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Review of Frank Pasquale’s “A Rule of Persons, Not Machines: The Limits of Legal Automation” – Article by Adam Alonzi

Review of Frank Pasquale’s “A Rule of Persons, Not Machines: The Limits of Legal Automation” – Article by Adam Alonzi

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Adam Alonzi


From the beginning Frank Pasquale, author of The Black Box Society: The Secret Algorithms That Control Money and Information, contends in his new paper “A Rule of Persons, Not Machines: The Limits of Legal Automation” that software, given its brittleness, is not designed to deal with the complexities of taking a case through court and establishing a verdict. As he understands it, an AI cannot deviate far from the rules laid down by its creator. This assumption, which is not even quite right at the present time, only slightly tinges an otherwise erudite, sincere, and balanced coverage of the topic. He does not show much faith in the use of past cases to create datasets for the next generation of paralegals, automated legal services, and, in the more distant future, lawyers and jurists.

Lawrence Zelanik has noted that when taxes were filed entirely on paper, provisions were limited to avoid unreasonably imposing irksome nuances on the average person. Tax-return software has eliminated this “complexity constraint.” He goes on to state that without this the laws, and the software that interprets it, are akin to a “black box” for those who must abide by them. William Gale has said taxes could be easily computed for “non-itemizers.” In other words, the government could use information it already has to present a “bill” to this class of taxpayers, saving time and money for all parties involved. However, simplification does not always align with everyone’s interests. TurboTax’s business, which is built entirely on helping ordinary people navigate the labyrinth is the American federal income tax, noticed a threat to its business model. This prompted it to put together a grassroots campaign to fight such measures. More than just another example of a business protecting its interests, it is an ominous foreshadowing of an escalation scenario that will transpire in many areas if and when legal AI becomes sufficiently advanced.  

Pasquale writes: “Technologists cannot assume that computational solutions to one problem will not affect the scope and nature of that problem. Instead, as technology enters fields, problems change, as various parties seek to either entrench or disrupt aspects of the present situation for their own advantage.”

What he is referring to here, in everything but name, is an arms race. The vastly superior computational powers of robot lawyers may make the already perverse incentive to make ever more Byzantine rules ever more attractive to bureaucracies and lawyers. The concern is that the clauses and dependencies hidden within contracts will quickly explode, making them far too detailed even for professionals to make sense of in a reasonable amount of time. Given that this sort of software may become a necessary accoutrement in most or all legal matters means that the demand for it, or for professionals with access to it, will expand greatly at the expense of those who are unwilling or unable to adopt it. This, though Pasquale only hints at it, may lead to greater imbalances in socioeconomic power. On the other hand, he does not consider the possibility of bottom-up open-source (or state-led) efforts to create synthetic public defenders. While this may seem idealistic, it is fairly clear that the open-source model can compete with and, in some areas, outperform proprietary competitors.

It is not unlikely that within subdomains of law that an array of arms races can and will arise between synthetic intelligences. If a lawyer knows its client is guilty, should it squeal? This will change the way jurisprudence works in many countries, but it would seem unwise to program any robot to knowingly lie about whether a crime, particularly a serious one, has been committed – including by omission. If it is fighting against a punishment it deems overly harsh for a given crime, for trespassing to get a closer look at a rabid raccoon or unintentional jaywalking, should it maintain its client’s innocence as a means to an end? A moral consequentialist, seeing no harm was done (or in some instances, could possibly have been done), may persist in pleading innocent. A synthetic lawyer may be more pragmatic than deontological, but it is not entirely correct, and certainly shortsighted, to (mis)characterize AI as only capable of blindly following a set of instructions, like a Fortran program made to compute the nth member of the Fibonacci series.

Human courts are rife with biases: judges give more lenient sentences after taking a lunch break (65% more likely to grant parole – nothing to spit at), attractive defendants are viewed favorably by unwashed juries and trained jurists alike, and the prejudices of all kinds exist against various “out” groups, which can tip the scales in favor of a guilty verdict or to harsher sentences. Why then would someone have an aversion to the introduction of AI into a system that is clearly ruled, in part, by the quirks of human psychology?  

