CCAI9033 Artificial Intelligence
War and Peace 2.0: How AI transforms conflicts and humanitarian response

This course is under the thematic cluster(s) of:

  • The Quest for a Meaningful Life (UQM)

SDG-09
SDG-10
SDG-11
SDG-17
Sustainable Development Goals

icon
Communication-intensive Courses
Timetable for Lectures

Course Description

[This is a certified Communication-intensive (Ci) Course which meets all of the requirements endorsed by HKU’s Senate, including i) the teaching and assessment of written, visual and digital communication ‘literacies’; and ii) at least 40% of the course grade assigned to communication-rich assessment tasks.]

Armed conflicts are likely as old as Humankind, and efforts to mitigate their consequences – the humanitarian response – have raised since at least the second half of the 19th century. Technological progress undoubtedly changes the face of warfare, from planes and tanks to the nuclear bomb, but recent conflicts in Ukraine and Gaza clearly show a significant evolution, if not a revolution: the role played by AI on the battlefield.

During this course, you will learn about various uses of AI in conflicts, both as a means to fight and to alleviate the suffering of those affected. After a historical perspective on war and humanitarian action, we will first cover how AI can be leveraged as a weapon in conflicts, whether to spread misinformation or directly on the battleground. After reflecting on how data collection and AI may impact civilians involved, we will then survey a number of AI-based approaches in humanitarian action, from digital mapping and advanced natural language processing to machine learning. We will pay close attention to ethical issues throughout the whole course. We will also dig deeper into the technical aspects of AI-based approaches, and experiment with a range of tools and real-life data.

Assessment will be based on several assignments which encourage creativity, reflection and communication, from creating innovative images with AI to designing a chatbot assisting vulnerable populations.

This course is a flipped-classroom course: you will listen to recordings of the lectures before coming to class, which will free time for many in-class group activities.

This course is certified as communication-intensive and through a range of different activities and assignments, you will get the opportunity to develop your communication skills with feedback from the teachers and your peers.

Course Learning Outcomes

On completing the course, students will be able to:

  1. Describe the recent evolutions of conflicts and humanitarian action under the influence of AI.
  2. Analyze the complexity of real geopolitical situations and of the different facets of the use of AI-based technologies, with a focus on ethics.
  3. Describe and apply AI-based techniques with data relevant to humanitarian action.
  4. Reflect on how human lives and human rights can be affected both positively and negatively by AI in situations of conflicts.
  5. Synthesize and communicate information effectively and creatively with digital outputs such as digital maps and chatbots
  6. Create rich visual outputs such as ‘deep style transfer’ pictures and posters.
  7. Produce textual outputs delivering facts and personal reflections with thoughtfulness, accuracy and impact.

Offer Semester and Day of Teaching

First semester (Wed)

Study Load

Activities Number of hours
Lectures 24
Tutorials 10
Reading / Self-study 40
Assessment: Image creation 10
Assessment: Group project and presentation 16
Assessment: Individual assignment 20
Total: 120

Assessment: 100% coursework

Assessment Tasks Weighting
Quizzes 10
Image creation 20
Group project and presentation 30
Individual assignments 30
Participation 10

Required Reading

A number of sources – news articles, reports or scientific publications, but also digital resources such as websites or videos – will be given for each lecture. Some of them will be required reading or watching, others – usually more complex materials – will be optional recommendations.

Preliminary reading program & relevant websites:

Week 2: War and humanitarian action: a very brief overview

Week 3: AI-generated misinformation

Week 4: Drones and robot dogs: the rise of autonomous weapons

Week 5: People, data, and AI

  • Afina, Y., & Paoli, G. P. (2024). Governance of Artificial Intelligence in the Military Domain: A Multi-stakeholder Perspective on Priority Areas. United Nations Institute for Disarmament Research (UNIDR).
  • EUMigraTool. (EMT). From https://emt.itflows.eu/
  • IMPACT Initiatives. (2024). Using big data and AI to support the Ukraine refugee response – A collaboration between IMPACT Initiatives and Data for Good at Meta. IMPACT Initiatives. From http://reliefweb.int/report/ukraine/using-big-data-and-ai-support-ukraine-refugee-response-collaboration-between-impact-initiatives-and-data-good-meta
  • Office of the High Commissioner for Human Rights. (2025). Human rights and artificial intelligence in the military domain. Geneva: United Nations.
  • Pizzi, M., Romanoff, M., & Engelhardt, T. (2020). AI for humanitarian action: Human rights and ethics. International Review of the Red Cross, 102(913), 145–180.

Week 6: The many facets of facial recognition

Week 7: Digital mapping for good: from crowdsourced efforts to AI solutions 

  • Weinandy, T. J. (2016). Volunteer and technical communities in humanitarian response. Lessons in digital humanitarianism from Typhoon Haiyan. UN Chronicle, 1, 29-30.

Week 8: Processing humanitarian data with advanced natural language processing

  • Imran, M., Mitra, P., & Castillo, C. (2016). Twitter as a lifeline: Human-annotated Twitter Corpora for NLP of crisis-related messages. Proceedings of the 10th International Conference on Language Resources and Evaluation, LREC 2016. Portoroz, Slovenia. [pp. 1638-1643]
  • Kumar, S., Barbier, G., Abbasi, M. A., & Liu, H. (2011, July 17-21). TweetTracker: An analysis tool for humanitarian and disaster relief. Proceedings of the Fifth International Conference on Weblogs and Social Media. Barcelona, Spain. [pp. 661-662]

Week 9: Developing chatbots for vulnerable populations

Week 10: Machine learning for good, Part I

  • DataKind. From https://www.datakind.org/ [Website]
  • Meier, P. (2015). Digital humanitarians: How big data is changing the face of humanitarian response (1st ed.). Routledge. [Chap. 5 “Artificial intelligence for disaster response”, Chap. 6 “Artificial intelligence in the sky”]
  • UN Global Pulse. From https://www.unglobalpulse.org/ [Website]

Week 11: Machine learning for good, Part II

  • Langrand, M. (2024, May 24). Between peril and promise: using AI to predict human displacement. Geneva Solutions. From https://genevasolutions.news/science-tech/between-peril-and-promise-using-ai-to-predict-and-avert-human-displacement
  • Oduoye, M. O., Fatima, E., Muzammil, M. A., Dave, T., Irfan, H., Fariha, F. N. U., Marbell, A., Ubechu, S. C., Scott, G. Y., & Elebesunu, E. E. (2024). Impacts of the advancement in artificial intelligence on laboratory medicine in low‐ and middle‐income countries: Challenges and recommendations—A literature review. Health Science Reports, 7(1), e1794.

Course Co-ordinator and Teacher(s)

Course Co-ordinator Contact
Professor C.D.M. Coupe
School of Humanities (Linguistics), Faculty of Arts		 Tel: 3917 2872
Email: ccoupe@hku.hk
Teacher(s) Contact
Professor C.D.M. Coupe
School of Humanities (Linguistics), Faculty of Arts		 Tel: 3917 2872
Email: ccoupe@hku.hk