Litigating with Technology in Friendly Terms: The AI Case
By: Geek Lawtinas
Tags: Artificial Intelligence, Lawtinas, Lawyers, Latinas In Tech, Inteligencia Artificial

It was getting to seem like you can’t listen to analysis on Artificial Intelligence without hearing the same tiresome fear of how it will leave us all out of jobs. Dr. Maura Grossman was the guest speaker last Thursday in our Emerging Tech & the Practice of Law class at Syracuse Law. Her presentation was informative, eye-opening and particularly inspiring for all the legal professionals who were listening to her with close attention.

The legal field has been historically conservative. Regardless of their generation, lawyers are usually skeptical of incorporating technology into their work. Artificial Intelligence, in particular, seems to be the threat of threats when it comes to considering emerging technologies in the practice of law. It is, conversely, a unique opportunity for lawyers to renovate our profession, maximize productivity, and deliver our clients the best results.

Artificial Intelligence, or AI, is an umbrella concept that escapes easy definitions. The term was first used in 1956 in Dartmouth College to refer to the technology, or software, “that could reproduce or accomplish things that were originally thought to be the province of humans, mostly cognitive activities.”[1] Today, with the evolution of AI and the impact of other technologies like big data,[2] high-performance computers,[3] and cloud computing,[4] humans produce huge amounts of data and have enormous computer power available to help a machine behave intelligently.

There are three types of AI:

Narrow AI, which can facilitate individual, repetitive tasks by learning from patterns found in data. AI today falls under this category.

Artificial General Intelligence, which refers to a single system “capable of performing all of the intellectual tasks that a human brain can.”[5] It is a notional concept that has not yet been developed in real life. This includes reasoning, learning, and problem-solving in complex and changing environments.[6]

Artificial Superintelligence is a hypothetical type of artificial intelligence “that surpasses human intellect and abilities in nearly all areas.”[7]

Machine Learning, the subdiscipline within AI around which the current hype cycle[8] revolves, is a pattern recognition technique based on algorithms. It enables computer systems to learn and make predictions based on historical data. Deep Learning, furthermore, is a subdomain of Machine Learning that consists of multiple cascading layers of data learning, modeled after the human nervous system with an artificial neural network approach.[9]

There is a lot of misinformation involving emerging technologies because of the fear that they can potentially escape our control. And that is partially true. For example, Blockchain enables the execution of autonomous code, which over time, may also provide the infrastructure to create organizations that rely entirely on algorithmic systems and AI to manage their activity.[10] Moreover, if not properly regulated, these emerging technologies can be useful to commit fraud and engage in money laundering, terrorist financing,[11] or other illicit activities.[12]

So, how does all this influence my legal practice? Will a robot take over my firm? It is cautious to calm down the anxiety with a myths and facts chart (Table 1). Knowing what AI can and cannot do — at least so far — will lead us to the role of AI in the practice of law.

Table 1 Based on “Benefits & Risks of Artificial Intelligence”[13]

Progress in AI has shown tremendous potential benefits in improving efficiency and savings in many industries, and the legal practice is next. Let’s consider a few examples. AI and Law researchers have developed computational models to perform legal reasoning (CMLRs). These models can generate arguments for and against particular outcomes in problems inputs, and explain their predictions with reasons that legal professionals can recognize and evaluate for themselves. The result is a collaborative activity between humans and computers in which each performs the kinds of intelligent activities that they can do best.[14]

Another example derives from the process of discovery, which involves identifying, preserving, collecting, analyzing, and producing evidence in legal actions.[15] E-Discovery, moreover, is the discovery of information and data that is stored electronically, and today, the vast majority of records are created and maintained electronically. Professors Gordon V. Cormack and Maura Grossman from the University of Waterloo studied if training documents for technology-assisted review for discovery in legal proceedings should be selected at random, or using one or more non-random methods, such as keyword search.[16]

For their study, they set up and ingenious scientific experiment to test the effectiveness of three machine-learning protocols: Continuous Active Learning (CAL), Simple Active Learning (SAL), and Simple Passive Learning (SPL).[17] Among their inferences, they found that CAL offers the reviewer the opportunity to quickly identify legal significant documents that can guide litigation strategy, and that the seed and training sets must be randomly selected to avoid “biasing” the learning algorithm.[18]

Furthermore, teams from Stanford and Suffolk Law have collected thousands of online questions about possible legal issues to start developing a data set that can serve to train a natural language processor (NLP), which is a subset of AI focused on understanding context in speech. An NLP could recognize that people who seek information online about getting “kicked out” of their rental property, without using the legal term “eviction,” need insight into eviction law. [19] So, they created an online game, Learned Hands[20] to increase the data available to help build NLPs.