DoNotPay is an an app that helps drivers fight parking tickets. It allows drivers with legitimate medical emergencies to gain exemptions. So, as Pasquale says, not only will traffic management be automated, but so will appeals. However, as he cautions, a flesh-and-blood lawyer takes responsibility for bad advice. The DoNotPay not only fails to take responsibility, but “holds its client responsible for when its proprietor is harmed by the interaction.” There is little reason to think machines would do a worse job of adhering to privacy guidelines than human beings unless, as mentioned in the example of a machine ratting on its client, there is some overriding principle that would compel them to divulge the information to protect several people from harm if their diagnosis in some way makes them as a danger in their personal or professional life. Is the client responsible for the mistakes of the robot it has hired? Should the blame not fall upon the firm who has provided the service?

Making a blockchain that could handle the demands of processing purchases and sales, one that takes into account all the relevant variables to make expert judgements on a matter, is no small task. As the infamous disagreement over the meaning of the word “chicken” in Frigaliment v. B.N.S International Sales Group illustrates, the definitions of what anything is can be a bit puzzling. The need to maintain a decent reputation to maintain sales is a strong incentive against knowingly cheating customers, but although cheating tends to be the exception for this reason, it is still necessary to protect against it. As one official on the  Commodity Futures Trading Commission put it, “where a smart contract’s conditions depend upon real-world data (e.g., the price of a commodity future at a given time), agreed-upon outside systems, called oracles, can be developed to monitor and verify prices, performance, or other real-world events.”  

Pasquale cites the SEC’s decision to force providers of asset-backed securities to file “downloadable source code in Python.” AmeriCredit responded by saying it  “should not be forced to predict and therefore program every possible slight iteration of all waterfall payments” because its business is “automobile loans, not software development.” AmeriTrade does not seem to be familiar with machine learning. There is a case for making all financial transactions and agreements explicit on an immutable platform like blockchain. There is also a case for making all such code open source, ready to be scrutinized by those with the talents to do so or, in the near future, by those with access to software that can quickly turn it into plain English, Spanish, Mandarin, Bantu, Etruscan, etc.

During the fallout of the 2008 crisis, some homeowners noticed the entities on their foreclosure paperwork did not match the paperwork they received when their mortgages were sold to a trust. According to Dayen (2010) many banks did not fill out the paperwork at all. This seems to be a rather forceful argument in favor of the incorporation of synthetic agents into law practices. Like many futurists Pasquale foresees an increase in “complementary automation.” The cooperation of chess engines with humans can still trounce the best AI out there. This is a commonly cited example of how two (very different) heads are better than one.  Yet going to a lawyer is not like visiting a tailor. People, including fairly delusional ones, know if their clothes fit. Yet they do not know whether they’ve received expert counsel or not – although, the outcome of the case might give them a hint.

Pasquale concludes his paper by asserting that “the rule of law entails a system of social relationships and legitimate governance, not simply the transfer and evaluation of information about behavior.” This is closely related to the doubts expressed at the beginning of the piece about the usefulness of data sets in training legal AI. He then states that those in the legal profession must handle “intractable conflicts of values that repeatedly require thoughtful discretion and negotiation.” This appears to be the legal equivalent of epistemological mysterianism. It stands on still shakier ground than its analogue because it is clear that laws are, or should be, rooted in some set of criteria agreed upon by the members of a given jurisdiction. Shouldn’t the rulings of law makers and the values that inform them be at least partially quantifiable? There are efforts, like EthicsNet, which are trying to prepare datasets and criteria to feed machines in the future (because they will certainly have to be fed by someone!).  There is no doubt that the human touch in law will not be supplanted soon, but the question is whether our intuition should be exalted as guarantee of fairness or a hindrance to moving beyond a legal system bogged down by the baggage of human foibles.

Adam Alonzi is a writer, biotechnologist, documentary maker, futurist, inventor, programmer, and author of the novels A Plank in Reason and Praying for Death: A Zombie Apocalypse. He is an analyst for the Millennium Project, the Head Media Director for BioViva Sciences, and Editor-in-Chief of Radical Science News. Listen to his podcasts here. Read his blog here.

U.S. Transhumanist Party Discussion Panel on Artificial Intelligence – January 8, 2017

U.S. Transhumanist Party Discussion Panel on Artificial Intelligence – January 8, 2017

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Gennady Stolyarov II


The U.S. Transhumanist Party’s first expert discussion panel, hosted in conjunction with the Nevada Transhumanist Party, asked panelists to consider emerging developments in artificial intelligence.

