The Department of Education (DoED) is poised to issue its “gainful employment” (GE) regulation that relies upon a non-transparent “black box” test to determine whether the large proportion of minority and lower-income students enrolled in career college programs will be eligible for Title IV student loans. Strong rumors contend that Secretary Duncan will approve using (private) actual income data collected by the Internal Revenue Service (IRS) and the Social Security Administration (SSA) rather than public/transparent data from the Bureau of Labor Statistics (BLS) to calculate “debt-to-income” ratios. According to the GE rule, the ratio will determine which students are eligible to receive financial aid to obtain their higher education degree and which will be denied.
Unfortunately, there are quite a few flaws in this plan. Under DoED’s actual income data approach, colleges will receive no information (i.e. data, methodology, or assumptions) other than the average income figure that the IRS/SSA releases. BLS, on the other hand, provides colleges and students with access to detailed tables, charts, and explanations of the methodology for calculating the wage estimates on BLS’s website. Even if it were true that IRS/SSA data on actual income is more accurate than the national data base of average income for specific occupations published by the BLS and accessible on the Internet, the question Secretary Duncan hasn’t addressed — at least not publicly — is this: Does that theoretical and unproven advantage in accuracy offset the substantial disadvantages in compromising all the administration’s core liberal values of 1) transparency, 2) due process, 3) the presumption of innocence, 4) a level playing field in government actions, and 5) privacy guarantees?
Clearly, the DoED’s decision to rely on highly private, “black box” data is an abuse of power that should be examined. For reasons we cannot comprehend, commentators, analysts, and media, as well as such liberal NGOs as the Center for American Progress, seem indifferent to this danger.
In a letter to the Social Security Administration, Senator Orrin Hatch expressed his concern that the SSA’s willingness to share massive individual tax return and income tax information with another government agency would violate the privacy protections under Section 6103 of the Internal Revenue Code (apart from, potentially, other privacy rights federal laws and regulations).
The answer received by Senator Hatch from the SSA Commissioner Michael J. Astrue was (at best) incomplete. Commissioner Astrue assured Senator Hatch that the information to be provided to DoED will be “strictly statistical” — i.e., “will not contain any information on individual taxpayers and no taxpayer will be identifiable, directly or indirectly.”
With all due respect, Commissioner Astrue’s statement is misleading. What he forgot to say is that even if the data sent to DoED is aggregated and not individualized, it can be roughly “dis-aggregated” and individualized if the number of students in a particular program is relatively small, as may, at times, be the case.
The government’s reliance on non-transparent data from the SSA and IRS is a “presumption of guilt” for the career colleges who are not given access to the data but required to make changes to their academic programs as a result.
Here’s how it will work if Secretary Duncan allows BLS data to be replaced by SSA/IRS data to measure the debt-to-income text: The Department has access to the data, the career colleges do not. Thus career colleges will not be able to watch over their students and the debts they are incurring in order to avoid failing the 8% or under student debt-to-income ratio. Instead, they will be told by the DoED, when it is done with its “black box” calculations, that students in the particular program under review are out and they lose their student loans. The onus is on the schools to prove they are innocent.
The Constitution guarantees a presumption of innocence. In subverting due process, “gainful employment” creates the presumption of guilt.