical and transparency standards that govern governmental work. FIM will complement

FOIA, thicken trust among trading-agencies, and create new and powerful defense mechanisms against Big

Brother government.

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Trading Federal Data - Ethical and Transparency Considerations

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