In 2026 UNESCO published “AI answers. You decide: A companion guide to the UNESCO media and information literacy curriculum”, a guide written by Anne Leppäjärvi, a Finnish educator in journalism and media and information literacy, and coordinated by Adeline Hulin and Olivier Van Bockstael of the organisation’s staff. The guide itself warns that the ideas expressed are those of its authors and do not necessarily commit UNESCO. It is in English and open access, under a CC-BY-SA 3.0 IGO licence.

It is aimed at teachers, not students, and requires no technical knowledge. It complements the curriculum “Media and Information Literate Citizens: Think Critically, Click Wisely!” (second edition, 2021) and UNESCO’s AI competency framework for teachers, whose media and information dimension, the guide says, it addresses. The activities are designed mainly for young people aged 13 to 15, with suggestions for adapting them to younger or older ages. Each section can be taught as a stand-alone lesson, so there is no need to follow the guide from start to finish.

Its guiding thread is the “Orientation Map”, with three layers: the individual, the AI systems, and the people and institutions that build, fund and regulate them. Alongside it, it proposes five questions that recur in every unit: who made it, what evidence supports it, what system shaped it, who benefits from you believing or sharing it, and what should I verify before acting. The first unit distinguishes four things AI does (predict, classify, make decisions about a person and generate content) and deals with the data people give up when using a free service. The second presents AI as both a producer and a curator of content, and proposes comparing four types of source according to their degree of editorial responsibility.

The third unit is the closest to everyday use of chatbots. It explains that a language model predicts plausible text from patterns, that fluency is not the same as accuracy, and that a synthesised answer can hide the sources and disagreements that a search engine does show. It offers the chain “trust, verify or question” depending on what is at stake, three self-check questions (“am I learning or just getting a result?”) and a four-step research loop. Its working rule is to treat an AI answer as a lead, not a source: the guide says, verbatim, “treat an AI-generated answer as a lead rather than a source”. It also devotes a section to those who seek companionship from a chatbot and, in that case, recommends a private, supportive conversation.

Units four and five turn to power, rights and the future. They address inequality that goes beyond access (language, computing power, knowledge represented in the data, cost), the accountability of algorithms, the energy cost of AI with figures from UNESCO research from 2025 that, according to the guide itself, will change, and three development scenarios: a few companies decide, public AI, and many small developers. Mariya Gabriel’s foreword sums up the approach in one sentence: “AI should not simply happen to us”. One of its arguments is that not using AI is a legitimate decision, as long as it does not mean giving up on understanding it.

It has limits worth knowing about. It is a long text, in English, written from an international perspective, and the examples and legal frameworks it cites do not always match the Spanish context. Several activities ask students to use an AI tool, and the guide reminds readers to check the school’s policy and each service’s minimum age beforehand; it cites UNESCO’s 2023 recommendation to set 13 as the age for independent use. The Diario has already looked at the question of age in a report for UNESCO on the appropriate age. The guide also notes that most of the activities can be done with the teacher operating the tool on a shared screen.

For a teacher, the most useful approach is to start with the “Discussion Guide” and “Try This” sections of the unit that best fits their subject. Activities such as “Sort My Day” (classifying the day’s uses of AI) or “Ask the Three Questions” (applying three questions to a chatbot’s answer and checking one of its sources) fit into a single session.

The Office for Students (OfS) is the regulator of higher education in England; Advance HE is a membership organisation that supports the improvement of university teaching in more than 30 countries. On 11 November 2026 they jointly published Artificial intelligence in higher education, which has two parts: a research report, Making AI work for students, and a web guide to effective institutional practice. They are aimed mainly at English universities and colleges. The paper has already covered the announcement and the discussion it prompted; this article focuses on what the documents say.

The report is based on a consultation carried out between June and September 2026: 16 events, 64 responses to open questions and 22 interviews, with input from 244 staff members and 91 students at no fewer than 127 institutions. Its authors warn that participants signed up voluntarily and so may not represent the whole population, and that the conclusions are those of the OfS and Advance HE, not regulatory requirements.

Citing surveys by the Higher Education Policy Institute (HEPI), the report notes that 94% of students said in late 2025 that they had used generative AI in assessed work, up from 53% in late 2023. It records valuable uses, especially for students with disabilities or whose first language is not English, and one central risk: offloading reading, problem-solving or writing onto AI can bypass the productive struggle needed to learn.

The assessment chapter is the most forceful. It describes how many unsupervised tasks can be completed to a good grade with little involvement from the student, and how the traffic-light systems (red, amber, green) that many institutions use to classify permitted uses are hard to enforce unless the design of assessments changes. On detectors, it concludes that their output should be, at most, one piece of evidence among others; the guide asks that misconduct proceedings rely on a balanced set of evidence, without “placing disproportionate weight on the outputs of AI detection tools”. It defends secure assessments (in-person exams, presentations, oral exams, practical tasks) while acknowledging that they may be less authentic. It adds: “If it becomes possible to complete an assessment using AI without the knowledge and skills being tested, the assessment should be replaced.” As an example, the University of Bath moved in September 2026 to two “lanes”: a closed one, with no access to AI, and an open one, designed on the assumption that it will be used.

On literacy and strategy, the report finds that students' training is uneven, that staff training is often optional with low take-up, and that at many institutions approaches grow out of the initiative of individual teachers. The University of Kent, as a case study, offers a ChatGPT Edu platform with compulsory prior training in literacy, responsible use and data protection, although using it is optional.

The guide is the regulatory part. It gives examples of practices likely to meet conditions B1 (academic experience), B2 (support) and B4 (assessment): reviewing the quality of materials and feedback produced with AI, telling students clearly which uses are permitted, and mitigating differences in access. It makes clear that it will not introduce new rules. In the future quality system it proposes, it expects institutions to show that their assessments stand up to AI, with a possible impact on their rating if there are doubts.

Among the documents in the library, it is related to the MIT committee report, which also calls for redesigning assessment; here the source is a regulator and the focus is regulatory compliance. Limits: it is a qualitative, self-selected study centred on England. For a teacher at any level, the most useful parts are chapter 2, with its redesign options, and paragraphs 53 to 55 on usage policies. To get started, the web guide is enough, and it can be read in a few minutes.