arbiter
JournalsAccount

CHIEF JUSTICE ROBOTS

Eugene Volokh

Duke Law Journal2019article
ABDC B
Weight
0.70

Abstract

Say an AI program someday passes a Turing test, because it can con-verse in a way indistinguishable from a human. And say that its develop-ers can then teach it to converse—and even present an extended persua-sive argument—in a way indistinguishable from the sort of human we call a “lawyer.” The program could thus become an AI brief-writer, ca-pable of regularly winning brief-writing competitions against human lawyers. Once that happens (if it ever happens), this Essay argues, the same technology can be used to create AI judges, judges that we should accept as no less reliable (and more cost-effective) than human judges. If the software can create persuasive opinions, capable of regularly winning opinion-writing competitions against human judges—and if it can be adequately protected against hacking and similar attacks—we should in principle accept it as a judge, even if the opinions do not stem from human judgment.

12 citations

Cite this paper

@article{eugene2019,
  title        = {{CHIEF JUSTICE ROBOTS}},
  author       = {Eugene Volokh},
  journal      = {Duke Law Journal},
  year         = {2019},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

CHIEF JUSTICE ROBOTS

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.70

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact1.00 × 0.4 = 0.40
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.