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Enabling FOIA: Getting Better Access to Government Data at a Lower Cost

Freedom of Information Act is vital for holding the government to account. But little effort has gone into building tools that enable fulfillment of FOIA requests. As a consequence of this underinvestment, fulfilling FOIA requests often means onerous, costly work for government agencies and long delays for the requesters. Here,

When the Cost of Misclassification is Higher for the Customer than for the Business

Consider a bank making decisions about loans. For the bank, making lending decisions optimally means reducing prediction errors*(cost of errors) minus the cost of making predictions (keeping things simple here). The cost of any one particular error, especially the denial of a loan when eligible, is typically small for

The Human and the Machine: Semi-automated approaches to ML

For a class of problems, a combination of algorithms and human input makes for the most optimal solution. For instance, three years ago, software to recreate shredded documents that won the DARPA award used “human[s] [to] verify what the computer was recommending.” The insight is used in character recognition

Big Data Algorithms: Too Complicated to Communicate?

“A decision is made about you, and you have no idea why it was done,” said Rajeev Date, an investor in data-science lenders and a former deputy director of Consumer Financial Protection Bureau From NYT: If Algorithms Know All, How Much Should Humans Help? The assertion that there is no

(No) Value Added Models

This note is in response to some of the points raised in the Agnoff Lecture by Ed Haertel. The lecture makes two big points: 1) Teacher effectiveness ratings based on current Value Added Models are ‘unreliable.’ They are actually much worse than just unreliable; see below. 2) Simulated counterfactuals of