Readings

Mattu, Julia Angwin, Jeff Larson,Lauren Kirchner,Surya. “Machine Bias.” ProPublica, https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing. Accessed 16 Oct. 2023.

Cooper, A. Feder, et al. “Accountability in an Algorithmic Society: Relationality, Responsibility, and Robustness in Machine Learning.” 2022 ACM Conference on Fairness, Accountability, and Transparency, 2022, pp. 864–76. arXiv.org, https://doi.org/10.1145/3531146.3533150.

Julia Stoyanovich and Falaah Arif Khan. “What is AI?”. We are AI
Comics, Vol 1 (2021) https://dataresponsibly.github.io/we-are-ai/comics/vol1_en.pdf

Julia Stoyanovich and Falaah Arif Khan. “Learning from Data”.
We are AI Comics, Vol 2 (2021)
https://dataresponsibly.github.io/we-are-ai/comics/vol2_en.pdf

Julia Stoyanovich, Mona Sloane and Falaah Arif Khan.
“Who lives, who dies, who decides?”. We are AI Comics, Vol 3 (2021)
https://dataresponsibly.github.io/we-are-ai/comics/vol3_en.pdf

Julia Stoyanovich and Falaah Arif Khan. “All about that Bias”.
We are AI Comics, Vol 4 (2021)
https://dataresponsibly.github.io/we-are-ai/comics/vol4_en.pdf

Julia Stoyanovich and Falaah Arif Khan. “We Are AI”.
We are AI Comics, Vol 5 (2021)
https://dataresponsibly.github.io/we-are-ai/comics/vol5_en.pdf

Writing

In a blog post of no more than 500 words, consider the three different approaches taken between the ProPublica article, the ACM conference paper, and the AI Comics. What is the value of each approach to reaching their intended audiences? What are the potential pitfalls?