The panel took place on Sunday, January 8, 2017, at 10 a.m. U.S. Pacific Time.

Key questions addressed include the following:

(i) What do you think will be realistic, practical applications of artificial intelligence toward improving human lives during the next 5 years?
(ii) Are you genuinely concerned about existential risk stemming from AI, or do you think those concerns are exaggerated / overhyped (or do you have some intermediate position on these issues)?
(iii) On the other hand, do you perceive significant tendencies in contemporary culture to overhype the positive / functional capabilities of AI?
(iv) How can individuals, particularly laypersons, become better at distinguishing between genuine scientific and technological advances in AI and hype / fear-mongering?
(v) What is your techno-optimistic vision for how AI can help improve the future of human (and transhuman) beings?
(vi) What are your thoughts regarding prognostications of an AI-caused technological Singularity? Are they realistic?

Panelists

Zak Field is an international speaker, consultant, games designer, and entrepreneur based in Norwich, UK. A rising thought leader in Mixed Realities (VR/AR), Zak speaks and consults on Mixed Realities-related topics like gamification, Virtual Reality (VR), Augmented Reality (AR), Robotics, Artificial Intelligences (AIs), and the Internet of Things (IoT).

In 2015, Zak partnered with Futurist Miss Metaverse as co-founder of BodAi, a robotics and AI company developing Bods, lifelike humanoid robot companions made accessible through a unique system that accommodates practical 21st-Century business and lifestyle needs.

David J. Kelley is the CTO for the tech venture capital firm Tracy Hall LLC, focused on companies that contribute to high-density sustainable community technologies, as well as the principal scientist with Artificial General Intelligence Inc. David also volunteers as the Chairman of the Transhuman National Committee board. David’s career has been built on technology trends and bleeding each research primarily around the capitalization of product engineering where those new products can be brought to market and made profitable. David’s work on Artificial Intelligence in particular – the ICOM research project with AGI Inc. – is focused on emotion-based systems that are designed to work around human constraints and help remove the ‘human’ element from the design of AI systems, including military applications for advanced self-aware cognitive systems that do not need human interaction.

Hiroyuki Toyama is a Japanese doctoral student at the Department of Psychology in University of Jyväskylä, Finland. His doctoral study has focused on emotional intelligence (EI) in the context of personality and health psychology. In particular, he has attempted to shed light on the way in which trait EI is related to subjective well-being and physiological health. He has a great interest in the future development of artificial EI on the basis of contemporary theory of EI.

Mark Waser is Chief Technology Officer of the Digital Wisdom Institute and D161T4L W15D0M Inc., organizations devoted to the ethical implementation of advanced technologies for the benefit of all. He has been publishing data science research since 1983 and developing commercial AI software since 1984, including an expert system shell and builder for Citicorp, a neural network to evaluate thallium cardiac images for Air Force pilots and, recently, mobile front-ends for cloud-based AI and data science. He is particularly interested in safe ethical architectures and motivational systems for intelligent machines (including humans). As an AI ethicist, he has presented at numerous conferences and published articles in international journals. His current projects can be found at the Digital Wisdom website – http://wisdom.digital/

Demian Zivkovic is CEO+Structure of Ascendance Biomedical, president of the Institute of Exponential Sciences, as well as a scholar of several scientific disciplines. He has been interested in science, particularly neuropsychology, astronomy, and biology from a very young age. His greatest passions are cognitive augmentation and life extension, two endeavors he remains deeply committed to, to this day. He is also very interested in applications of augmented reality and hyperreality, which he believes have incredible potential for improving our lives.

He is a strong believer in interdisciplinarity as a paradigm for understanding the world. His studies span artificial intelligence, innovation science, and business, which he has studied at the University of Utrecht. He also has a background in psychology, which he has previously studied at the Saxion University of Applied Sciences. Demian has co-founded Ascendance Biomedical, a Singapore-based company focused on cutting edge biomedical services. Demian believes that raising capital and investing in technology and education is the best route to facilitate societal change. As a staunch proponent of LGBT rights and postgenderism, Demian believes advanced technologies can eventually provide a definite solution for sex/gender-related issues in society.