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software testing

2,566 papers

#natural language process... Open access Sep 2026

Atypical Failure, Maximal Consequence: Bayesian Character Inference, Threshold Outcome Luck, and Multiplicative Punishment Cascades

This conceptual article develops a formal theory of atypical human failure in which severe life-course consequences can emerge from a conjunction of adverse conditions, a low-frequency behavioural lapse, stochastic outcome mechanics, categorical legal or institutional thresholds, and dynamically propagating collateral...

Kwan Hong TAN · 0 citations
#natural language process... Open access Sep 2026

Atypical Failure, Maximal Consequence: Bayesian Character Inference, Threshold Outcome Luck, and Multiplicative Punishment Cascades

This conceptual article develops a formal theory of atypical human failure in which severe life-course consequences can emerge from a conjunction of adverse conditions, a low-frequency behavioural lapse, stochastic outcome mechanics, categorical legal or institutional thresholds, and dynamically propagating collateral...

Kwan Hong TAN · 0 citations
#machine learning Open access Sep 2026

Reliability Beyond Accuracy in Crop Classification Benchmarks (Supplementary Materials)

Reliability Beyond Accuracy in Crop Classification Benchmarks (Supplementary Materials)Introduction: Near-perfect crop-label accuracy can conceal uncertainty, perturbation sensitivity, and weak explanations. This study evaluates these reliability dimensions without treating benchmark classification as agronomic recomme...

Kwan Hong TAN · 0 citations
#large language models Open access Sep 2026

The Counterfactual Preservation Principle: Evidence Decay and the Limits of AI Delegation

AI delegation can remove the comparison evidence needed to establish whether automation continues to improve outcomes. This paper develops the counterfactual preservation principle: sustained claims of current comparative benefit require a continuing source of identification whose temporal relevance remains defensible....

Kwan Hong TAN · 0 citations
#large language models Open access Sep 2026

The Counterfactual Preservation Principle: Evidence Decay and the Limits of AI Delegation

AI delegation can remove the comparison evidence needed to establish whether automation continues to improve outcomes. This paper develops the counterfactual preservation principle: sustained claims of current comparative benefit require a continuing source of identification whose temporal relevance remains defensible....

Kwan Hong TAN · 0 citations
#large language models Open access Sep 2026

Narrative Hysteresis: The Presumption Gap, Gendered Epistemic Risk, and Reputational Non-Reversibility After Public Accusation

Legal systems can reverse convictions, dismiss charges, and acquit defendants, but public narratives are not designed to reverse with comparable speed or precision. This article develops narrative hysteresis as a theory of reputational path dependence after public accusation. It integrates the continued influence effec...

Kwan Hong TAN · 0 citations
#large language models Open access Sep 2026

Narrative Hysteresis: The Presumption Gap, Gendered Epistemic Risk, and Reputational Non-Reversibility After Public Accusation

Legal systems can reverse convictions, dismiss charges, and acquit defendants, but public narratives are not designed to reverse with comparable speed or precision. This article develops narrative hysteresis as a theory of reputational path dependence after public accusation. It integrates the continued influence effec...

Kwan Hong TAN · 0 citations
#artificial intelligence Open access Sep 2026

Hermeneutic Sovereignty under Generative AI: A Humanities Framework for Protecting Human Meaning-Making from Interpretive Foreclosure

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 · 0 citations
#natural language process... Open access Sep 2026

The Liminal Ontology: A New Framework for Consciousness, Identity, and the So-Called Supernatural

This thesis introduces a novel theoretical framework, the Liminal Ontology, to address the enduring philosophical and scientific challenges posed by consciousness, identity, and anomalous experiences. Moving beyond the traditional dualism of mind and matter and the limitations of materialism, the Liminal Ontology posit...

Kwan Hong TAN · 0 citations
#natural language process... Open access Sep 2026

The Liminal Ontology: A New Framework for Consciousness, Identity, and the So-Called Supernatural

This thesis introduces a novel theoretical framework, the Liminal Ontology, to address the enduring philosophical and scientific challenges posed by consciousness, identity, and anomalous experiences. Moving beyond the traditional dualism of mind and matter and the limitations of materialism, the Liminal Ontology posit...

Kwan Hong TAN · 0 citations
#natural language process... Open access Aug 2026

Is Science Losing Its Objectivity in a Post-COVID World?

The COVID-19 pandemic served as a profound stress test for the global scientific enterprise, conducted under unprecedented public scrutiny and political pressure. This paper argues that the pandemic did not simply erode scientific objectivity but rather accelerated a necessary reckoning with its complex nature. Moving...

Kwan Hong TAN · 0 citations
#natural language process... Open access Aug 2026

Is Science Losing Its Objectivity in a Post-COVID World?

The COVID-19 pandemic served as a profound stress test for the global scientific enterprise, conducted under unprecedented public scrutiny and political pressure. This paper argues that the pandemic did not simply erode scientific objectivity but rather accelerated a necessary reckoning with its complex nature. Moving...

Kwan Hong TAN · 0 citations

From tech blogs

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MIT News · Artificial Intelligence Oct 2, 2026

Documenting the tech worker movement

Writing as a participant and researcher, PhD student JS Tan SM ’22 has co-authored a new book about the rise of tech worker protests and the employer backlash that followed.

GPT-Lab Sep 23, 2026

Requirements Don’t Live in Isolation: What We’re Exploring with Req-Space

Requirements in large systems rarely exist in isolation. Their meaning depends on the wider project context - other requirements, policies, decisions, tests, and implementation details. That becomes especially important when AI is used for review, because spotting a possible conflict or gap is only the beginning. ReqSpace explores how AI, visualisation, and connected project context can help reviewers understand those findings, trace the relationships behind them, and focus on the questions that…

GPT-Lab Sep 17, 2026

Beyond Prompt Engineering: The Role of Tacit Knowledge in Software Engineering

AI is making software generation faster, but speed does not remove the need for expertise. As more work is delegated to AI, tacit knowledge may become one of the most important human advantages in software engineering. The post Beyond Prompt Engineering: The Role of Tacit Knowledge in Software Engineering appeared first on GPT-Lab.

MIT News · Artificial Intelligence Aug 17, 2026

Q&A: Rethinking how innovation happens

In his latest book, Professor Eugene Fitzgerald examines the forces that turn breakthroughs into value — and why innovation resists simple formulas.

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