The Three Laws of Robotics in the Age of Big Data | Balkin

Jack M. Balkin  (Yale); The Three Laws of Robotics in the Age of Big Data; Ohio State Law Journal, Vol. 78, (2017), Forthcoming (real soon now, RSN), Yale Law School, Public Law Research Paper No. 592; 2016-12-29 → 2017-09-10; 45 pages; ssrn:2890965.

tl;dr → administrative laws [should be] directed at human beings and human organizations, not at [machines].

Laws

  1. machine operators are responsible
    [for the operations of their machines, always & everywhere]
  2. businesses are responsible
    [for the operation of their machines, always & everywhere]
  3. machines must not pollute
    [in a sense to be defined later: e.g. by a "tussle"]

None of this requires new legal theory; c.f. licensing for planes, trains & automobiles; and on to nuclear plants, steel unto any intellectual business operation of any kind (ahem, medical, architecture, legal services; and anything at all under the Commerce Clause, no?)

Mentions

  • Isaac Asimov, the stories of
    …and the whole point of the stories was the problematic nature of The Three Laws, They seemed fun and clear but they were problematized and the don’t work as a supervisory apparatus. Maybe they don’t work at all. Is the same true here? Not shown.
  • Laws of Robotics,
    Three Laws of Robotics.
  • [redefined] the “laws of robotics” are the legal and policy principles that govern [non-persons, unnatural-persons].

Concepts Principles (HF/SE/IF/AN)

  1. homunculus, a fallacy
  2. substitution, an effect
  3. information fiduciaries, a role
  4. algorithmic nuisance, an ideal (an anti-pattern

Analysis

A matrix, the he cross product, of twelve (12) combinations:

Requirement of (TAdP)
  1. Transparency
  2. Accountability
  3. due Process
Principles of (HF/SE/IF/AN)
  • [the] homunculus fallacy
  • [a] substitution effect
  • information fiduciaries
  • algorithmic nuisance

 Argot

The Suitcase Words
  • Isaac Asimov.
  • three law of robotics.
  • programmed,
    programmed into every robot.
  • govern.
  • robots.
  • algorithms.
  • artificial intelligence agents..
  • legal principles,
    basic legal principles.
  • the homunculus fallacy.
  • he substitution effect.
  • information fiduciaries.
  • algorithmic nuisance.
  • homunculus fallacy.
  • attribution.
  • human intention.
  • human agency.
  • robots.
  • belief,
    false belief.
  • person
    little person.
  • robot.
  • program.
  • intentions,
    good intentions.
  • substitution effect.
  • social power.
  • social relations.
  • robots.
  • Artificial Intelligence (AI).
  • AI agents.
  • algorithms.
  • substitute,
    algorithmssubstitute for human beings.
  • operate,
    algorithms operate as special-purpose people..
  • mediated
    ,mediated through new technologies.
  • three laws of robotics
    Three Laws of Robotics.
  • Algorithmic Society.
  • robots.
  • artificial intelligence agents.
  • algorithms.
  • governments.
  • businesses.
  • staffed.
  • Algorithmic Society.
  • asymmetries,
    asymmetries of information,
    asymmetries of monitoring capacity,
    asymmetries computational power.
  • Algorithmic Society:.
  • operators,
    operators of robots,
    operators of algorithms
    operators of artificial intelligence agents.
  • information fiduciaries.
  • special duties,
    special duties of good faith,
    special duties fair dealing.
  • end-users, clients and customersdata subjects.
  • businesses,
    privately owned businesses.
  • the public,
    the general public..
  • duty,
    central public duty.
  • algorithmic nuisances.
  • leverage utilize use.
  • asymmetries of information,
    asymmetries of monitoring capacity,
    asymmetries of computational power.
  • externalize,
    externalize the costs,
    externalize the costs of their activities.
  • algorithmic nuisance.
  • harms
    harms of algorithmic decision making.
  • discrimination
    intentional discrimination.
  • pollution,
    unjustified pollution
    socially unjustified pollution
    contra (socially-)justified pollution.
  • power
    computational power.
  • obligations,
    obligations of transparency,<br/ obligations of due process,
    obligations of accountability.
  • obligations flow.
  • requirements,
    substantive requirements,
    three substantive requirements.
  • transparency.
  • accountability.
  • due process.
  • obligation,
    an obligation of.
  • fiduciary relations.
  • public duties.
  • measure,
    a measure,
    a prophylactic measure.
  • externalization,
    unjustified externalization
    unjustified externalization of harms.
  • remedy,
    remedy for harm.

Previously filled.

Code Dependent: Pros and Cons of the Algorithm Age | Pew Research

, ; Code Dependent: Pros and Cons of the Algorithm Age; 2017-02-08; 87 pages; landing.
Teaser: Algorithms are aimed at optimizing everything. They can save lives, make things easier and conquer chaos. Still, experts worry they can also put too much control in the hands of corporations and governments, perpetuate bias, create filter bubbles, cut choices, creativity and serendipity, and could result in greater unemployment.

tl;dr → there be dragons; this is an important area; the future is at stake; the alarum has been sounded; there are seers who can show us the way. In their own words.

Series

Future of the Internet, of Pew Research & Elon University.

