Developing a Grounded View of AI
This work addresses the need for humans to understand and responsibly use AI for societal well-being, but it appears incremental as it builds on existing discussions without introducing a major breakthrough.
The paper tackles the problem of distinguishing AI behavior from rule-based software by examining its nature and limits from engineering perspectives, proposing a methodology to identify distinctions in AI model decisions with three types of decisions.
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.