AI in Anthropology
Course Number: AN999
Subject: Anthropology
Generative artificial intelligence can be used in many aspects of learning, teaching, and research. It also raises questions that are especially relevant to Anthropology, including how people and cultures are represented, whose knowledge is included or excluded, and how research data and community knowledge are handled.
This page connects Anthropology students and instructors with Laurier’s general guidance on generative AI and highlights selected questions and resources relevant to the discipline. Expectations for generative AI use vary by course and assignment. Students should always follow the directions provided by their instructor.
Laurier Guidance For Students
Start here for Laurier guidance on:
- Using generative AI responsibly, including determining whether it is permitted, following course expectations, and protecting personal, confidential, and copyrighted information.
- Maintaining academic integrity, including evaluating AI-generated content and acknowledging or citing AI use when required.
- Developing your AI literacy, including effective prompting and Laurier’s self-paced Generative AI Literacy Modules.
The Student Resource Hub emphasizes that students should check their course outline and instructor’s expectations before using generative AI.
Laurier Guidance For Instructors
Start here for Laurier guidance on:
- Establishing course expectations, including instructor guidelines, syllabus statements, student acknowledgement statements, and communication about permitted AI use.
- Supporting academic integrity and assessment, including assessment design, authorized and unauthorized uses of AI, and strategies for responding to emerging challenges.
- Developing your teaching practice, including curated resources, examples from Laurier instructors, recordings, workshops, and support from Teaching Excellence and Innovation.
The guide supports instructors in making informed decisions about whether and how generative AI relates to their courses, disciplines, learning outcomes, and assessments.
Anthropological Perspectives on AI
Anthropologists study AI not only as a tool, but also as a social and cultural phenomenon. Anthropological perspectives can help us examine how AI represents and classifies people and knowledge, reflects unequal relationships of power, changes work and social life, and is adopted, resisted, or reshaped by different communities.
Selected Resources
These selected resources explore AI in Anthropology teaching, research, and professional practice. They may help instructors consider AI as a classroom issue, an object of anthropological inquiry, and an emerging influence on anthropological methods.
Teaching Anthropology in the Age of AI
- The Emic Perspective of Generative AI [Blog post]
Uses the anthropological distinction between emic and etic perspectives to encourage instructors to investigate students’ motivations and experiences with generative AI rather than concentrating only on detection and prohibition. - AI for Learning: Experiments from Three Anthropology Classrooms [Article]
Presents classroom experiments involving anthropological writing, medical AI applications, and archaeology, with attention to AI literacy, reliability, research, and ethics. - Managing AI in the Classroom: An Ethnography of the “In-between” [Research article]
Examines how professors in the University of British Columbia Faculty of Arts navigate uncertainty when developing classroom policies for generative AI.
Anthropological Perspectives on AI and Algorithms
Introductions to how anthropologists study AI, algorithms, intelligence, human-machine relationships, and the social assumptions embedded in technical systems.
- The Anthropology of AI with Joseph Wilson [Research profile/interview]
Discusses AI as a cultural and social concept and considers what debates about artificial intelligence reveal about culturally situated ideas of intelligence and humanity. - Anthropologists Have Their Eye on AI [Research overview]
Introduces work connecting anthropology with AI, including questions of theory, sociocultural inquiry, research methods, governance, and Indigenous future-building. - Artificial Intelligence and the Anthropologist [Research reflection]
Describes anthropological research into how social, cultural, ethical, and technical considerations interact in AI research and development. - Anthropology and Algorithms [Podcast and transcript]
Explores how anthropology can contribute to understanding algorithms, including their cultural construction and implications for ethics, regulation, everyday life, and social justice. - Anthropology and AI: From Past Engagements to the Contemporary Landscape [Video]
Traces anthropology’s engagement with artificial intelligence from earlier interdisciplinary work on cybernetics to contemporary debates about anthropologists’ roles in interpreting and influencing AI.
AI in Anthropological Research and Methods
Resources on using AI and computational techniques in ethnography, qualitative analysis, data collection, and anthropological research workflows.
- AI Anthropology: A New Opportunity for Anthropological Work[Article]
Proposes an approach in which anthropologists study AI, use AI-enabled research methods, and contribute anthropological knowledge to the design and development of AI systems. - AI Anthropology Toolkit [Open-source toolkit]
Provides computational resources for anthropological and qualitative research, including tools and workflows for data collection, transcript processing, qualitative coding, thematic analysis, and multimodal research. - Automated Digital Ethnography: Revolutionizing Anthropological Research [Methods overview]
Introduces an AI-assisted approach to collecting and analyzing digital ethnographic material and discusses scalability, multimodal analysis, privacy, cultural sensitivity, bias, and the continued importance of human interpretation.
Applied Anthropology, Careers, and Disciplinary Futures
Resources on anthropologists’ professional roles in AI, applications of anthropological knowledge, and the possible effects of AI on the discipline.
