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Run! For Runtime (powered by Al Gore-rithm)

SSI Hack Day project: Run! For Runtime

A drawing of the Al-Gore-Rithm AI assistant character

Why?

There is a disconnect between users of compute (in particular, high resource users in research who are increasingly nudged towards using generative AI for simple tasks) and the resources used to enable that compute. A user runs a job and waits for the output. But "hidden" labour, material resources, and energetics underpin all compute. This game brings that the surface, and prompts users to consider the proportionality - or otherwise - of their compute actions.

Who is this for?

This project is aimed at people trying to educate researchers or students in the impact of computating in their work. It consists of a set of materials for facilitators to run an exercise consiting of a number of tasks to be performed by participants, who are divided unequally to represent the researcher and the resources required. We also provide a web application to help run the exercise, with the option of running it in-person, virtual or hybrid.

For more information on how to use these resources, please read the facilitator instructions.

Contributing ✏️

Run! for runtime is a collaborative project and we welcome suggestions and contributions. We hope one of the invitations below works for you, but if not, please let us know!

🏃 I'm busy, I only have 1 minute

  • Invite members of your communities to look at our project

I've got 5 minutes - tell me what I should do

  • Look through the README and see if you think this would be a useful teaching tool for you
  • Submit issues for any bugs or typos you see

💻 I see the potential... I can work on this for #opensourcefriday

  • Go through the task descriptions and add your own / improve the existing ones

🎉 It's my life's mission to make people understand the environmental, social and moral impact of computing

  • Become a facilitator and use Run! for Runtime to spread the message
  • Keep Run for Runtime updated with the latest resources/research

Please open a GitHub issue to suggest a new idea, contribute a task, or let us know about bugs.

Acknowledgements 👪

This project originated as part of the Collaborations Workshop 2024.

It was based on an original idea by Samantha Ahern, Sophia Batchelor, Neil Chue Hong, Sarah Jaffa, Patrick McCann and Colin Sauze.

The first prototype was developed during the CW24 hackday by Samantha Ahern (@quirksahern), James Baker (@drjwbaker), Sophia Batchelor (@BrainonSilicon), Neil Chue Hong (@npch) and Patrick McCann (@pgmcann).

License

This work is licensed under a Creative Commons Attribution 4.0 International license. You are free to share and adapt the material for any purpose, even commercially, as long as you provide attribution (give appropriate credit, provide a link to the license, and indicate if changes were made) in any reasonable manner, but not in any way that suggests the licensor endorses you or your use, and with no additional restrictions.

Software source code is licensed under a MIT license. You are free to use this software without restriction including to use, copy, modify, sublicense, distribute or sell. The copyright notice and license must be included in all copies or substantial portions of the Software

Further reading 📚

Some great resources on understanding the impact of computing, AI and data centres include:

  • Estampa's Cartography of generative AI (2024)
  • Max Liborion's Pollution Is Colonialism (2021)
  • Mary L. Gray and Siddharth Suri's book Ghost work: how to stop Silicon Valley from building a new global underclass (2019)
  • Loïc Lannelongue, Jason Grealey, and Michael Inouye's ‘Green Algorithms: Quantifying the Carbon Footprint of Computation’ Advanced Science (2021)
  • Crawford's Atlas of AI