From the abstract of Yale Law prof Jack Balkin’s The Three Laws of Robotics in the Age of Big Data, 78 Ohio State Law Journal ___ (2017)(Forthcoming):

This essay introduces these basic legal principles using four key ideas: (1) the homunculus fallacy; (2) the substitution effect; (3) the concept of information fiduciaries; and (4) the idea of algorithmic nuisance.

The homunculus fallacy is the attribution of human intention and agency to robots and algorithms. It is the false belief there is a little person inside the robot or program who has good or bad intentions.

The substitution effect refers to the multiple effects on social power and social relations that arise from the fact that robots, AI agents, and algorithms substitute for human beings and operate as special-purpose people.

The most important issues in the law of robotics require us to understand how human beings exercise power over other human beings mediated through new technologies. The “three laws of robotics” for our Algorithmic Society, in other words, should be laws directed at human beings and human organizations, not at robots themselves.

Behind robots, artificial intelligence agents and algorithms are governments and businesses organized and staffed by human beings. A characteristic feature of the Algorithmic Society is that new technologies permit both public and private organizations to govern large populations. In addition, the Algorithmic Society also features significant asymmetries of information, monitoring capacity, and computational power between those who govern others with technology and those who are governed.

With this in mind, we can state three basic “laws of robotics” for the Algorithmic Society:

First, operators of robots, algorithms and artificial intelligence agents are information fiduciaries who have special duties of good faith and fair dealing toward their end-users, clients and customers.

Second, privately owned businesses who are not information fiduciaries nevertheless have duties toward the general public.

Third, the central public duty of those who use robots, algorithms and artificial intelligence agents is not to be algorithmic nuisances. Businesses and organizations may not leverage asymmetries of information, monitoring capacity, and computational power to externalize the costs of their activities onto the general public. The term “algorithmic nuisance” captures the idea that the best analogy for the harms of algorithmic decision making is not intentional discrimination but socially unjustified “pollution” – that is, using computational power to make others pay for the costs of one’s activities.

Obligations of transparency, due process and accountability flow from these three substantive requirements. Transparency – and its cousins, accountability and due process – apply in different ways with respect to all three principles. Transparency and/or accountability may be an obligation of fiduciary relations, they may follow from public duties, and they may be a prophylactic measure designed to prevent unjustified externalization of harms or in order to provide a remedy for harm.

Very interesting. — Joe

Here’s the blurb for Joanna Goodman’s Robots in Law: How Artificial Intelligence is Transforming Legal Services:

Although 2016 was a breakthrough year for artificial intelligence (AI) in legal services in terms of market awareness and significant take-up, legal AI represents evolution rather than revolution. Since the first ‘robot lawyers’ started receiving mainstream press coverage, many law firms, other legal service providers and law colleges are being asked what they are doing about AI. Robots in Law: How Artificial Intelligence is Transforming Legal Services is designed to provide a starting point in the form of an independent primer for anyone looking to get up to speed on AI in legal services. The book is organized into four distinct sections: Part I: Legal AI – Beyond the hype Part II: Putting AI to work Part III: AI giving back – Return on investment Part IV: Looking ahead The first three present an in-depth overview, and analysis, of the current legal AI landscape; the final section includes contributions from AI experts with connections to the legal space, on the prospects for legal AI in the short-term future. Along with the emergence of New Law and the burgeoning lawtech start-up economy, AI is part of a new dynamic in legal technology and it is here to stay. The question now is whether AI will find its place as a facilitator of legal services delivery, or whether it will initiate a shift in the value chain that will transform the legal business model.

For more, see Bob Ambrogi’s This Week In Legal Tech column (ATL). — Joe

Law bloggers frequently cite to primary sources but most offer no links to them because the sources they use reside behind a paywall, be it Bloomberg, LexisNexis or Thomson Reuters. For LexBlog bloggers, the paywall problem has been resolved by the integration of Fastcase’s legal search service into LexBlog’s WordPress platform. Now clicking on a LexBlog link will display within the same browser interface primary law sourced by Fastcase. For details, see Kevin O’Keefe’s LexBlog launches Fastcase integration. — Joe

Hoping to represent a class of consumers who bought LN’s New York Landload-Tennat Law (aka the Tanbook), the law firm of Himmelstein, McConnell, Gribben, Donoghue & Joseph brought a Feb. 23 complaint against the publisher in Manhattan Supreme Court.

