± SCIENCE Today’s artificial intelligence still faces two major challenges. One is that, in most industries, data exist…+ SCIENCE Deep learning takes on protein folding In 1972, Anfinsen won a Nobel prize for demonstrating a connection bet…± SCIENCE Significance Deep neural networks are currently the most successful machine-learning technique for solving a…+ SCIENCE Deep learning allows computational models that are composed of multiple processing layers to learn representa…+ HEALTH For the task of analyzing survival data to derive risk factors associated with mortality, physicians, researc…+ SCIENCE Artificial intelligence (AI) coupled with promising machine learning (ML) techniques well known from computer…+ SCIENCE Deep learning is revolutionizing many areas of science and technology, especially image, text, and speech rec…+ SCIENCE Current deep-learning models are mostly built upon neural networks, i.e. multiple layers of parameterized dif…
TruaceTracing the truth around AIMonday, July 13, 2026
Subscribe
TRV-2026-0190Certified recordPeer-reviewed

Manipulation and Deception in Generative AI-Mediated Education: Preserving Epistemic Agency, Critical Thinking, and Creativity

Abstract Generative AI now mediates core parts of learning, yet we lack criteria to tell its legitimate pedagogical uses from manipulative and deceptive ones. We also know too little about how AI reshapes the growth of critical thinking and creativity, or about whether it accelerates drift from educational goods to evaluative metrics. Using a postdigital, pragmatist lens that treats classrooms as sociomaterial assemblages of people, platforms, and institutions, we propose three orienting principles: moral legiti…

Education · P Space — documented harm · certified 2026-07-13 · v1 · article view · machine-readable

Current reading — problem

Generative AI now mediating core parts of learning risks crossing into manipulation and deception and accelerating drift from educational goods to metrics, reshaping development of critical thinking and creativity.

What this doesn’t fix

The work acknowledges foundational gaps in criteria and evidence for distinguishing legitimate from manipulative AI uses and for understanding effects on thinking and creativity.

Evidence

Reader signal

How should this claim be treated?

Cite this record

Truvace Impact Record TRV-2026-0190, v1: “Manipulation and Deception in Generative AI-Mediated Education: Preserving Epistemic Agency, Critical Thinking, and Creativity.” Truvace, 2026-07-13. /record/TRV-2026-0190 (accessed at citation time). sha256 a0e94d07a15c4ef5…

Calibration history

Every change to this record since certification, in the open. None yet — the reading has held since it entered the record.

  1. Certifiedv1a0e94d07a15c…

    Certified into the record

Verify this record
How to verify without trusting this page

Fetch the canonical text of any version from /api/record/TRV-2026-0190 and hash it yourself — for example shasum -a 256 on the saved canonical field. The result must equal content_hash, and each version’s text ends with prev:followed by the prior version’s hash (version 1 chains to 64 zeros). If a single character of any version had been altered since certification, the chain would not reproduce.