Feels a bit surreal to have completed the taught components for the first year already, but here we are. I was feeling a bit lost for how to continue over the summer, but luckily I have lovely classmates and we have teamed up to have regular check-ins. Task one – recap what I’ve learnt so far:

1. The patriarchy and capitalism go hand-in hand and while I’ve always been a strong feminist, I’m becoming more anti-capitalist by the day. It’s an exploitative model that isn’t working and I’m even more sure some sort of radical distribution model is needed (UBI etc.)
2. I strongly dislike the capitalist concept of productivity and the more I learn about other cultures and think about the future of AI, the more I think that the drive for productivity will be our demise.
3. I don’t know how to balance being on social media and caring about my data privacy, I think the reality is that you can’t – either you are on social media and sacrificing some privacy or you are not.
4. Working in an interdisciplinary way is not ‘obvious’ or even the norm and it’s important to intentionally consider many different angles and points of view.
5. I’m starting to enjoy collaborating on project work, more than I thought I would.
6. There is another path (SST) to technological determinism and when considering the future I should be wary of my own bias for thinking of technology solutions and that the progression of automation is inevitable.
7. Learning about all the terrible ways data is harvested about us can be exhausting and it’s important to look for those trying to do better alongside finding out about the bad.
8. It’s very important to test assumptions (e.g. assuming that the DWP is using automated processing of digital forms) and seek truth.
9. Data is not neutral.
10. All biases and exploitations can be reduced down to something that sits along a race (including religions as races), class or gender line.
11. The scale of impact that colonialism has had can’t really be understood for centuries yet as we are still ‘undoing’ it.
12. Abstracts and conclusions are helpful because there isn’t enough time to read everything.

• Inclusive Society –  Results are in. Not my best score, but on reflection not terrible. I’m not sure I will do a creative output for the final thesis, or if I do it will be quite close to a more formal output, perhaps as a policy paper or report.
• Work Futures – assignment in. This is probably one of my favourite assignments so far and I really dived into the challenge of productivity and why focusing on AI tools that improve it might cause more problems than they solve. Once I have my grade I’ll do a deep dive blog post on the idea as I think it’s quite fundamental to my views on why we need more radical distribution mechanisms.
• Ethical Data Futures – Completed the assignment. Why are they all so short on word count and how are we supposed to fit it all in? I think I’ve been able to respond well enough to the assignment question, though I would have loved more face time on this course.
• Building Near Futures – I loved what we created and our group for this project. Our concept used AI to help people edit images of them on the web, with a murky undertone of corporate power. It was such a fun project despite a frustratingly organised course. I hope next year they reduce the number of people on the course or split it into two cohorts as there were too many people for the tutors to support properly.

One of my goals with this thesis was to experience the process of publishing in a journal. I’m keen to become more involved with research and I know that publishing is a part of this. It was putting a lot of pressure (in my head) on the project. I’ve since been asked to contribute to a journal in my professional capacity. I might not be held to the same rigour as an academic piece, but at least I can take that pressure off this project!

Still mulling the two options over. UBI still has my heart but the more I think about the PIP project the more I feel it needs to be done. Another classmate is also potentially looking into digital accessibility so we might be able to support each other. One of the spanners in the works is that the government is looking to change the rules around how PIP is paid (see white paper here), however, these might only come in after I finish the course. I will have to consider this for when I do interviews.

[8] Checkpoint / Knowledge Integration and Project Planning: Data, Inequality and Society (2022-2023) by blogadmin is licensed under a Creative Commons Attribution CC BY 3.0