🤖 AI Summary
This study addresses the limitations of conventional AI alignment approaches, which often reduce organizational decision-making to a single objective while overlooking pluralistic values and procedural heterogeneity. The authors propose the concept of “process alignment,” which evaluates whether large language models weight information in ways consistent with an organization’s decision-making strategies, rather than focusing solely on output accuracy. Empirical analyses in two domains—European Court of Human Rights (ECHR) rulings and German credit decisions—reveal that process alignment strongly correlates with output accuracy in the ECHR context (r = 0.85) but not in credit decisions (r = 0.15), where external interventions also yield inconsistent effects, exposing underlying historical biases. The findings underscore the necessity of incorporating multi-perspective, process-level considerations into alignment evaluation and caution that high process alignment is both difficult to achieve and not universally desirable.
📝 Abstract
Aligning AI systems with organizational decision-making is typically framed as a single-target problem: make the model behave like the organization. We argue this framing obscures a deeper pluralistic challenge. We rely on a decision-policy capturing method to measure process alignment: whether an LLM weights information as the organization does, not merely whether it reaches the same conclusions. Applying this method to ECHR Article 6 decisions, process alignment strongly predicts output accuracy (r = 0.85, p < .001) and externalization substantially improves alignment for poorly-aligned models. Applying it to German consumer credit decisions, this relationship collapses (r = 0.15, p = .60): interventions produce inconsistent effects and the benchmark encodes potentially discriminatory historical patterns. This contrast is itself a pluralistic alignment finding: in contested domains, high process alignment is neither achievable via externalization nor unconditionally desirable. Output agreement alone cannot distinguish a model that has internalized an organizational policy from one that merely approximates its outcomes; process-level measurement is a necessary component of any pluralistic alignment evaluation.