What is AI? Why is its integration in law school curricula so important?
The Stanford 鈥樷�� defines AI as a set of computational technologies that can perform tasks that require humans thinking, learning, and reasoning. AI functions by combining large sets of data with intelligent algorithms to learn patterns in the data and make decisions based on those patterns. AI is becoming increasingly ubiquitous across sectors of society. From immigration, policing, to insurance, AI鈥檚 influence knows no bounds. A report by outlined the 鈥渋mpacts of automated decision-making in Canada鈥檚 immigration and refugee system鈥�. It highlights the federal government鈥檚 experiments with adopting predicative analytics to automate activities normally done by immigration officials, such as evaluating immigrant and visitor applications. Using AI in the immigration and refugee application process has far reaching implications. Many refugee and immigration claims are nuanced and complex which AI decision-making technology may not be equipped to handle. The inability to detect nuance may lead to discriminatory and biased practices to vulnerable communities such as who may not be afforded adequate human rights protections and resources to defend themselves against these discriminatory practices.
AI is also present in that use algorithms and historical data to predict where crimes are most likely to occur and by whom in order to allocate police resources. The predictive policing system also assesses risks through the creation of profiles for individuals in the criminal justice system based on age, criminal record, employment history, and social affiliations. These profiles are then used by various members of the criminal justice system to determine whether an individual should be imprisoned, directed to social services, or surveilled by law enforcement. However, predictive systems use data that rely on, among other metrics, crime reports that do not accurately reflect crime that actually happens in the community. The type of crimes that are reported and enforcement practices themselves can be biased, for example black Americans are than white Americans who use it at a similar rate. This type of data then works to reinforce discriminatory police enforcement as the predictive systems may not account for biases and inaccuracies in the historical data.
A final example to illustrate the wide reach of artificial intelligence is its use in determining car insurance rates. AI and machine learning technologies are often used by using large data sets such as credit scores, homeownership, geographic location, and motor vehicle records. Although these data sets may be predictive of insurance risk they also correlate with race and are often reflective of decades of discrimination and societal bias. A has found that in many cases major insurance companies were charging insurance premiums up to 30% higher for residents who lived in zip codes with a high minority population as opposed to 鈥渨hiter neighbourhoods with similar accident costs鈥�. Given that auto insurance is required by the law in almost all American states and Canadian provinces the impact on disparate and discriminatory pricing can often be a hurdle to upward mobility and often increase the burden on low-income individuals who cannot afford it.
With AI鈥檚 far-reaching application, a host of ethical implications are to be considered especially by future jurists. Governments and private sectors continue to delegate responsibilities and decision-making processes to automated systems under the assumption of 鈥溾��. As illustrated these technologies are vulnerable to discrimination, bias, and error. AI can replicate the biases of the individual who designed it or biases within its selected data which can magnify patterns of discrimination that exist in society. Given the impact of AI on justice and equality across all fields of law, AI should be addressed in an integrated manner in law school curricula. The integration of the study of AI throughout the curriculum will prepare law students to tackle the various challenges they are sure to meet in an AI-driven world.
Expert opinion on the importance of law students being equipped to tackle AI-related challenges
There is a general consensus that law schools do not prepare their students for evolving technological realities. The is often attributed to the legal profession being self-regulated and changes only occur when outside forces require them to. Some claim the occurred over 130 years ago when Christopher Columbus Langdell and James Barr Ames of Harvard Law School invented the case method of teaching the law. Of course, changes in legal education have occurred such as efforts to make legal education more practice relevant and reflective of a changing society.
For example, clinical legal education has been a feature in for decades and, for some years now, is expanding in as well. Clinics provide students with practical experience to provide communities with essential legal services including stimulating casework, test case initiatives, and community legal education activities. Many law schools offer students clinical education programs that complement their legal curricula. Clinics also offer students the opportunity to explore ethical issues and learn about the social realities of legal institutions outside of law school, which enhances future lawyers鈥� sensitivity to and awareness of problems of inequality, exclusion and discrimination both locally and . The pedagogical methodology of clinical programs proves to be an effective method of bringing social justice into legal curriculum by providing legal services to disadvantaged communities, including Canada鈥檚 still widely underserved .
Some law schools have clinics that focus on technology and innovation allowing students to prepare for practicing in the everchanging technological landscape. The at the Schulich School of Law in Dalhousie works to help technology start-ups in Atlantic Canada seeking early-stage legal information on technology, intellectual property, and business law issues. It also provides students with the opportunity to learn about the practice of start-up law and how to use technology to improve service delivery.
A recent initiative at 捆绑SM社区鈥檚 Faculty of Law resulted in the creation of the first Canadian student-run Business Law Blog at a law school in North America: The 鈥�捆绑SM社区 Business Law Meter鈥� features student-researched and -authored, timely commentaries on newest developments in Canadian and comparative business law, including developments related to Artificial Intelligence, Social Media Platforms and Global Value Chains.
Despite the efforts to create a more practice relevant curriculum, there are still many gaps law schools need to fill. For today鈥檚 and tomorrow鈥檚 lawyers, legal education serves as a that needs to be augmented by skills often not taught in law schools. AI is currently changing how lawyers navigate the ever-changing marketplace and the immediate socio-economic environment. Meanwhile, very rare and elective courses on AI do not serve as adequate training for future jurists who may grapple with AI issues in their practice. Law schools need to start aligning themselves with the marketplace if students are to be equipped to handle the realities of AI鈥檚 presence in the market.