- Preparing for Careers in the Age of AI [Video]
A Society for Applied Anthropology webinar about career preparation and pathways for anthropologists working in AI-related environments. - Imagining Anthropological Futures with AI: Opportunities and Pressures on the Field[Video]
Considers opportunities for anthropologists to participate in AI development alongside the institutional, methodological, and professional pressures AI creates for the discipline. - Applied AI in Practice [Video]
Presents examples of anthropological methods and perspectives being applied to AI products, services, research, user experience, and questions of trust and agency. - Ten Predictions for AI and the Future of Anthropology [Article]
Offers a speculative account of AI’s possible effects on anthropological research, ethnography, multimodal analysis, public engagement, professional practice, and disciplinary development.
Books
Longer scholarly treatments of anthropology, AI, and the social worlds surrounding artificial intelligence.
A collection examining relationships between Anthropology and AI, including anthropological contributions to the understanding, design, and critique of AI systems.
- Anthropology and AI [eBook]
An interdisciplinary introduction to relationships between anthropological research and artificial intelligence.
Organizations, Communities, and Events
Professional groups, conferences, and networking opportunities for continuing engagement with anthropology and AI.
- Anthropology, AI and the Future of Human Society [Conference archive]
Information from the Royal Anthropological Institute’s 2022 virtual conference, which addressed AI and emerging technologies in relation to society, ethics, law, inequality, politics, identity, conflict, the environment, and human-machine interaction.
AI & Anthropology Topical Interest Group [Professional group]
A Society for Applied Anthropology community connecting the study of AI as a sociotechnical phenomenon, the use of AI in research, and anthropological contributions to AI design, policy, organizational change, and professional practice.
Questions for Anthropology
Generative AI systems do not simply retrieve neutral facts. They generate responses from patterns in their training data and may reproduce inaccuracies, stereotypes, exclusions, and unequal relationships of knowledge and power.
When using, evaluating, or studying generative AI in Anthropology, consider the following questions.
Representation
- Does the AI output generalize about a cultural, linguistic, social, or Indigenous community?
- Does it present a culture as uniform, isolated, or unchanging?
- Does it rely on stereotypes or make unsupported assumptions about people’s identities, beliefs, or practices?
- Does it distinguish between how people represent themselves and how they have been represented by outsiders?
Knowledge and Power
- Whose perspectives and forms of knowledge are represented in the response?
- Whose perspectives, languages, or ways of knowing may be absent?
- Does the response privilege dominant, Western, colonial, or English-language sources and categories?
- Who benefits from the collection, classification, and use of the information on which an AI system relies?
Evidence and Context
- Can claims about people, communities, practices, places, or histories be verified?
- Are the sources real, appropriate, and accurately represented?
- Has important historical, political, social, or cultural context been omitted?
- Does the response acknowledge differences within and among communities?
AI tools may produce convincing but incorrect information, invent sources, misinterpret complex material, and reinforce biases or stereotypes. The Laurier Student Resource Hub therefore advises users to verify facts, sources, and claims rather than treating AI-generated output as authoritative.
Fieldwork, Privacy, and Consent
Before entering research material into an AI tool, consider:
- Do I have permission to upload or process this material?
- Does it contain names, contact information, images, interview data, fieldnotes, recordings, transcripts, or other identifiable information?
- Is the material confidential, culturally sensitive, community-owned, or subject to an agreement about its use?
- Could using the tool conflict with participant consent, research ethics approval, data-management commitments, or community expectations?
- Do I understand how the tool may store or use the information that I enter?
Do not upload sensitive research or community material merely to test what an AI system can do. Students should consult your instructor, supervisor, research ethics documentation, data-management plan, or other applicable guidance before using AI with research data.
Finding and Evaluating Sources
AI tools can suggest terminology or possible directions for a search, but they should not replace searching scholarly literature or reading the sources on which your work depends.
When an AI tool recommends a book, article, author, theory, or ethnographic example:
- Search for the item in Omni or an appropriate Library database.
- Confirm that the source exists.
- Check that the title, author, date, and publication information are correct.
- Read the source itself rather than relying on the AI system’s description.
- Consider whether the source is appropriate for your question and disciplinary context.
- Do not cite a source that you have not located and examined.
Generative AI can invent sources, exaggerate facts, and misinterpret complex questions and articles. It also identifies generating search terms and developing research questions as possible research uses when an instructor permits AI use.
Search the Library
- Use Omni to find books, ebooks, articles, and other materials.
- Use Anthropology Plus, Abstracts in Anthropology, AnthroSource, or other databases listed on the Anthropology guide to search disciplinary literature. The existing Anthropology guide identifies these as primary or focused databases for Anthropology research.
- Use citation information from a verified scholarly source to locate related research.
- Ask the Anthropology librarian for help developing search terms or confirming a source.
Consult Other Resources from the Library
- AI in assignments
- AI in research
- Citing the Use of AI
- Using AI in Research: Brainstorming Examples and Tips
Research Help
Need help locating research on AI and Anthropology, developing search terminology, or checking a source recommended by an AI tool?
Contact Peter Genzinger, Anthropology Librarian