Over What Range Should Reliabilists Measure Reliability?

Area of Science:

• Epistemology
• Philosophy of Mind
• Artificial Intelligence Ethics

Background:

• Process reliabilism posits that justified beliefs arise from reliable belief-forming processes.
• A key challenge, the generality problem, questions the appropriate range over which to assess process reliability.
• The increasing use of AI systems in belief formation necessitates a re-evaluation of these epistemological frameworks.

Purpose of the Study:

• To challenge the assumption that reliability must be calculated across all possible token processes.
• To propose a novel solution to the generality problem, particularly concerning AI-driven belief acquisition.
• To refine the criteria for evaluating the reliability of belief-forming processes in complex scenarios.

Main Methods:

• Analysis of existing solutions to the generality problem in process reliabilism.
• Case study examination of belief formation using AI system outputs.
• Development of a restricted range evaluation for process reliability.

Main Results:

• Existing generality problem solutions are insufficient for AI-assisted belief formation.
• Reliability assessment should not encompass all conceivable inputs, especially for AI systems.
• A restricted range, based on belief content and input similarity, offers a viable solution.

Conclusions:

• The scope of reliability assessment in process reliabilism needs to be context-dependent.
• Evaluating reliability over a restricted range, guided by content and input similarity, resolves issues with AI systems.
• This refined approach better accounts for justified belief formation in technologically advanced environments.