
pmid: 38403050
Litigation is a creature of disagreement. Our essay explores the potential of artificial intelligence (AI) to help reduce legal disagreements. In any litigation, parties disagree over the facts, the law, or how the law applies to the facts. The source of the parties' disagreements matters. It may determine the extent to which AI can help resolve their disputes. AI is helpful in clarifying the parties’ misunderstanding over how well-defined questions of law apply to their facts. But AI may be less helpful when parties disagree on questions of fact where the prevailing facts dictate the legal outcome. The private nature of information underlying these factual disagreements typically fall outside the strengths of AI's computational leverage over publicly available data. A further complication: parties may disagree about which rule should govern the dispute, which can arise irrespective of whether they agree or disagree over questions of facts. Accordingly, while AI can provide clarity over legal precedent, it often may be insufficient to provide clarity over legal disputes. This article is part of the theme issue 'A complexity science approach to law and governance'.
Artificial Intelligence, Dissent and Disputes
Artificial Intelligence, Dissent and Disputes
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 3 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
