CoChat
Sign Up
Cited by 101Ethics and Social Impacts of AIDigitalization, Law, and RegulationLegal and Labor Studies

The DOI matches its Crossref record.

New Laws of Robotics

Pasquale, Frank·2020·Harvard University Press eBooks
DOI 10.4159/9780674250062
Open this paper in CoChat — free account

Abstract

AI is poised to disrupt our work and our lives. We can harness these technologies rather than fall captive to them—but only through wise regulation. Too many CEOs tell a simple story about the future of work: if a machine can do what you do, your job will be automated. They envision everyone from doctors to soldiers rendered superfluous by ever-more-powerful AI. They offer stark alternatives: make robots or be replaced by them. Another story is possible. In virtually every walk of life, robotic systems can make labor more valuable, not less. Frank Pasquale tells the story of nurses, teachers, designers, and others who partner with technologists, rather than meekly serving as data sources for their computerized replacements. This cooperation reveals the kind of technological advance that could bring us all better health care, education, and more, while maintaining meaningful work. These partnerships also show how law and regulation can promote prosperity for all, rather than a zero-sum race of humans against machines. How far should AI be entrusted to assume tasks once performed by humans? What is gained and lost when it does? What is the optimal mix of robotic and human interaction? New Laws of Robotics makes the case that policymakers must not allow corporations or engineers to answer these questions alone. The kind of automation we get—and who it benefits—will depend on myriad small decisions about how to develop AI. Pasquale proposes ways to democratize that decision making, rather than centralize it in unaccountable firms. Sober yet optimistic, New Laws of Robotics offers an inspiring vision of technological progress, in which human capacities and expertise are the irreplaceable center of an inclusive economy.

Overview

Integrity signals

Registry

Crossref · 10.4159/9780674250062

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Still being checked.

Cited by

Sorted by citations

Related

See all

Metadata

Authors
Pasquale, F.
Corresponding author
Pasquale, Frank
ORCID
Pasquale, Frank
Venue
Harvard University Press eBooks
Publisher
Harvard University Press
Published
2020-10-26
DOI
10.4159/9780674250062
OpenAlex
W3093932696
Cited by
101
References
0
Citations by year
2026: 8 · 2025: 16 · 2024: 15 · 2023: 21 · 2022: 31 · 2021: 9 · 2020: 1
FWCI
15.56
Type
book
Language
en
Open access
closed
Locations
Harvard University Press eBooks (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
  • Social Sciences › Law › Digitalization, Law, and Regulation
  • Social Sciences › Business, Management and Accounting › Industrial relations › Legal and Labor Studies
Keywords
AI regulation, automation, future of work, human-robot collaboration, human-AI collaboration, meaningful work, inclusive economy, work values, artificial intelligence in healthcare, artificial intelligence in education, human expertise

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review