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TRUVACE RECORD VERSION
record: TRV-2026-2145
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-10-22T01:10:41.591654Z
status: published
lens: p_space
sector: education
headline: Los riesgos de la IA dialógica en la educación superior: afectaciones cognitivas y en la capacidad de lecto-escritura
dek: Dialogic Artificial Intelligence (DAI) or communicative AI within Large Language Models (LLMs) is rapidly expanding across higher education and academic workflows in both teaching and research. The adoption of DAI is being driven by the pressure to enhance productivity and automate academic practices. This paper discusses the primary risks that the intensive use of DAI poses to human cognitive capacities, information biases, and the erosion of literacy, critical thinking, argumentation, and academic discourse sk…
gain_title: (none)
problem_title: Heavy use of conversational AI in university teaching and research may weaken students' and scholars' cognition, reading and writing, argumentation skills, and blur authorship and plagiarism boundaries.
trace_subject: (none)
gain_reading: (none)
gain_evidence: (none)
problem_reading: Heavy use of conversational AI in university teaching and research may weaken students' and scholars' cognition, reading and writing, argumentation skills, and blur authorship and plagiarism boundaries.
problem_evidence: the erosion of literacy, critical thinking, argumentation, and academic discourse skills | emerging forms of plagiarism and misconduct facilitated by DAI
quick_read: A peer-reviewed paper examines how dialogic AI, meaning large language model chatbots, is spreading through higher education teaching, research and academic workflows. It identifies risks to human cognitive capacities, to information quality through biases, and to literacy and academic discourse skills.

The paper matters because universities are adopting these tools under productivity pressure while the concerns reach the core of learning and scholarship. It warns the effects could be irreversible, though the supplied text gives no empirical measurements, so the scale and permanence of the harms remain a matter of argument rather than demonstrated outcomes.
limitation: The source frames the transformation as something DAI 'could' cause, so the cognitive and literacy harms are possibilities discussed conceptually rather than measured outcomes.
tag: Evidence-backed problem
key_points: Dialogic AI is expanding quickly across teaching and research in higher education. | Adoption is driven by pressure to raise productivity and automate academic practices. | Identified risks include cognitive effects, information biases, and weakened critical thinking and argumentation. | New forms of plagiarism and misconduct are enabled, and individual authorship is described as giving way to human-AI co-authorship. | The paper offers criteria for university policy that go beyond bans and punishment.
rundown: The paper treats conversational AI as an immersive technology that affects human agency and autonomy. It argues that the technology could transform cognition, literacy, the sense of authorship and collaborative frameworks in research and teaching.

On integrity, it analyzes emerging plagiarism and misconduct facilitated by these tools. It reflects on how the notion of individual authorship has become obsolete and is being replaced by human-AI co-authorship.

It closes with criteria and recommendations for university regulation. These explicitly move beyond prohibitions, punitive measures, or ineffective appeals to individual ethics in the use of LLMs.
sources:
- peer_reviewed | SCIO: Revista de Filosofía | https://doi.org/10.46583/scio_2026.30.1260 | 2026-10-20
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