AI Placebo Differential – Measuring What AI Apps Add Beyond ChatGPT (github.com)

A new evaluation framework called the AI Placebo Differential has been introduced to measure the unique value added by AI applications compared to base models like ChatGPT. This structured method addresses a common question from users and investors: "Can't ChatGPT do this?" By quantifying differences across five key metrics—accuracy, usability, reliability, agentic chain quality, and token efficiency—the framework helps identify how well-designed applications provide enhanced outputs that exceed what plain models can achieve. This model is significant for the AI/ML community as it highlights the importance of context, user experience, and operational efficiency in AI applications. The framework reveals that while ChatGPT can theoretically perform many tasks, an effective application automates complex processes, integrates domain-specific knowledge, and offers refined user experiences that raw models cannot match without extensive manual input from users. For instance, legal AI applications integrating case law deliver far more accurate advice than ChatGPT, underlining the need for tailored AI solutions that operate seamlessly while offering measurable advantages in task execution, making it not just a better tool but often the only viable solution at scale.