Developing a Grounded View of AI

TL;DR

This paper explores the fundamental differences between AI and rule-based systems from an engineering perspective, proposing a methodology to understand AI behavior and ensure responsible use for societal well-being.

Contribution

It introduces a novel methodology to distinguish AI behaviors based on decision types, aiding in understanding AI's limits and supporting human responsibility.

Findings

Proposes a methodology to identify AI decision types.

Highlights the importance of understanding AI behavior for safety.

Supports responsible AI deployment for societal benefit.

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.