Table of Contents

  • Overview
  • Themes illuminating concerns and challenges
  • Key experts’ thinking about the future impacts of algorithms
  • About this canvassing of experts
  • Theme 1: Algorithms will continue to spread everywhere
  • Theme 2: Good things lie ahead
  • Theme 3: Humanity and human judgment are lost when data and predictive modeling become paramount
  • Theme 4: Biases exist in algorithmically-organized systems
  • Theme 5: Algorithmic categorizations deepen divides
  • Theme 6: Unemployment will rise
  • Theme 7: The need grows for algorithmic literacy, transparency and oversight
  • Acknowledgments

Promotion

Code-Dependent: Pros and Cons of the Algorithm Age; , (Pew Research Center); In Their Blog; 2017-02-08.

Teaser: Algorithms are aimed at optimizing everything. They can save lives, make things easier and conquer chaos. Still, experts worry they can also put too much control in the hands of corporations and governments, perpetuate bias, create filter bubbles, cut choices, creativity and serendipity, and could result in greater unemployment/

Mentions

  • Pew Research Center of the Pew Charitable Trusts
  • Imagining the Internet Center at Elon Univesity
  • <ahem>the Singularity enthusiasts … .</ahem>

Themes

  1. Algorithms will continue to spread everywhere
  2. Good things lie ahead
  3. Humanity adn human judgement are lost wwhen data nad predictive modeling become paramount
  4. Biases exist in algorithymically-organized systems
  5. algorithmic categorizations deepen divides
  6. Unemployment will rise
  7. The need grows for algorithmic literacy, transparency and oversight.

Argot

  • <snicker>Artificial Intelligence (AI)</snicker>
  • algocratic governance
  • surveillance capitalism
  • information capitalism
  • topsight
  • black-box nature [of]
  • digital scientism
  • obedience score

Quoted

  • Aneesh Aneesh, Stanford University.
  • Peter Diamandis, CEO, XPrize Foundation.
  • Shoshana Zuboff, Harvard.
  • Jim Warren, activist.
  • Terry Langendoen, expert, U.S. National Science Foundation.
  • Patrick Tucker technology editor at Defense One,.
  • Paul Jones, clinical professor at the University of North Carolina-Chapel Hill and director of ibiblio.org.
  • David Krieger, director of the Institute for Communication & Leadership IKF,.
  • Galen Hunt, partner research manager at Microsoft Research NExT,.
  • Alf Rehn, professor and chair of management and organization at Åbo Akademi University in Finland,.
  • Andrew Nachison, founder at We Media,.
  • Luis Lach, president of the Sociedad Mexicana de Computación en la Educación, A.C.
  • Frank Pasquale, professor of law, University of Maryland.
  • Jeff Jarvis, reporter.
  • Cindy Cohn, executive director at the Electronic Frontier Foundation,.
  • Bernardo A. Huberman, senior fellow and director of the Mechanisms and Design Lab at HPE Labs, Hewlett Packard Enterprise.
  • Marcel bullinga, expert.
  • Michael Rogers, principal, Practical Futurist.
  • Brian Christian, Tom Griffiths.
  • David Gelertner.
  • Deloitte Global (anonymous contributors).
  • Barry Chudakov, founder and principal at Sertain Research and StreamFuzion Corp.
  • Stephen Downes, staff, National Research Council of Canada,.
  • Bart Knijnenburg, assistant professor in human-centered computing at Clemson University.
  • Justin Reich, executive director at the MIT Teaching Systems Lab.
  • Dudley Irish, tradesman (a coder).
  • Ryan Hayes, owner of Fit to Tweet,.
  • Adam Gismondi, a visiting scholar at Boston College.
  • Susan Etlinger, staff, Altimeter Group.
  • Chris Kutarna, fellow, Oxford Martin School.
  • Vintno Cert, Internet Hall of Fame, vice president and chief internet evangelist at Google:.
  • Cory Doctorow, writer, computer science activist-in-residence at MIT Media Lab and co-owner of Boing Boing.
  • Jonathan Grudin, Microsoft.
  • Doc Searls, director, Project VRM, Berkman Center, Harvard University,.
  • Marc Rotenberg, executive director of the Electronic Privacy Information Center.
  • Richard Stallman, Internet Hall of Fame, president of the Free Software Foundation.
  • David Clark, Internet Hall of Fame, senior research scientist at MIT,.
  • Baratunde Thurston, Director’s Fellow at MIT Media Lab, ex-digital director of The Onion.
  • Anil Dash, pundit.
  • John Markoff, New York Times.
  • Danah Boyd (“danah boyd”), founder, Data & Society, an advocacy group.
  • Henning Schulzrinne, Internet Hall of Fame, professor at Columbia University,.
  • Amy Webb, futurist and CEO at the Future Today Institute.
  • Jamais Cascio, distinguished fellow at the Institute for the Future.
  • Mike Liebhold, senior researcher and distinguished fellow at the Institute for the Future,.
  • Ben Shneiderman, professor of computer science at the University of Maryland,.
  • David Weinberger, senior researcher at the Harvard Berkman Klein Center for Internet & Society.

Referenced

Previously filled.