Digital Epistemology: Evaluating The Credibility Of Knowledge Generated By Ai

Abstract

The rise of Artificial Intelligence (AI) as a key player in knowledge production has transformed traditional epistemological frameworks, necessitating a critical evaluation of its credibility and trustworthiness. This paper investigates the emerging domain of digital epistemology, focusing on how AI challenges established notions of validity, reliability, and trust in knowledge generation. By examining philosophical perspectives and interdisciplinary insights, we identify three primary challenges to AI-generated knowledge: algorithmic biases, the dependence on flawed or incomplete datasets, and the opacity of decision-making processes. These challenges raise significant concerns about the ethical and epistemological implications of relying on AI in contexts such as healthcare, law, and policy-making. Furthermore, this study explores the mechanisms required to evaluate the credibility of AI systems, emphasizing the importance of transparency, explainability, and accountability in fostering trust. We argue that the epistemological relationship between AI and its human users hinges on balancing technological capabilities with ethical considerations, ensuring that AI serves as a tool to complement rather than undermine human autonomy. The findings underscore the need for a robust digital epistemology that adapts classical principles of knowledge to the complexities of the digital era. This framework can guide the development of AI systems that prioritize ethical decision-making and credible knowledge outputs, addressing both theoretical and practical concerns. By bridging philosophy and technology, this paper offers critical insights into the evolving role of AI in shaping how knowledge is produced, validated, and trusted in the digital age.