About
Ramin Saadat is an independent researcher and the founder of the BIIS RESEARCH LIMITED. British Institute for Ignorance Studies® (BIIS). His primary research focus is Ignorance studies, specializing in the diverse aspects and cultural production of ignorance in the 21st century.
Over two decades, Saadat has developed the 'Evolutionary Pragmatist Approach' (EPA), a methodological framework that examines the biological constraints of human evolution alongside the pragmatic utility of knowledge. His interdisciplinary work investigates the neurophysiology of 'memetic dominance', the restoration of Common Sense in the age of Artificial Intelligence , and the psychological phenomenon of 'Perpetual Childhood'.
As a leading researcher in ignorance studies, Saadat is the author of several published books, including, in addition to extensive research on 'Mental Viruses' and 'Cognitive Immunity'. His work bridges Eastern philosophical traditions with Western analytical science to safeguard human agency against systemic misinformation.
Employment
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BIIS Research Limited Founder and Lead Researcher2026 - Present
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (85)
- Beyond Truth: From Epistemic Situatedness to Scientific Ethics as Method Save
- Ignorance as a Stable Equilibrium: An Evolutionary Framework (Systemic Misalignment as a Co-Evolutionary Outcome of Biological, Cognitive, and Cultural Processes) Save
- Hijacking Without Neurons: Three Pathways of Reprogramming in Plants and the Paradox of Adaptive Vulnerability Save
- From Agnoia to Amathia: Towards Sophisticated Ignorance Save
- Flee the Tribe Save
- Existence: The Splendour of A-Normativity Save
- Crisis of Persuasion: Why Does Our View Never Change Save
- Crisis Management or Management Crisis? Britain in a Deadlock of Hesitation and Choice Save
- Context, Perspective, or Argument? Perhaps None! (Introducing the Concept of "Teleotexture" in Hermeneutic Realism) Save
- Cognitive Effort in Large Language Models: A New Mirror for Seeing Human Reasoning Save