Machine Testimony

82 Pages Posted: 7 Jan 2017 Last revised: 18 May 2017

Andrea L. Roth

University of California, Berkeley - School of Law

Date Written: April 11, 2017

Abstract

Machines play increasingly crucial roles in establishing facts in legal disputes. Some machines convey information — the images of cameras, the measurements of thermometers, the opinions of expert systems. When a litigant offers a human assertion for its truth, the law subjects it to testimonial safeguards — such as impeachment and the hearsay rule — to give juries the context necessary to assess the source’s credibility. But the law on machine conveyance is confused; courts shoehorn them into existing rules by treating them as “hearsay,” as “real evidence,” or as “methods” underlying human expert opinions. These attempts have not been wholly unsuccessful, but they are intellectually incoherent and fail to fully empower juries to assess machine credibility. This Article seeks to resolve this confusion and to offer a coherent framework for conceptualizing and regulating machine evidence. First, it explains that some machine evidence, like human testimony, depends on the credibility of a source. Just as so-called “hearsay dangers” lurk in human assertions, “black box dangers” — human and machine errors causing a machine to be false by design, inarticulate, or analytically unsound — potentially lurk in machine conveyances. Second, it offers a taxonomy of machine evidence, explaining which types implicate credibility and how courts have attempted to regulate them through existing law. Third, it offers a new vision of testimonial safeguards for machines. It explores credibility testing in the form of front-end design, input and operation protocols; pretrial disclosure and access rules; authentication and reliability rules; impeachment and courtroom testing mechanisms; jury instructions; and corroboration rules. And it explains why machine sources can be “witnesses” under the Sixth Amendment, refocusing the right of confrontation on meaningful impeachment. The Article concludes by suggesting how the decoupling of credibility testing from the prevailing courtroom-centered hearsay model could benefit the law of testimony more broadly.

Keywords: automation, machines, assertions, hearsay, algorithms

Suggested Citation

Roth, Andrea L., Machine Testimony (April 11, 2017). Yale Law Journal, Vol. 126, No. 1, 2017; UC Berkeley Public Law Research Paper No. 2893755. Available at SSRN: https://ssrn.com/abstract=2893755

Andrea L. Roth (Contact Author)

University of California, Berkeley - School of Law ( email )

215 Boalt Hall
Berkeley, CA 94720-7200
United States

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