Artificial intelligence is changing how knowledge is produced, shared and validated, and its effects depend on the social, cultural and educational conditions in which it is used. Three recent initiatives — in the Middle East and North Africa, in anthropological research and at a Spanish university — offer complementary ways of examining that relationship.
MIL4Peace and media literacy for peace in the Arab world
On 28 October, DW Akademie, the media development organisation of Germany’s international broadcaster Deutsche Welle, presented MIL4Peace at an online regional event. The Arabic-language digital learning platform offers free resources on media and information literacy, critical thinking, disinformation, hate speech, artificial intelligence and peacebuilding. It is intended for teachers, media professionals, civil society organisations and young leaders across the Middle East and North Africa.
The launch features among the activities of UNESCO’s Global Media and Information Literacy Week, held from 24 to 31 October under the theme We All Play a Part. The platform is being developed as part of the EU-funded MIL4Peace project, which strengthens the capacity of civil society in Lebanon, Libya and Tunisia, particularly youth-led organisations, to engage young people in conflict prevention and peacebuilding.
In contexts marked by conflict, inequality and political tensions, the circulation of information shapes trust between communities, opportunities for public participation and the ability to recognise narratives that fuel hostility. Fact-checking is only one part of the challenge.
Creating the resources in Arabic is also a significant cultural choice. Inclusive media literacy must begin with the languages, experiences and communication practices of the people it seeks to reach.
From an anthropological perspective, MIL4Peace raises questions about how trust in information is built in different social settings and, given that this is an initiative driven from Europe, how much scope local communities and organisations have to shape their own educational tools.
Sources: UNESCO, Global MIL Week 2026 – Celebrations around the World, EU Medbridge, MIL4Peace project and MIL4Peace platform.
Digital, computational and AI anthropology according to Matt Artz
On 19 October, Practicing Anthropology, a journal of the Society for Applied Anthropology, published Matt Artz’s article ‘From Digital to Computational to AI Anthropology’ online. Artz, an anthropologist at Azimuth Labs, distinguishes AI anthropology from its two closest neighbouring fields.
Artz defines each field by the relationship between the researcher and the machine. Digital anthropology treats digital technology as an object of study, a fieldwork tool and a medium of contemporary life. Computational anthropology uses it to engage with cultural materials on a scale beyond the reach of conventional fieldwork. AI anthropology, he argues, approaches the system as an interlocutor: a collaborator that the researcher guides through natural language in real time, with the researcher and the system mutually shaping one another over the course of their exchange.
To support this distinction, Artz draws on Andrew Pickering’s ‘dance of agency’, Donna Haraway’s becoming-with and cybernetic feedback. The difference between the three fields would lie in a change of relationship: a shift from acting upon technology to acting with it. The fields overlap, and AI anthropology would bring them together in a single practice organised around an anthropology of, by and for AI.
The proposal is thought-provoking, but it also raises questions that warrant critical discussion. In what sense can an AI system be considered an interlocutor? What distinguishes linguistic interaction, methodological collaboration and an ethnographic relationship? What place do lived experience, responsibility and social relations occupy in research mediated by generative models?
Artz locates the transformation in the recursive relationship between researcher and system, without making it dependent on the machine’s intelligence or inner life. His proposal leaves a fundamental question open: to what extent can that interaction be equated with an ethnographic relationship shaped by lived experience, responsibilities and specific social conditions? That open question is also what makes the proposal productive. It invites us to examine these distinctions and ask whether generative systems transform the discipline’s epistemological foundations or extend methods that already existed.
For AIthropology Lab, this debate is particularly significant. AI anthropology needs to study technologies and their social consequences, but also the conditions under which these tools enter into our own practices of knowledge production.
Sources: Artz, M. (2026). From Digital to Computational to AI Anthropology. Practicing Anthropology and full text on the author’s website.
Bias, ethics and generative AI at a UNED conference
The National University of Distance Education (UNED) concludes the First International Conference of the ICE/UA-6194 Network in Madrid today. Entitled Critical Thinking and Ethics: Generative Artificial Intelligence in 21st-Century Language Learning. Humanism and Education vs Technology, the event began on 28 October. It is jointly directed by UNED, the University of Alicante and the University of the West Indies, and its programme covers language teaching, literature, cultural heritage, translation, academic writing and digital humanities.
Thursday’s programme included a keynote by Rocío Ortuño Casanova, director of UNED’s Digital Humanities Innovation Lab (LINHD), on retrieval-augmented generation (RAG) as a humanistic model for responsible educational AI. Later in the day, the programme listed a session entitled ‘Let’s Talk About Bias: Artificial Intelligence and Ethics’, involving Ortuño, Tomás Domingo Moratalla, Alba García Seco de Herrera and Alejandro Benito Santos. The latter three are members of the INHDIE research group.
The conference also includes perspectives that move the debate beyond its usual centres. Friday’s programme features a paper by Macarena Ortiz (University of Sydney) and Adriana Díaz on algorithmic coloniality and language teaching, exploring decolonial approaches to AI mediation. Thursday’s programme included Ugo Blanco, from UNDP in Trinidad and Tobago, speaking on AI governance and ethics from the perspective of the Caribbean’s small island developing states.
The programme places critical evaluation of systems involved in selecting, organising and interpreting information at the heart of the discussion. AI tools can reproduce biases in their training data, and their responses may be incorrect, incomplete or insufficiently representative of cultural diversity.
From a humanities perspective, it matters which sources are used, whose voices are excluded and how responsibility is distributed when an interpretation incorporates model-generated content. RAG systems retrieve information from documentary sources before producing a response, yet questions of selection, authority and the contextualisation of knowledge remain unresolved.
From this perspective, integrating AI into universities requires methodological transparency, the cross-checking of sources and human responsibility for research outcomes.
Sources: LINHD (UNED), LINHD participates in an international conference on critical thinking and generative AI and final conference programme.
Literacy, method and responsibility
The three initiatives approach the relationship between knowledge and artificial intelligence from different angles. MIL4Peace places it within communities seeking to strengthen participation and coexistence. Artz reconsiders anthropological methods in the light of interactions with generative systems. The UNED conference brings ethical and epistemological criteria into educational and scientific practice.
Taken together, they show that critical literacy, methodological reflection and institutional responsibility complement one another. For anthropology, these transformations open up opportunities for research while demanding attention to the cultural contexts in which knowledge is produced, the power relations running through technologies and the limits of their interpretative capacities.
Thinking with artificial intelligence also requires understanding the social, cultural and political conditions that make that interaction possible.