A reading list for a journal club and special topics class. A tentative title is:
Unconventional approaches in AI and CS: transdisciplinarity, complex systems perspectives, participatory design, ethics and explainability
Computer scientist as toolsmith 2
https://dl.acm.org/doi/epdf/10.1145/227234.227243
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In contrast with many engineers who make houses, cars, medicines, and clothing for human need and enjoyment, we make things that do not themselves directly satisfy human needs, but which others use in making things that enrich human living. In a word, the computer scientist is a toolsmith—no more, but no less. It is an honorable calling. If we perceive our role aright, we then see more clearly the proper criterion for success: a toolmaker succeeds as, and only as, the users of his tool succeed with his aid. However shining the blade, however jeweled the hilt, however perfect the heft, a sword is tested only by cutting. That swordsmith is successful whose clients die of old age.
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The scientist builds in order to study; the engineer studies in order to build.
Machine learning toolsmith
https://bastian.rieck.me/blog/posts/2022/toolsmith/
Troubling Trends in Machine Learning Scholarship
https://arxiv.org/abs/1807.03341
Trans-disciplinarity
https://medium.com/@miekevanderbijl/transdisciplinary-innovation-and-design-d19d1520ddca
https://dl.designresearchsociety.org/drs-conference-papers/drs2022/researchpapers/112/
Design in complex environments and complex systems
https://www.sciencedirect.com/science/article/pii/S2405872618300790#fn44
The Mythical Man Month
https://archive.org/details/MythicalManMonth/page/n29/mode/2up
Patient and public involvement (PPI) in AI
Communication between humans and computers
http://inverseprobability.com/talks/notes/understanding-ai.html
How data is used by activists and how to sustain data activism (participatory activism)
https://doi.org/10.1016/j.patter.2022.100530
User feedback in developing nations
https://ideaspace.cam.ac.uk/2022/02/01/start-up-stories-with-tristram-norman/
Seymour Papert
https://www.nature.com/articles/537308a
Actively constructing models builds understanding
Cognitive bias in software engineering
https://cacm.acm.org/magazines/2022/4/259421-cognitive-biases-in-software-development
Challenges in deploying machine learning models
https://www.repository.cam.ac.uk/handle/1810/336516
Data ethics club
https://doi.org/10.1016/j.patter.2022.100537
https://dataethicsclub.com/contents/write_ups/write-ups.html
https://dataethicsclub.com/contents/reading-list.html
High stakes decisions using simple models (Cynthia Rudin): iterating with experts and building simple explainable models
https://arxiv.org/abs/1811.10154
Class contrastive reasoning
https://www.nature.com/articles/s41537-021-00191-y
Explainability is in the mind of the beholder
https://arxiv.org/abs/2112.14466
Explainable AI Pandora's Box Pitfalls
https://cacm.acm.org/magazines/2022/4/259398-explainable-ai/fulltext
The Nature and Experience of Mathematical Beauty
https://scholarship.claremont.edu/jhm/vol6/iss1/3
Conversations with clinicians
https://www.vanderschaar-lab.com/making-machine-learning-interpretable-a-dialog-with-clinicians/
All boxes are black (clinicians also do not understand exactly how machines/interventions work)
https://journals.lww.com/anesthesia-analgesia/Fulltext/2016/02000/All_Boxes_Are_Black.6.aspx#
The emergence of understanding in a computer model of concepts and analogy-making
https://www.sciencedirect.com/science/article/abs/pii/0167278990900865?via%3Dihub
https://www.tomhegen.com/collections/the-lithium-series-i
The Psychology of Invention in the Mathematical Field
The Theory of Mind
Copycat (a computational model of analogy making)
The emergence of understanding in a computer model of concepts and analogy-making
https://www.sciencedirect.com/science/article/abs/pii/0167278990900865?via%3Dihub
Creativity and artificial intelligence
https://www.sciencedirect.com/science/article/pii/S0004370298000551
The overfitted brain: Dreams evolved to assist generalization
https://doi.org/10.1016/j.patter.2021.100244
Commonsense reasoning
https://dl.acm.org/doi/10.1145/2701413
Stories and narratives (Patrick Winston)
https://nautil.us/the-storytelling-computer-8380/
https://dspace.mit.edu/handle/1721.1/67693
Health information systems in developing countries: some reflections on information for action
Toward Justice in Computer Science through Community, Criticality, and Citizenship
Intersectional AI is essential: polyvocal, multimodal, experimental methods to save artificial intelligence
https://revistas.ucp.pt/index.php/jsta/article/view/7328
Inequality of what? An intersectional approach to digital inequality under Covid-19
https://www.sciencedirect.com/science/article/abs/pii/S1471772721000075
Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence
https://link.springer.com/article/10.1007/s13347-020-00405-8
A decolonial framework helps connect instances of algorithmic oppression to wider socio-political and cultural contexts, enabling a geographically, historically and intersectionally expansive analysis of risks and opportunities pertaining to AI systems. Notably, it allows for the analysis to move beyond North American or European identity frameworks or definitions of harms. By connecting instances of algorithmic oppression across geographies, new approaches that consider alternative possibilities of using technology in socially complex settings in more critical and considered ways will emerge, and so too will designs that incorporate inclusive and well-adapted mechanisms of oversight and redress from the start.
Info-topia: Postcolonial cyberspace and artificial intelligence in TRON: Legacy and Nalo Hopkinson’s Midnight Robber
https://www.tandfonline.com/doi/abs/10.1080/17449855.2017.1405834
Feminicide and counterdata production: Activist efforts to monitor and challenge gender-related violence
https://doi.org/10.1016/j.patter.2022.100530
https://www.cl.cam.ac.uk/teaching/2122/R255/
Reimagine a future where AI is deployed
Evaluate systemic impact of AI
Case studies: working in a logistics company and deploying AI
Voices of students (paper)
Soumya Banerjee