Reimagining Truth and Trust

Abstract

In AI-mediated information environments, truth is no longer simply uncovered through journalistic verification. It is produced through data, algorithms, platform logics, and collective participation. This book argues that AI-based fact-checking does not merely accelerate verification but transforms the epistemic conditions under which truth is constructed, evaluated, and trusted. Across technical, cognitive, philosophical, and social dimensions, the chapters show how detection models, probabilistic inference, human bias, explainability, and participatory verification jointly reshape contemporary truth production. Rather than treating misinformation as a problem solvable through more accurate algorithms alone, the book advances the concept of epistemic sustainability. This framework emphasizes transparency, interpretability, inclusivity, and civic participation as conditions for maintaining legitimate and trusted knowledge over time. AI can calculate claims at scale, but the fairness, accountability, and social justification of those calculations remain institutional and human responsibilities. The central argument is that the future of fact-checking depends not on replacing human judgment with automation, but on building epistemic infrastructures that enable humans and AI to co-produce truth in democratically accountable ways.