Former Michigan Chief Justice Bridget McCormack argues that the legal system's probabilistic nature, driven by human fallibility, is a core inefficiency. Greater predictability would reduce disputes by allowing businesses and individuals to plan around clear, consistently enforced rules.
The AAA strategically launched its AI arbitrator for construction disputes. This industry already uses AI, values speed over confidentiality, and provided a rich library of 'documents-only' cases to train the system in a constrained, low-risk environment before expanding.
An AI arbitration system can repeatedly summarize its understanding of claims and evidence, asking parties for corrections. This process ensures parties feel heard and understood—a key element of procedural fairness that time-constrained human judges often cannot provide.
A significant portion of B2B contracts will soon be negotiated and executed by autonomous AI agents. This shift will create an entirely new class of disputes when agents err, necessitating automated, potentially on-chain, systems to resolve conflicts efficiently without human intervention.
As former Chief Justice, Bridget McCormack had to lobby legislators for funding for improvements like online dispute resolution. Unlike a business, public courts can't use revenue from good performance for R&D, creating a structural barrier to modernizing the justice system.
Former Chief Justice McCormack argues the legal system is a public good most citizens can't access, comparing it to needing a special guide to use a public highway. With 92% of Americans unable to afford legal help, the system is fundamentally failing the majority it's meant to serve.
While AI can inherit biases from training data, those datasets can be audited, benchmarked, and corrected. In contrast, uncovering and remedying the complex cognitive biases of a human judge is far more difficult and less systematic, making algorithmic fairness a potentially more solvable problem.
Citing high rates of appellate court reversals and a 3-5% error rate in criminal convictions revealed by DNA, former Chief Justice McCormack argues the human-led justice system is not as reliable as perceived. This fallibility creates a clear opening for AI to improve accuracy and consistency.
A primary use case emerging for the AI Arbitrator is as an 'early case evaluation' tool. Parties can upload evidence and arguments to get an objective assessment of their position's strength. This helps them decide whether to proceed, settle, or drop the case, saving significant time and legal fees.
Unlike a human judge, whose mental process is hidden, an AI dispute resolution system can be designed to provide a full audit trail. It can be required to 'show its work,' explaining its step-by-step reasoning, potentially offering more accountability than the current system allows.
When discussing AI risks like hallucinations, former Chief Justice McCormack argues the proper comparison isn't a perfect system, but the existing human one. Humans get tired, biased, and make mistakes. The question isn't whether AI is flawless, but whether it's an improvement over the error-prone reality.