Transparency's AI Problem

Authors

Hannah Bloch-Wehba, Texas A&M University School of LawFollow

Document Type

Conference Proceeding

Publication Date

6-2021

Abstract

A consensus seems to be emerging that algorithmic governance is too opaque and ought to be made more accountable and transparent. But algorithmic governance underscores the limited capacity of transparency law—the Freedom of Information Act and its state equivalents—to promote accountability. Drawing on the critical literature on “open government,” this Essay shows that algorithmic governance reflects and amplifies systemic weaknesses in the transparency regime, including privatization, secrecy, private sector cooptation, and reactive disclosure. These deficiencies highlight the urgent need to reorient transparency and accountability law toward meaningful public engagement in ongoing oversight. This shift requires rethinking FOIA’s core commitment to public disclosure of agency records, exploring instead alternative ways to empower the public and to shed light on decisionmaking. The Essay argues that new approaches to transparency and accountability for algorithmic governance should be independent of private vendors, and ought to adequately represent the interests of affected individuals and communities. These considerations, of vital importance for the oversight of automated systems, also hold broader lessons for efforts to recraft open government obligations in the public interest.

Num Pages

34

Series Title

Data & Democracy Essay Series

Publisher

Knight First Amendment Institute

Recommended Citation

Hannah Bloch-Wehba, Transparency's AI Problem, (2021).
Available at: https://scholarship.law.tamu.edu/facscholar/1477

File Type

PDF