Developing a Grounded View of AI

TL;DR

Problem: AI differs from rule-based software, challenging traditional engineering and epistemology. Approach: formulate AI as three perspectives—AI as scientific discovery, as a technical artifact of engineering, and as a human-made phenomenon—and introduce a unified epistemic framework (the Φ-Я triplet) with the three decision modes. Contributions: articulate the Я-Relation vs Φ-Relation, define Я-thinking and Φ-thinking, and provide practical tools to assess AI behavior, including a model of outputs via $y = f(x, \\xi)$ and the distribution $p(y|x)$. Significance: enables more robust, human-centered governance of AI, supporting safer deployment for individuals, society, and environment.

Abstract

As a capability coming from computation, how does AI differ fundamentally from the capabilities delivered by rule-based software program? The paper examines the behavior of artificial intelligence (AI) from engineering points of view to clarify its nature and limits. The paper argues that the rationality underlying humanity's impulse to pursue, articulate, and adhere to rules deserves to be valued and preserved. Identifying where rule-based practical rationality ends is the beginning of making it aware until action. Although the rules of AI behaviors are still hidden or only weakly observable, the paper has proposed a methodology to make a sense of discrimination possible and practical to identify the distinctions of the behavior of AI models with three types of decisions. It is a prerequisite for human responsibilities with alternative possibilities, considering how and when to use AI. It would be a solid start for people to ensure AI system soundness for the well-being of humans, society, and the environment.