Teaching Workshop: Artificial Intelligence and Archaeology
A.Y. 2025/2026
Learning objectives
The first objective of the course is to provide students with a critical and operational understanding of the potential, methodologies and ethical challenges associated with the application of Artificial Intelligence (AI) in the fields of Cultural Heritage and Archaeology. The course aims to bridge the gap between the humanities and advanced technologies, transforming students from mere users into knowledgeable professionals, capable of communicating with technical experts and integrating AI into future research, conservation and heritage enhancement projects.
Expected learning outcomes
They are intended to emphasise the following skills:
1. Knowledge and understanding: identifying and defining the fundamental concepts of Artificial Intelligence (AI); describing the state-of-the-art and applications of AI in the processes of research, cataloguing, conservation and enhancement of cultural and archaeological heritage; understanding the role and limitations of different AI techniques.
2. Application of knowledge and understanding: critically analyse a project or case study; select the most appropriate digitisation technology for the cultural asset.
3. Autonomy of judgement: critically evaluate the effectiveness, reliability and ethical principles related to the application of AI; interpret the results of an AI-guided analysis, distinguishing between machine-generated and human-generated evidence.
4. Communication skills: communicate technical concepts and AI methods in a clear and structured manner; support one's critical analysis with respect to a known case study.
5. Learning skills: recognise the need for continuous updating in this field of research, independently identifying and evaluating the sources' truthfulness; develop a targeted bibliographic research methodology, depending on the case study or projects related to cultural and archaeological heritage.
1. Knowledge and understanding: identifying and defining the fundamental concepts of Artificial Intelligence (AI); describing the state-of-the-art and applications of AI in the processes of research, cataloguing, conservation and enhancement of cultural and archaeological heritage; understanding the role and limitations of different AI techniques.
2. Application of knowledge and understanding: critically analyse a project or case study; select the most appropriate digitisation technology for the cultural asset.
3. Autonomy of judgement: critically evaluate the effectiveness, reliability and ethical principles related to the application of AI; interpret the results of an AI-guided analysis, distinguishing between machine-generated and human-generated evidence.
4. Communication skills: communicate technical concepts and AI methods in a clear and structured manner; support one's critical analysis with respect to a known case study.
5. Learning skills: recognise the need for continuous updating in this field of research, independently identifying and evaluating the sources' truthfulness; develop a targeted bibliographic research methodology, depending on the case study or projects related to cultural and archaeological heritage.
Lesson period: Second semester
Assessment methods: Giudizio di approvazione
Assessment result: superato/non superato
Single course
This course can be attended as a single course.
Course syllabus and organization
Single session
Responsible
Lesson period
Second semester
Course syllabus
The course will be structured in three parts:
1. Introduction to Artificial Intelligence and its key concepts (definition and areas of application of AI; basic notions of machine learning, computer vision, pattern recognition; examples of AI in cultural and archaeological heritage.
2. AI tools and techniques applied to cultural heritage (digitisation of works and sites with 3D scanning; analysis of images and archaeological data; cataloguing and digital preservation).
3. Case studies and practical workshops (AI applications in archaeology; use of basic software for image recognition or data analysis; discussion on privacy management, ethical challenges and future applications).
1. Introduction to Artificial Intelligence and its key concepts (definition and areas of application of AI; basic notions of machine learning, computer vision, pattern recognition; examples of AI in cultural and archaeological heritage.
2. AI tools and techniques applied to cultural heritage (digitisation of works and sites with 3D scanning; analysis of images and archaeological data; cataloguing and digital preservation).
3. Case studies and practical workshops (AI applications in archaeology; use of basic software for image recognition or data analysis; discussion on privacy management, ethical challenges and future applications).
Prerequisites for admission
There are no compulsory exams or preparatory courses.
However, to achieve the course objectives, active participation during lessons, critical thinking and reflection skills, and a propensity for teamwork are required to provide innovative food for thought, analyse and develop personal opinions on the matter, and collaborate to share ideas and perspectives.
However, to achieve the course objectives, active participation during lessons, critical thinking and reflection skills, and a propensity for teamwork are required to provide innovative food for thought, analyse and develop personal opinions on the matter, and collaborate to share ideas and perspectives.
Teaching methods
The course is delivered through frontal lessons, presented in PDF format or via other media (videos, fact sheets, articles, web resources, among others). Some parts of the lessons will be dedicated to practical activities and discussions among/with the students enrolled in the course.
Teaching Resources
The teaching materials consist of PDF slides to be presented in class, accompanied by other support materials, in-depth scientific papers downloadable from online journals in Open Access or hybrid formats, provided by the lecturer, and lecture notes.
NB: The programme is subject to change and updates, which will be communicated in a timely manner.
Non-attending students must agree on an alternative course of study with the lecturer.
NB: The programme is subject to change and updates, which will be communicated in a timely manner.
Non-attending students must agree on an alternative course of study with the lecturer.
Assessment methods and Criteria
The oral exam will be held in person, except in emergency cases, when Microsoft Teams will be used.
The test aims to assess the student's knowledge of the course content, the state of the art, and the applications of AI in the field of Cultural Heritage and Archaeology, as well as a bibliographic review of case studies and concrete research projects developed in recent decades.
The exam will also include the presentation (via slides) of a case study (agreed with the professor), in which an analysis of the project, the methods used, and the results obtained is required, to promote assessment and critical thinking skills.
The test aims to assess the student's knowledge of the course content, the state of the art, and the applications of AI in the field of Cultural Heritage and Archaeology, as well as a bibliographic review of case studies and concrete research projects developed in recent decades.
The exam will also include the presentation (via slides) of a case study (agreed with the professor), in which an analysis of the project, the methods used, and the results obtained is required, to promote assessment and critical thinking skills.
Professor(s)