What law schools should be doing to prepare their students for the digital age
Outside of the need for lawyers to have skills to navigate the changing market the and the both note in their model code regarding competence that lawyers should be aware of changing technology in their relevant practice, including the risks associated with it. To meet this requirement law schools should teach and integrate 鈥渁dvanced technologies to prepare their graduates to practice in the artificial intelligence age鈥�. To achieve a curriculum that successfully integrates AI the study of AI and the law needs to be into the normal curriculum at law faculties. Experts note that this can only succeed if those in charge of legal education receive . The interaction between practicing lawyers and legal educators can ensure that the study of AI and the law retains practical relevance.
Professor of Business Law at 捆绑SM社区鈥檚 Faculty of Law in Montreal, Peer Zumbansen, teaches 鈥淩egulating Artificial Intelligence鈥� and regularly invites experts from around the world to illuminate certain aspects of the fast-changing field to his students. In Zumbansen鈥檚 view,
鈥渓awyers will need to enter the workforce well aware of and equipped with a reasonable understanding of AI and its transformative impact not only on economic and financial services but virtually on any area of social and political life today. That requires, however, that we don鈥檛 treat 鈥楢I and law鈥� as an exotic and self-standing element in curriculum design and amendment. To do so would risk making the same mistake that law schools around the world have and continue to make in the context of offering occasional courses on 鈥榣aw and globalization鈥� 鈥� which continue to stand largely isolated from the rest of the law school curriculum. Instead, what is needed is an integration of AI and law/technology issues into a wholesome effort to render legal education today more critical, inclusive and 鈥� above all 鈥� decidedly more responsive to the huge transformations 鈥� economic, demographic, political and cultural 鈥� the world is experiencing.鈥�
Hurdles to integrating AI and the law into law school curricula
Implementing AI throughout the base curriculum at law schools does present significant challenges. One is that few legal scholars have the technical background in computer science to integrate the study of AI and the law into their curriculum meaningfully. This is often the case because most research on AI and the law has been conducted by . To overcome this problem lawyers and legal educators must be enabled to acquire sufficient backgrounds in computer science.
Despite the widely varying degree to which are offered at law schools, there are some schools that provide models on how law schools can start integrating AI into their curricula.
Stanford University developed the (鈥淪AILS鈥�) the goal of which is to 鈥渞aise awareness of the legal issues associated with artificial intelligence and machine learning鈥�. SAILS works to encourage cross-disciplinary collaboration and to be a resource for artificial intelligence and machine learning and the law. Through their Education Resource Modules the SAILS Education Team curated resources on some key areas of the . Some modules include criminal justice and AI, freedom of expression and AI, and AI, liability, and legal personhood. These modules encompass a wide range of issues involving AI and the law and provide the means to develop a critical understanding of the field.
is a global educational institution located in Spain that is primarily a business and law school. In both faculties Esade incorporates AI and technological innovation in their curriculum. For example, the institution offers a . The program gives students the tools to integrate business knowledge with AI and can serve as inspiration to law schools and how they can change their curriculum. Esade鈥檚 works to ensure their students are familiar with marketplace realities. The curriculum includes subjects in economics, accounting and finance while also allowing students to choose specialization tracks from the beginning of their academic career. One specialization track includes 鈥溾�� which involves multiple subject areas on the intersection of law and technology including those on disruptive technologies and artificial intelligence. The Esade model of teaching business and law can serve as inspiration for law schools to consider when thinking about the integration of AI into legal education.
The Harvard Business School (鈥淗BS鈥�) serves as another example of how AI education can be incorporated into legal education. HBS uses the which puts students in the role of a key decision maker to discuss real-life business scenarios. Students are asked to analyse and decide what they would do to address challenges presented in the case study. HBS has included case studies with that allow them to think about emerging issues such as how big data is used by international corporations, long-term policy and ethical considerations related to AI. Already in 2018, HBS Dean Stephen Schwarzman noted the importance of providing students with opportunities to explore how the increase of AI in the marketplace will affect the role of managers. The case studies allow students to understand both the opportunities and disruptive implications of AI in order to prepare them for an AI driven future.
These examples indicate some of the ways in which law schools can start integrating AI and the law into their curricula by providing meaningful ways in which students can engage with issues relating to AI and the law.
What does the future hold for the study of AI in law schools?
Whether or not law schools start adopting an approach to legal education that integrates AI and technology meaningfully into the curriculum depends on relevant stakeholders鈥� willingness to move the profession forward. Long-time observers of Canadian legal education such as 捆绑SM社区鈥檚 former Dean, the late Roderick Macdonald and Thomas McMorrow of the University of Ontario鈥檚 Institute of Technology posited in 2014 that the legal education in Canada has a set that is resistant to change, and that it was up to professors and students to resist stagnancy. In order to remain relevant sites of education law schools would need to start orienting themselves towards educating and critiquing the modern world. Echoing this call, renowned legal historian and legal education thinker Robert Gordon remarked in 2007, the main entry point for changes in the curriculum remained professors鈥� to introducing outside disciplines in their courses. Importantly, professors will also need the ability to integrate these disciplines into traditional teaching models.
Regardless of the barrier to integrating AI into legal education, AI will continue to be a force that legal professionals will encounter in their practice. Now AI represents an opportunity for law schools to be that addresses the realities of an AI-driven world. The question remains whether law schools will seize this opportunity?
Asiyah Siddique, Charlotte Tyhurst, Darena Mu莽a, Laurence Labb茅 contributed research to this article.