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Imagining Tech Futures for the Common Good

Module description

This module analyses AI, data, algorithms and social media with a focus on imagining better tech futures for the common good. To achieve this, we ask: what does the common good mean? And how can digital technologies be used as tools for the common good? When asking these questions, we draw from perspectives on decolonial imagination, intersectionality, and critical data/AI studies. We also build upon notions of autonomy, the commons, and pluriversality, employing participatory pedagogies and applying them to future tech scenarios. Such scenarios are framed in line with the UN’s Sustainable Development Goals (SDGs). At the end of the term, we will set up a Digital Media Museum of the Future, working in groups to devise creative artefacts and connecting them to these concepts. This museum can be used as a creative portfolio in which students can showcase their digital media skills as well as critical thinking. There are no pre-requisites or co-requisites for this module, and no specialist knowledge, skills, or experience are required to take it. This module is recommended for interdisciplinary pathways.

Module aims - intentions of the module

This module aims to:

• Introduce the core theories and concepts that underpin digital media, imagining speculative futures and Sustainable Development Goals
• Engage you in group work to create digital media artefacts, drawing from research, and reflecting your specialisations in media and communication. 
• Enable you to apply your ideas and use your imagination, combining this exercise with digital media skills to tackle a sustainable development goal (SDG)
• To introduce you to participatory methodologies and approaches
• Engage you in the practical skills and methods specific to digital media and communications professions.
• Foster your critical thinking by addressing the relationships between digital media, Sustainable Development Goals (SDGs) and your imagination for a better future

Intended Learning Outcomes (ILOs)

ILO: Module-specific skills

On successfully completing the module you will be able to...

• 1. Identify and critically analyse the core theories and concepts that underpin digital media, speculative futures and critical data/AI studies
• 2. Work in groups and develop media artefacts to set up a Digital Media Museum of the Future, reflecting your conceptual understanding, and your ability to imagine better futures connected to the UN’s Sustainable Development Goals.

ILO: Discipline-specific skills

On successfully completing the module you will be able to...

• 3. Demonstrate an understanding about the UN’s Sustainable Development Goals (SDGs) and their three environmental, social and economic pillars, applying them to media and communication studies and practices.
• 4. Demonstrate a grasp of a range of digital media professional skills required in the planning and production, design and distribution of a modern campaign/multimedia publication/station/channel/site (as part of the Digital Media Museum of the Future).

ILO: Personal and key skills

On successfully completing the module you will be able to...

• 5. Demonstrate research and content creation skills using a critically informed approach.
• 6. Critically analyse your own practice, and the degree to which the finished product meets the goals set at the start, synthesising knowledge gained and applying it to the group and individual work.
• 7. Develop collaborative group work, deciding on your roles and communicating professionally with your peers .

Syllabus plan

The content will vary from year to year, but it is envisioned that the module will cover many of the following topics:

• Imagining Tech Futures for the Common Good
• From Social Good to the Commons
• Participatory approaches to data and AI
• Towards a Collective Understanding of Autonomy
• From Data Colonialism to Pluriversal Futures
• From Algorithmic Oppression to Intersectional Futures
• AI and empathy
• AI, gender and racial equality
• Perspectives of marginalised communities in the Global south on AI and data

Learning activities and teaching methods (given in hours of study time)

Details of learning activities and teaching methods

Formative assessment

Summative assessment (% of credit)

Details of summative assessment

Details of re-assessment (where required by referral or deferral)

Re-assessment notes

Deferral – if you miss an assessment for certificated reasons judged acceptable by the Mitigation Committee, you will normally be either deferred in the assessment or an extension may be granted. The mark given for a re-assessment taken as a result of deferral will not be capped and will be treated as it would be if it were your first attempt at the assessment.

Referral – if you have failed the module overall (i.e., a final overall module mark of less than 40%) you will be required to submit a further assessment as necessary. If you are successful on referral, your overall module mark will be capped at 40%.

Indicative learning resources - Basic reading

• Benjamin, R. (2024). Imagination: A Manifesto. W.W Norton & Company.
• Berendt, M. (2019). AI for the Common Good?! Pitfalls, Challenges, and Ethics Pen-Testing. Paladym, Journal of Behavioral Robotics, 10, 44-65.
• Birkinbine, B. (2018). Commons praxis: towards a critical political economy of the digital commons. TripleC 16(1):290–305
• Brah, A. (2022). Decolonial Imaginings: Intersectional Conversations and Contestations. Goldsmiths Press. Chapter 10.
• Costanza-Chock, S. (2021). Design Justice; Community-Led Practices to Build the Worlds We Need. Cambridge, MA: the MIT Press. Conclusion – Directions for Future Work.
• Dencik, L., Hintz, A., Redden, J. & Treré, E. (2022). Data Justice. London, Thousand Oaks, CA: Sage Publications. Chapter “Data and Social Justice”.
• Escobar, A. (2018). Designs for the Pluriverse: Radical Interdependence, Autonomy and the Making of Worlds. Durham, London: Duke University Press. Chapter 6.
• Krenak, A. (2020). Ideas to Postpone the End of the World. Anansi International.
• Medrado, A. & Verdegem, P. (2023). AI for Social Good? Inspirations from Participatory Action Research (PAR) to Critical Data Studies. London University of Westminster. https://westminsterresearch.westminster.ac.uk/item/w3050/ai-for-social-goodinspirations-from-participatory-action-research-par-to-critical-data-studies
• Olufemi, L. (2021). Experiments in Imagining Otherwise. Hajar Press. Listen along the Experiments in Imagining Otherwise Playlist on Spotify, curated by the author.

Indicative learning resources - Other resources

• Ada Lovelace Institute (2022). Rethinking Data and Rebalancing Digital Power. Available: https://www.adalovelaceinstitute.org/project/rethinking-data/ Chapter 2.
• The Tierra Comun Network (2023). Resisting Data Colonialism, A Practical Intervention: the Tierra Comun Network. Resisting Data Colonialism: What Lies Ahead (page 95). The Institute of Network Cultures. https://networkcultures.org/wp-content/uploads/2023/12/ResistingDataColonialism_INC2023 _TOD50.pdf
• Coding Rights (no date). Musea M.A.M.I (Musea de Antiguedades Misóginas Increíbles). https://museamami.org/sobre/ Coding Rights (no date).
• The Oracle for Transfeminist Technologies. https://www.transfeministech.codingrights.org/

Key words search

Decolonial imagination, tech future, AI, data, sustainable development goals, digital media