After the Human: Artificial Intelligence, Subjectivity, and the Future of Knowledge

Name: After the Human: Artificial Intelligence, Subjectivity, and the Future of Knowledge
Brand: Aletheia Editions
SKU: 9781067624101
Price: 2800.0 INR
Availability: InStock

by Martin Neilan

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ISBN13: 9781067624101
Binding: Hardcover
Subject: N/A
Publisher: Aletheia Editions
Publisher Imprint: Aletheia Editions
Publication Date: April 25, 2026
Pages: 280
Original Price: GBP 29.99
Language: English
Edition: N/A
Item Weight: 663 grams
BISAC Subject(s): Artificial Intelligence / General

About The Author

Neilan, Martin: - Martin Neilan brings a distinctive perspective to critical AI studies, grounded in architectural theory, a discipline that treats buildings and cities as material sites where power and subjectivity are shaped. Trained to think across concepts, materials, abstract systems, and lived experience, he applies this interdisciplinary lens to examine how AI infrastructures are reshaping human subjectivity.Neilan holds three first-class degrees, including a Master of Arts in Histories and Theories (with Distinction) from the AA in London, where his research explored transparency, governmentality, and modern subjectivity in Modernist architecture. As an undergraduate, he was his university's record prize winner, served as valedictorian, and received the Hackett Scholarship for Overseas Study, the institution's most prestigious award. A recipient of multiple national and international awards as a practitioner, he now works as an independent scholar, bringing together continental philosophy and technical analysis while making complex ideas accessible to a wider audience.After the Human draws on Michel Foucault's archaeology of knowledge and genealogy of power to examine how contemporary AI systems are transforming the conditions of human subjectivity. It is part of a broader research initiative tracing the historical emergence of optimisation as a cultural logic, from medieval religious practices, through Enlightenment rationality, to modern self-improvement regimes. The book argues that machine-learning systems are not only intensifying these trajectories but inaugurating a qualitative shift in how subjectivity itself is structured.

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