Artificial Equity
A human rights approach to algorithms and data privacy
It’s been 3 months since I graduated from my master’s program. It feels like a year has gone by since the long nights, endless stacks of “recommended reading,” and verbose academic prose I no longer fully comprehend. Public policy is a broad and ambiguous profession, much like the visual design career I came from.
I’m sharing with you all my final research paper because, frankly, I’m proud of how I came out the other side of this two year experience. But also, while we look to OpenAI, Anthropic, and other new venture capital-backed private corporations to establish responsible AI standards, we must be critical of who sets the rules the rest of us live by.
Politicians and government agencies rely on the proprietary knowledge hoarded by private tech corporations. Their knowledge is the result of an industry filled to the brim with STEM educated employees and ivy league entrepreneurs; worlds built on a history of generational wealth, racism, sexism, and discrimination of all kinds. We lack algorithms that represent the diversity of gender, race, ethnicity, sexuality, and disability. Cynically, it’s by design, but more practically it is now a flaw of an education and employment system that relies on old tools like degrees and references.
This paper is likely too long for casual reading, but enjoy the executive summary, introduction, let your eyes drift along the contours of my personally designed charts and tables, and finally, come to rest at the conclusion. There are currently many proposals for data privacy legislation, and there will be more to come in future seasons. I hope to provide you some insight into the legalese so you can go about your lives knowing I’m perfectly happy diving into the deep in your stead.
Enjoy!
Lisa Kim Thorn, MPP ’23 (Hec yeah! 👩🏻🎓)