Archaeology and AI - ARC00141M

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Module summary

This module explores how artificial intelligence (AI), particularly machine learning, predictive analytics, computer vision, large language models (LLM) and generative AIs, can be employed within Archaeology and Cultural Heritage. As a fast-moving suite of technologies, we will introduce you to the field's cutting-edge and examine best practices for data gathering, data management, algorithmic decision-making and interpretation using these tools. Students will gain insights into the potential and challenges of AI for archaeological research. The module will also critically assess ethical considerations surrounding algorithmic bias, intellectual property and responsible stewardship of archaeological information in the context of the ‘AI Revolution’

Module will run

Occurrence	Teaching period
A	Semester 2 2025-26

Module aims

Specifically this module aims:

• To develop knowledge and understanding of artificial intelligence within archaeology and cultural heritage and the intended and unintended implications of use of these methods.
• To develop a critical perspective of the theoretical underpinnings of artificial intelligence use in archaeology and cultural heritage.
• To raise awareness of advances in AI and archaeology and cultural heritage within the context of progressive change and future potential.

Module learning outcomes

By the end of the module the students should be able to:

• Demonstrate fundamental knowledge of AI concepts and data management principles in archaeological and cultural heritage research, applying these skills to at least one real or simulated dataset.
• Critically assess the ethical implications and potential biases of AI applications in archaeology and cultural heritage, offering strategies to address issues of bias or accountability.
• Explore case studies related to artificial intelligence and archaeology and cultural heritage.
• Present an AI-driven workflow for archaeological and cultural heritage data analysis, including its limitations, potential improvements, and broader heritage impact.
• Debate potential future uses of AI within archaeology and cultural heritage.

Module content

This module aims to provide students with a robust understanding of how AI can be harnessed in archaeological research and the wider heritage sector by introducing core AI concepts and methodologies, fostering an appreciation of the ethical and practical implications of data management, developing critical thinking on the impact and limitations of AI applications, and exploring cutting-edge innovations (from artefact recognition to predictive modeling) that reveal the transformative potential of AI in uncovering, interpreting, and preserving the past.

Indicative assessment

Task	% of module mark
Essay/coursework	100

Special assessment rules

None

Indicative reassessment

Task	% of module mark
Essay/coursework	100

Module feedback

Formative: oral feedback from module leaders

Summative: written feedback within the University's turnaround policy

Indicative reading

Magnani, M. and Clindaniel, J. (2023). Artificial Intelligence and Archaeological Illustration. Advances in Archaeological Practice, 11 (4), pp.452–460.

Martos, R., Ibáñez, O. and Mesejo, P. (2024). Artificial intelligence in forensic anthropology: State of the art and Skeleton-ID project. In: Methodological and Technological Advances in Death Investigations. Elsevier. pp.83–153.

Tenzer, M. et al. (2024). Debating AI in Archaeology: applications, implications, and ethical considerations. Internet archaeology, (67). [Online]. Available at: doi:10.11141/ia.67.8