AI Accuracy Is Not the Problem. Decision Risk Is.

Description and use

<p><em>Why production AI systems need more than accurate models, and how to build automation that remains reliable when predictions are wrong.</em></p> <p>There has been a lot of discussion about comparing <a href="https://docs.typesafe.ai/" rel="noopener noreferrer">Jev</a> with traditional large language models (LLMs). Most comparisons focus on which model gives more accurate answers.</p> <p>That is a useful test. But I think we're paying too much attention to the model and not enough to the system we're building around it.</p> <p>Jev is interesting because it is designed for structured deci

Problem

<p><em>Why production AI systems need more than accurate models, and how to build automation that remains reliable when predictions are wrong.</em></p> <p>There has been a lot of discussion about comparing <a href="https://docs.typesafe.ai/" rel="noopener noreferrer">Jev</a> with traditional large language models (LLMs). Most comparisons focus on which model gives more accurate answers.</p> <p>That is a useful test. But I think we're paying too much attention to the model and not enough to the system we're building around it.</p> <p>Jev is interesting because it is designed for structured deci

Outcome

<p><em>Why production AI systems need more than accurate models, and how to build automation that remains reliable when predictions are wrong.</em></p> <p>There has been a lot of discussion about comparing <a href="https://docs.typesafe.ai/" rel="noopener noreferrer">Jev</a> with traditional large language models (LLMs). Most comparisons focus on which model gives more accurate answers.</p> <p>That is a useful test. But I think we're paying too much attention to the model and not enough to the system we're building around it.</p> <p>Jev is interesting because it is designed for structured deci

Evidence

AI Accuracy Is Not the Problem. Decision Risk Is.

Source