Algorithmic Adjudication and Constitutional AI—The Promise of A Better AI Decision Making Future?

Authors

April G. Dawson, North Carolina Central UniversityFollow

ORCID (Links to author’s additional scholarship at ORCID.org)

https://orcid.org/0009-0001-3180-3418

Abstract

Algorithmic governance is when algorithms, often in the form of AI, make decisions, predict outcomes, and manage resources in various aspects of governance. This approach can be applied in areas like public administration, legal systems, policy-making, and urban planning. Algorithmic adjudication involves using AI to assist in or decide legal disputes. This often includes the analysis of legal documents, case precedents, and relevant laws to provide recommendations or even final decisions. The AI models typically used in these emerging decision-making systems use traditionally trained AI systems on large data sets so the system can render a decision or prediction based on past practices. However, the decisions often perpetuate existing biases and can be difficult to explain. Algorithmic decision-making models using a constitutional AI framework (like Anthropic's LLM Claude) may produce results that are more explainable and aligned with societal values. The constitutional AI framework integrates core legal and ethical standards directly into the algorithm’s design and operation, ensuring decisions are made with considerations for fairness, equality, and justice. This article will discuss society’s movement toward algorithmic governance and adjudication, the challenges associated with using traditionally trained AI in these decision-making models, and the potential for better outcomes with constitutional AI models.

Recommended Citation

April G. Dawson, Algorithmic Adjudication and Constitutional AI—The Promise of A Better AI Decision Making Future?, 27 SMU Sci. & Tech. L. Rev. 11 (2024)