Ethics in Artificial Intelligence and Alternative Dispute Resolution: Generating AI/Human Reviewed Ethical Guidelines for ADR Practitioners and the Legal Profession

Abstract

This paper reviews current artificial intelligence guidelines, laws, rules, and standing orders imposed or provided by judges, attorneys, bar associations, and alternative dispute resolution institutions from both the United States and Canada.  Additionally, several key cases reviewing the use of generative AI in court filings are included and demonstrate the ethical and legal issues attorneys have already committed before a court.  After reviewing these rules and guidelines for mentions of alternative dispute resolution AI guidance, it is expanded upon by reviewing and generating, with the help of a fine-tuned Llama 3.1 model, a set of useful and detailed AI guidelines for alternative dispute resolution (ADR) practice.  To better explain AI and litigation analytics, there are sections covering the history of ADR and artificial intelligence from an ethical perspective, a brief section on AI based assistants for ADR practitioners, and a small section on the future of AI in dispute resolution.

Keywords: artificial intelligence, ethics, online dispute resolution, keywords, fine-tuning, litigation analytics, arbitral analytics, sentiment analysis, Benford’s law, machine learning, arbitration, alternative dispute resolution, U.S. Federal Courts, Canadian Courts, ADR, LEGAL-BERT, neural networks, deep learning, Llama, Ethics.Law-Llama, Word Count, Hugging Face, rules of professional conduct, legal ethics, standing orders, law society ethical rules, ADR institution, AI ethics, guardrails, (AI)rbitrators, Medi(AI)tors, Facilit(AI)tors, arbitrator, mediator, facilitator, generative artificial intelligence, GAI

JEL Classification: K10, K12, K19, K20, K23, K29, K30, K33, K39, K40, K41, K49