Artificial intelligence is usually analysed as a productivity technology, a labour-market shock, or a governance problem. This article argues that its deeper political significance may arise from a fourth channel: ontological displacement. Ontological displacement occurs when a technology weakens the socially recognise...
Kwan Hong TAN· Zenodo (CERN European Organi...· 0 citations
Generative artificial intelligence increasingly mediates not only what institutions decide, but how institutions interpret people. Large language models draft case summaries, student feedback, performance reviews, clinical notes, policy briefs, creative text and administrative explanations. Existing AI governance frame...
Kwan Hong TAN· International Journal of Law...· 0 citations
This paper critically examines the foundational assumptions of rational decision-making models and finds them to be systematically and comprehensively flawed. Through a rigorous analysis of empirical evidence from behavioral economics and neuroscience, we demonstrate that traditional models, such as Expected Utility Th...
Kwan Hong TAN· Zenodo (CERN European Organi...· 0 citations
This paper critically examines the foundational assumptions of rational decision-making models and finds them to be systematically and comprehensively flawed. Through a rigorous analysis of empirical evidence from behavioral economics and neuroscience, we demonstrate that traditional models, such as Expected Utility Th...
Kwan Hong TAN· PhilPapers (PhilPapers Found...· 0 citations
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This thesis investigates the complex and often contentious question of whether predictive models are epistemically superior to causal models. It challenges the simplistic dichotomy that often frames this debate, arguing that the epistemic superiority of a model is not an intrinsic property but is contingent upon the sp...
Kwan Hong TAN· Zenodo (CERN European Organi...· 0 citations
This thesis investigates the complex and often contentious question of whether predictive models are epistemically superior to causal models. It challenges the simplistic dichotomy that often frames this debate, arguing that the epistemic superiority of a model is not an intrinsic property but is contingent upon the sp...
Kwan Hong TAN· Zenodo (CERN European Organi...· 0 citations
This paper develops a novel account of truth grounded in fluctuational epistemology, a framework that situates knowledge within the ontological instability of reality. Traditional theories—correspondence, coherence, pragmatic, and deflationary—assume varying degrees of stability in the relation between propositions and...
Kwan Hong TAN· Zenodo (CERN European Organi...· 0 citations
This paper develops a novel account of truth grounded in fluctuational epistemology, a framework that situates knowledge within the ontological instability of reality. Traditional theories—correspondence, coherence, pragmatic, and deflationary—assume varying degrees of stability in the relation between propositions and...
Kwan Hong TAN· Zenodo (CERN European Organi...· 0 citations
Institutions are beginning to use multiple large language models, AI agents, automated reviewers, and human overseers as if agreement among them were independent corroboration. That assumption can fail. This paper develops the Synthetic Consensus Cascade (SCC) framework, a multidisciplinary mathematical model linking c...
Kwan Hong TAN· Zenodo (CERN European Organi...· 0 citations
Institutions are beginning to use multiple large language models, AI agents, automated reviewers, and human overseers as if agreement among them were independent corroboration. That assumption can fail. This paper develops the Synthetic Consensus Cascade (SCC) framework, a multidisciplinary mathematical model linking c...
Kwan Hong TAN· Zenodo (CERN European Organi...· 0 citations
This paper critically examines the pervasive yet often unsubstantiated notion that we are living in an algorithmically determined world. While popular discourse and some academic literature suggest a monolithic takeover by algorithmic systems, this research argues for a more nuanced and empirically grounded understandi...
Kwan Hong TAN· Zenodo (CERN European Organi...· 0 citations
This paper critically examines the pervasive yet often unsubstantiated notion that we are living in an algorithmically determined world. While popular discourse and some academic literature suggest a monolithic takeover by algorithmic systems, this research argues for a more nuanced and empirically grounded understandi...
Kwan Hong TAN· PhilPapers (PhilPapers Found...· 0 citations
Students in MIT’s Concourse program delve deeply into the human condition, debate challenging questions, and learn to develop judgment about issues that can’t be quantified.
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduSep 30, 2026
Able to defeat top-ranked human players and more efficient than other models, the new system could help decision-makers in military maneuvers or business negotiations.
Computer scientist, entrepreneur, and philanthropist will collaborate with the MIT Schwarzman College of Computing to advance AI and scientific discovery.
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