“Rather than an authoritative source of state statutes, laws and regulations, the Tanbook, which is represented by the defendant as complete and unedited, is instead, at least as pertains to those involving rent regulated housing in New York rife with omissions and inaccuracies, rendering it of no value to the attorneys, lay people, or judges who use it,” the 25-page complaint states.

Details at Class Calls LexisNexis Publication Totally Useless (Courthouse News Service). Hat tip to and see also Jean O’Grady’s Dewey B Strategic post. — Joe

In The Best Apps To Track Trump’s Legal Changes, Bob Ambrogi identifies three apps designed to monitor the Trump administration’s actions.

  1. The goal of Track Trump is “to isolate actual policy changes from rhetoric and political theater and to hold the administration accountable for the promises it made.”
  2. The Cabinet Center for Administrative Transition (CCAT) from the law firm Cadwalader, Wickersham & Taft collects “pronouncements, position papers, policy statements, and requirements as to legislative and regulatory change related to the financial service agenda of the President, the new administration and the new Congress. It tracks legislative developments, executive orders, policy positions, regulations, the regulators themselves, and relevant Trump administration news.”
  3. Columbia Law School’s Trump Human Rights Tracker follows the Trump administration’s actions and their implications for human rights.

— Joe

Here’s the abstract for Opening the Black Box: In Search of Algorithmic Transparency by Rachel Pollack Ichou (University of Oxford, Oxford Internet Institute):

Given the importance of search engines for public access to knowledge and questions over their neutrality, there have been many theoretical debates about the regulation of the search market and the transparency of search algorithms. However, there is little research on how such debates have played out empirically in the policy sphere. This paper aims to map how key actors in Europe and North America have positioned themselves in regard to transparency of search engine algorithms and the underlying political and economic ideas and interests that explain these positions. It also discusses the strategies actors have used to advocate for their positions and the likely impact of their efforts for or against greater transparency on the regulation of search engines. Using a range of qualitative research methods, including analysis of textual material and elite interviews with a wide range of stakeholders, this paper concludes that while discussions around algorithmic transparency will likely appear in future policy proposals, it is highly unlikely that search engines will ever be legally required to share their algorithms due to a confluence of interests shared by Google and its competitors. It ends with recommendations for how algorithmic transparency could be enhanced through qualified transparency, consumer choice, and education.

— Joe

Berkeley J. Dietvorst, The University of Chicago Booth School of Business, Joseph P. Simmons, University of Pennsylvania, The Wharton School, and Cade Massey, University of Pennsylvania, The Wharton School, Algorithm Aversion: People Erroneously Avoid Algorithms after Seeing Them Err, Journal of Experimental Psychology: General (forthcoming).

Abstract: Research shows that evidence-based algorithms more accurately predict the future than do human forecasters. Yet, when forecasters are deciding whether to use a human forecaster or a statistical algorithm, they often choose the human forecaster. This phenomenon, which we call algorithm aversion, is costly, and it is important to understand its causes. We show that people are especially averse to algorithmic forecasters after seeing them perform, even when they see them outperform a human forecaster. This is because people more quickly lose confidence in algorithmic than human forecasters after seeing them make the same mistake. In five studies, participants either saw an algorithm make forecasts, a human make forecasts, both, or neither. They then decided whether to tie their incentives to the future predictions of the algorithm or the human. Participants who saw the algorithm perform were less confident in it, and less likely to choose it over an inferior human forecaster. This was true even among those who saw the algorithm outperform the human.

In White House posts wrong versions of Trump’s orders on its website, USA Today reports that the texts of at least five Trump executive orders hosted on the White House website do not match the official text sent to the Federal Register. Quoting from the USA Today article, examples include:

► The controversial travel ban executive order suspended the Visa Interview Waiver Program and required the secretary of State to enforce a section of the Immigration and Naturalization Act requiring an in-person interview for everyone seeking a non-immigrant visa. But the White House version of the order referred to that provision as 8 U.S.C. 1222, which requires a physical and mental examination — not 8 U.S.C. 1202, which requires an interview.

