Glossary of AI Terms

Artificial Intelligence (AI)
A set of technologies that enable computer systems to analyse information, learn from data, and perform tasks associated with human abilities, such as interpreting information or generating responses.

Generative AI
A type of AI capable of creating new content—such as text, images, video, audio, or code—based on patterns learned during training.

Predictive AI
The use of AI to analyse data, recognise patterns, and carry out classifications or predictions based on previous information.

AI model
An Artificial Intelligence system trained on data to perform specific tasks, such as classifying, translating, summarising, or generating content.

AI language model
An AI model trained on large volumes of text to generate responses in natural language, used in chatbots and conversational assistants.

Generative AI tool
An application or platform that allows users to interact with generative AI models to produce content (e.g., chatbots or image generators).

Prompt (instruction to AI)
Text written by a person to tell an AI tool what task to perform and under what conditions.

Prompting (interaction with AI)
The process of formulating, adjusting, and refining prompts to improve the quality and appropriateness of AI-generated responses.

AI hallucination
A situation in which AI generates false or unverifiable information presented with an appearance of rigour and coherence.

Bias in AI
A tendency for AI to produce partial or discriminatory results as a consequence of the data used for training or the context of use.

Human oversight in the use of AI
The principle that AI-supported outputs and decisions must be reviewed, validated, and ultimately assumed by a responsible person.

Declaration of AI use
The obligation to explicitly state that an AI tool has been used, specifying its role in the development of an academic or professional work.

AI-based Chatbot
Conversational system that uses AI models to interact with users through natural language.

AI as a Support Tool
Principle according to which AI is used to assist academic processes without replacing reflection, decision-making, or human authorship.

AI in Teaching
Use of generative AI to support planning, the creation of teaching materials, and educational activities, under human supervision and with clear pedagogical criteria.

AI in Learning
Use of AI by students to support understanding, organisation, and learning practice, without replacing their own intellectual work.

AI in Research
Use of AI to support literature review, text structuring, or preliminary analysis, with verification, transparency, and ethical oversight.

AI in University Administration
Use of AI to support administrative and service-related tasks, ensuring data protection, human verification, and regulatory compliance.

Verification of AI-Generated Outputs
Process of cross-checking information, data, or claims produced by an AI tool against reliable sources.

Transparency in AI Use
Practice of clearly stating when and how AI has been used in an academic, research, or administrative process.

Academic Authorship and AI Use
Principle establishing that the intellectual responsibility for a piece of work lies with the author, even when AI has been used as support.

Academic Integrity and AI
Set of values guiding the honest use of AI, avoiding concealment of its use or the delegation of intellectual authorship to the tool.

AI-Related Academic Misconduct
Use of AI that violates academic integrity, such as presenting AI-generated content as one’s own without declaring it.

Plagiarism and AI Use
Academic risk arising from the improper use of AI, which can be prevented through transparency, appropriate citation, and respect for authorship.

Privacy and AI Use
Principle whereby personal data or sensitive information should not be entered into AI tools.

Personal Data and AI Use
Identifiable information about individuals that should not be shared with external AI tools without legal safeguards.

Confidential Information and AI Use
Non-public documents or content that should not be entered into external AI tools.

Intellectual Property and AI Use
Rights over works and materials that must be respected when AI tools are used to create or transform content.

Copyright and AI Use
Legal framework governing authors’ rights as applied to AI use, requiring respect for licences, attribution, and limits on reuse.

Open Licences and AI Use (Creative Commons)
Licences that allow content to be reused under certain conditions, facilitating safe AI use in academic contexts.

AI Governance
Set of institutional rules, responsibilities, and mechanisms to guide, supervise, and review AI use at the university.

Traceability of AI Use
Ability to identify which AI tool was used, for what purpose, and at what stage of an academic or administrative process.

AI and Data Protection
Relationship between AI use and personal data protection regulations, requiring particular caution in university environments.

AI and Academic Assessment
Relationship between AI use and assessment processes, which may require specific restrictions to ensure authorship and learning outcomes.

AI and the Digital Divide
Impact of AI use on inequalities in access, competences, and opportunities within the university community.

AI and Sustainability
Consideration of the environmental and energy impact associated with the use and development of AI tools.