AI & Law: British Nationality Act Unexpectedly Spurred AI And Law

Stanford CodeX 2021 Prize winner is a keystone paper on AI & Law using the BNA

by Dr. Lance B. Eliot

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Key briefing points about this article:

  • A foundational research paper in the 1980s explored the British Nationality Act
  • The researchers sought to transform the law into AI-based programming code
  • At the time, the Prolog programming language was considered a top means for doing so
  • This seminal work has been oft-cited and provided a foundation in AI and the law
  • The researchers recently received the inaugural Stanford CodeX Prize 2021

Introduction

Let’s take a look at the past and for which we might also divine a glimpse into the future.

The British Nationality Act was passed in 1981 and shortly thereafter was used as a means of showcasing the efficacy of using Artificial Intelligence (AI) techniques and technologies, doing so to explore how the at-the-time newly enacted statutory law might be encoded into a computerized logic-based formalization. A now oft-cited research paper entitled “The British Nationality Act as a Logic Program” was published in 1986 in the prestigious Communication of the ACM and subsequently became a hallmark for subsequent work in AI and the law (for the heralded research paper, see this link here).

Those that are immersed in present-day efforts of intertwining AI and the law owe a debt or proper homage to this pioneering work from the 1980s.

I bring up this foundational work because co-authors Robert Kowalski, Fariba Sadri, and Marek Sogot were honored at this year’s CodeX FutureLaw 2021 annual conference for their pioneering efforts (the event took place online on April 8, 2021, and video recorded sessions are available for viewing). The esteemed researchers were augustly named as the inaugural winners of the Stanford CodeX Prize. FutureLaw is undertaken each year in the Spring by the Stanford Law School and the Stanford CodeX Center for Legal Informatics and focuses on the present day, predicted future, and prior cornerstone efforts underpinning the realm of computational law and LegalTech.

Let’s take a quick look at some key facets of the landmark research paper.

Firstly, there were several other efforts already underway in that era that were trying to apply AI to the law but oftentimes used predominantly made-up examples rather than tackling actual legislature-derived and officially approved statutory laws. Though using concocted exemplars was certainly helpful, there was a sense of urgency about seeking to use real-world legalese and moving into the realm of messiness and complexity thereof.

As the paper stated about choosing the British Nationality Act: “The act embodies all the characteristics of statutes in general: syntactic complexity, vagueness, and reference to previously enacted legislation. In the course of this article, we will describe how the text of a large part of the British Nationality Act 1981 was translated into a simple form of logic, and we will examine some possible applications of this translation.”

The work that they undertook was handy as a large-scale attempt at translating laws into computer-based logic that could then be run or executed. In other words, this is more than simply putting text into a computer system. The notion is that the logic of the law can be encompassed by the coding and therefore the law can be utilized as though it is active and able to be interpreted and applied.

This can ostensibly be used after the fact once a law already exists. The researchers pointed out that such formalized computer-based logic enactment can also be used when laws are initially devised or being drafted: “It means that an executable, logic-based representation of rules and regulations can be used not only to apply the rules but to aid the process of drafting and redrafting the rules in the first place.”

Their research effort was aimed at the core mechanics of transforming legal rules into a form of computer-based logic. This provides a layer for subsequently building more advanced capabilities incorporating AI-based legal reasoning: “Finally, we should stress once again that we have not addressed the broad and much more difficult problem of simulating legal reasoning. Rather, we have concentrated on the limited objective of implementing rules and regulations to apply them mechanically to individual cases.”

The Use of Prolog

The vaunted research paper provided snippets of the programming code developed and which was implemented in a programming language known as Prolog.

Consider an example as based on this legalese portion of the Act: “A newborn infant who, after commencement, is found abandoned in the United Kingdom shall, unless the contrary is shown, be deemed for the purposes of subsection (1): (a) to have been born in the United Kingdom after commencement and (b) to have been born to a parent who at the time of the birth was a British citizen or settled in the United Kingdom.”

This is the Prolog code that they devised to represent this indication:

> x is a British citizen

> if x was found as a newborn infant abandoned in the U.K.

> and x was found on date y

> and y is after or on commencement and not [x was not born in the U.K. after or on commencement]

> and not [x was not born to a parent who qualifies under 1.1 at time of birth]

For those of you further interested in the Prolog programming language for use in AI and the law, I’ve covered Prolog and other logic-based programming languages in my writings, along with an extensive up-to-date look at the use of more advanced AI capabilities including contemporary Machine Learning (ML) and Deep Learning. For details on this and other AI and law topics, including a rudimentary explanation about Prolog, see my book entitled “AI and Legal Reasoning Essentials” at this link here: https://www.amazon.com/Legal-Reasoning-Essentials-Artificial-Intelligence/dp/1734601655

Conclusion

Per the famous sage wisdom by George Santayana, we must make sure to acknowledge and remember the past: “Progress, far from consisting in change, depends on retentiveness. Those who cannot remember the past are condemned to repeat it.”

Our deepest thanks ought to go to the many legal scholars, legal professionals, and AI developers that have labored to make progress in the realm of AI and the law, and it is important to provide a tip of the hat from time to time to ensure that we remember and build upon those revered prior efforts accordingly.

For the latest trends about AI & Law, visit our website www.ai-law.legal

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Copyright © 2021 Dr. Lance Eliot. All Rights Reserved.

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