► An executive order on ethical standards for administration appointees, as it appears on the White House website, refers to”section 207 of title 28″ of the U.S. Code. As the nonprofit news site Pro Publica reported last week, that section does not exist. The Federal Register correctly cited section 207 of title 18, which does exist.

— Joe

Here’s the abstract for Susan Nevelow Mart’s very interested article The Algorithm as a Human Artifact: Implications for Legal {Re}Search (SSRN):

Abstract: When legal researchers search in online databases for the information they need to solve a legal problem, they need to remember that the algorithms that are returning results to them were designed by humans. The world of legal research is a human-constructed world, and the biases and assumptions the teams of humans that construct the online world bring to the task are imported into the systems we use for research. This article takes a look at what happens when six different teams of humans set out to solve the same problem: how to return results relevant to a searcher’s query in a case database. When comparing the top ten results for the same search entered into the same jurisdictional case database in Casetext, Fastcase, Google Scholar, Lexis Advance, Ravel, and Westlaw, the results are a remarkable testament to the variability of human problem solving. There is hardly any overlap in the cases that appear in the top ten results returned by each database. An average of forty percent of the cases were unique to one database, and only about 7% of the cases were returned in search results in all six databases. It is fair to say that each different set of engineers brought very different biases and assumptions to the creation of each search algorithm. One of the most surprising results was the clustering among the databases in terms of the percentage of relevant results. The oldest database providers, Westlaw and Lexis, had the highest percentages of relevant results, at 67% and 57%, respectively. The newer legal database providers, Fastcase, Google Scholar, Casetext, and Ravel, were also clustered together at a lower relevance rate, returning approximately 40% relevant results.

Legal research has always been an endeavor that required redundancy in searching; one resource does not usually provide a full answer, just as one search will not provide every necessary result. The study clearly demonstrates that the need for redundancy in searches and resources has not faded with the rise of the algorithm. From the law professor seeking to set up a corpus of cases to study, the trial lawyer seeking that one elusive case, the legal research professor showing students the limitations of algorithms, researchers who want full results will need to mine multiple resources with multiple searches. And more accountability about the nature of the algorithms being deployed would allow all researchers to craft searches that would be optimally successful.

Recommended. — Joe

And here they are:

Vice President/President-Elect

Kathleen (Katie) Brown
Associate Dean for Library Services
Charlotte School of Law

Femi Cadmus
Edward Cornell Law Librarian &
Associate Dean for Library Services
Cornell University Law Library

Secretary

Luis Acosta
Law Library of Congress
Chief, Foreign, Comparative, and International Law Division II

Scott D. Bailey
Global Director of Research Services
Squire Patton Boggs LLP

Board Members (pick two)
 
Beth Adelman
Director of the Law Library &
Vice Dean for Legal Information Services
The University at Buffalo
State University of New York

Katherine M. Lowry, JD
Director of Practice Services
Baker Hostetler LLP

Catherine M. Monte
Chief Knowledge Officer
Fox Rothschild LLP

Jean P. O’Grady
Director of Research & Knowledge Services
DLA Piper

The election will be held September 30 to October 31, and successful candidates will begin their terms of office in July 2017. — Joe

Applied First Amendment Jurisprudence for Public Libraries [SSRN] by Marc Lowell discusses “the historic pathway of key [First Amendment] cases that bring the relevant law regarding the physical space of the public library.” Here’s the abstract:

Whether the physical space of a public library is entitled to some degree of special protection under First Amendment jurisprudence is of great import to public library administrators for a variety of reasons that include the development of patron behavior policies, patron interaction and staff training, and reducing the probability of litigation involving the infringement of First Amendment rights of patrons. This paper discusses the legal intersection of First Amendment protections and public library spaces and suggests constructive steps public libraries may take to reduce risks of litigation, legal costs, and exposure to First Amendment hazards with patrons.

Recommended. — Joe

Legal software publishing companies and legal application developers that serve the public directly beware. A discussion paper from the ABA Commission on the Future of Legal Services is inviting comments on proposing a regulatory scheme that would impose restrictions on currently unregulated, non-traditional legal service providers. See Issues Paper Concerning Unregulated LSP Entities (March 31, 2016). Is the ABA protecting the “public interest” or attempting to expand its control over competitive threats to the organized bar’s hegemony? — Joe