Government by Algorithm: Artificial Intelligence in Federal Administrative Agencies

Engstrom, David Freeman; Ho, Daniel E.; Sharkey, Catherine M.; Cuéllar, Mariano-Florentino

doi:10.2139/ssrn.3551505

Cited by 137 publications

(124 citation statements)

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“…External peer review may improve patent examination, but it may not be more cost effective than increased examination time (Frakes & Wasserman ) or alternative peer‐review designs such as internal peer review (Ho ). Artificial intelligence may also decrease prior art search costs (Engstrom et al ; Helmers et al ) . The resources required to match and to adapt referee reports (Figure ) demonstrate the cost and the need to have internal institutions (akin to a strong editorial board) to make peer review work.…”

Section: Discussionmentioning

confidence: 99%

Improving Scientific Judgments in Law and Government: A Field Experiment of Patent Peer Review

Ho¹,

Ouellette²

2020

J Empirical Legal Studies

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Many have advocated for the expansion of peer review to improve scientific judgments in law and public policy. One such test case is the patent examination process, with numerous commentators arguing that scientific peer review can solve informational deficits in patent determinations. We present results from a novel randomized field experiment, carried out over the course of three years, in which 336 prominent scientific experts agreed to provide input on U.S. patent applications. Their input was edited for compliance with submission requirements and submitted to the U.S. Patent and Trademark Office (USPTO) by our research team. We show that the intervention caused examiners to (1) increase search efforts and citations to the non‐patent (scientific) literature and (2) grant the application at lower rates in the first instance. However, results were substantially weaker and resource costs substantially higher than anticipated in the literature, highlighting significant challenges and questions of institutional design in bringing scientific expertise into law and government.

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Section: Discussionmentioning

confidence: 99%

Improving Scientific Judgments in Law and Government: A Field Experiment of Patent Peer Review

Ho¹,

Ouellette²

2020

J Empirical Legal Studies

Self Cite

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“…Agents are now learning how to collaborate and interact with other agents, or how to collect large amounts of information, and then distill the content down into more easily understood components. While beyond the scope of this article, it is worth noting the significant efforts of federal administrative agencies to use AI for improved governance relating to data management, adjudication, enforcement, and accountability functions (see Engstrom and Ho 2020; Engstrom et al 2020).…”

Section: The Rise Of Agents In Negotiationmentioning

confidence: 99%

Designing Ethical Online Dispute Resolution Systems: The Rise of the Fourth Party

Wing¹,

Martinez²,

Katsh³

et al. 2021

Negotiation Journal

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As the pandemic forces public and private institutions to move online, many court and business leaders are looking to the field of online dispute resolution (ODR) for best practices and lessons learned. Developed over the last twenty years, largely in response to the growth of e‐commerce, the ODR field has generated a deep well of theory and practice while also identifying potential ethical dilemmas and risks. The application of technology, the “fourth party,” plays an increasingly integral role in how we negotiate resolutions to our disputes, with or without a third party. A brief overview of the history of ODR’s development will set the context for the exploration of the range of tools and techniques encompassed by online dispute resolution. Consideration of the ethical challenges raised by ODR practice will illuminate key questions and choices that need to be made in designing ODR systems and in governing their use.

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“…Governments have long been using computer algorithms to assist government officials make decisions and increasingly to automate those decisions without human involvement. To date, the use of AI in government decision making is still limited (Engstrom et al, 2020;De Sousa et al, 2019;Sun & Medaglia, 2019), though similar systems based on sophisticated statistical analyses are widely deployed. Indeed, is it sometimes hard to know if a system is a true AI.…”

Section: Automated Decision-makingmentioning

confidence: 99%

Improving public services using artificial intelligence: possibilities, pitfalls, governance

Henman

2020

Asia Pacific Journal of Public Administration

138

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Artificial intelligence arising from the use of machine learning is rapidly being developed and deployed by governments to enhance operations, public services, and compliance and security activities. This article reviews how artificial intelligence is being used in public sector for automated decision making, for chatbots to provide information and advice, and for public safety and security. It then outlines four public administration challenges to deploying artificial intelligence in public administration: accuracy, bias and discrimination; legality, due process and administrative justice; responsibility, accountability, transparency and explainability; and power, compliance and control. The article outlines technological and governance innovations that are being developed to address these challenges.

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Government by Algorithm: Artificial Intelligence in Federal Administrative Agencies

Cited by 137 publications

References 0 publications

Improving Scientific Judgments in Law and Government: A Field Experiment of Patent Peer Review

Improving Scientific Judgments in Law and Government: A Field Experiment of Patent Peer Review

Designing Ethical Online Dispute Resolution Systems: The Rise of the Fourth Party

Improving public services using artificial intelligence: possibilities, pitfalls, governance

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