With the above in mind, it is evident that there is plenty of room for lawyers to benefit from technology. Artificial Intelligence has a lot of potential in the legal tech industry to make our practice more efficient and cost-effective. The Stanford/Suffolk game also shows that it can make access to justice less of a privilege. Prof. Grossman’s presentation was encouraging to keep learning about technology in the legal practice. And for those who still resist, there is terrible news: As per ABA Model Rule of Professional Conduct 1.1 amendment of 2012, it is no longer an option but an ethical duty for all lawyers to learn about technology![21]

[1] New York State Bar Association. 2018. NYSBA — Artificial Intelligence | Maura Grossman and Mark Berman. January 5. Accessed September 13, 2019. https://www.youtube.com/watch?v=m1o7fT1aTAU. See also Sarangi, Saswat, and Pankaj Sharma. 2019. Artificial Intelligence: Evolution, Ethics, and Public Policy. London and New York: Routledge, at 16.

[2] Davis, Nick. 2019. Artificial Intelligence and Big Data: A Powerful Combination for Future Growth. March 21. Accessed September 13, 2019. https://su.org/blog/artificial-intelligence-and-big-data-a-powerful-combination-for-future-growth/.

[3] Inside HPC. 2019. The Convergence of HPC and AI. August 4. Accessed September 13, 2019. https://insidehpc.com/2019/08/the-convergence-of-hpc-and-ai/.

[4] Google. 2019. AI and machine learning products. Accessed September 13, 2019. https://cloud.google.com/products/ai/.

[5] Centre for Public Impact. 2017. Destination unknown: Exploring the impact of Artificial Intelligence on Government. . Accessed Septemer 13, 2019. https://publicimpact.blob.core.windows.net/ production/2017/09/Destination-Unknown-AI-and-government.pdf.; in Brookfield Institute. 2018. Intro to AI for Policymakers: Understanding the shift. March. Accessed September 13, 2019. https://brookfieldinstitute.ca/report/intro-to-ai-for-policymakers/.

[6] Brookfield Institute, 2018.

[7] Centre for Public Impact, 2017, in Brookfield Institute, 2018.

[8] Spotless Data. 2018. Amara’s Law. April 10. Accessed September 13, 2019. https://spotlessdata.com/blog/amaras-law.

[9] Brookfield Institute, 2018.

[10] De Filippi, Primavera, and Aaron Wright. 2018. Blockchain and the Law. Cambridge, MA: Harvard University Press.

[11] De Filippi and Wright, 2018, at 4.

[12] European Securitites and Markets Authority. 2017. The Distributed Ledger Technology Applied to Securities Markets. ESMA50–1121423017–285, ESMA.

[13] Tegmark, Max. 2016. Benefits & Risks of Artificial Intelligence. Accessed September 13, 2019. https://futureoflife.org/background/benefits-risks-of-artificial-intelligence/?cn-reloaded=1.

[14] Ashley, Kevin. 2017. Artificial Intelligence and Legal Analytics: New Tools for Law Practice in the Digital Age. Cambridge: Cambridge University Press. In this book, Ashley also examines recently developed techniques for extracting conceptual information automatically from legal text, including extracting semantic information automatically from statutes and legal decisions. He also explores how the new text processing tools can connect the CMLRs so they can deal directly with legal digital document technologies to assist humans in predicting and justifying legal outcomes.

[15] Scheindlin, Shira A. 2016. Electronic Discovery and Digital Evidence (Second Edition). St. Paul: West Academic Publishing.

[16] Cormack, Gordon V., and Maura R. Grossman. 2014. “Evaluation of machine-learning protocols for technology-assisted review in electronic discovery.” SIGIR ’14 Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval 153–162. https://dl.acm.org/citation.cfm?doid=2600428.2609601.

[17] Losey, Ralph C. 2016. “Reflections on the Cormack and Grossman SIGIR Study.” In Perspectives on Predictive Coding and Other Advanced Search Methods for the Legal Practitioner, by Jason R. Baron, Ralph C. Losey and Michael D. Berman, 107–142. Chicago: American Bar Association.

[18] Cormack and Grossman, 2014, at 160.

[19] Rickard, Erika, and Lester Bird. 2019. How Artificial Intelligence Could Improve Access to Legal Information. January 24. Accessed September 13, 2019. https://www.pewtrusts.org/en/research-and-analysis/articles/2019/01/24/how-artificial-intelligence-could-improve-access-to-legal-information.

[20] <https://learnedhands.law.stanford.edu/app>.

[21] See American Bar Association. 2012. Rule 1.1 Competence — Comment. Accessed September 13, 2019. https://www.americanbar.org/groups/professional_responsibility/publications/model_rules_of_professional_conduct/rule_1_1_competence/comment_on_rule_1_1/ and Black, Nicole. 2018. Practicing Law in the 21st Century: The Ethical Requirement of Technology Competence. December 20. Accessed September13 2019. https://www.americanbar.org/groups/gpsolo/publications/gp_solo/2018/november-december/practicing-law-21st-century/.