I will try to take a personal approach to analyze each of the three major readings we did this week and connect it with the questions we have been asked to think about for the blog post.

Imagine that you are commuting to work in the morning on the subway and just searching for some articles to read around the topic of bias in algorithms. Maybe you even work in public policy or journalism or just somebody really into AI ethics and advocacy. You come across the ProPublica article on your phone. The article paints a clear message of real-world problems caused by racial bias in algorithms. The article can make you think of a friend who once faced some form of discrimination and feel a strong connection to the issue. Or maybe as a public policymaker, you think of your constituents and how best to serve the public cause. The article feels close to the heart. Somewhat like a call to action. Yet, you wonder if it’s a bit too straightforward and if there might be more to the story.

A few days later, while in a library, you stumble upon the ACM conference paper as you research maybe for a potential research paper. It feels like a heavy paper, filled with academic jargon. You recall that one philosophy class you took in college. The paper dives deep, reminding you of those intense classroom debates on ethics. It’s thorough and enlightening, but you can’t help feeling a bit lost in the complex terms. You wonder how many people outside of academia would connect with this.

Then, one rather boring evening as you are doomed to scrolling social media, you learn about AI Comics and since you are already bored with nothing else to do, you decide to see what is about. The visuals instantly grab your attention. You’re reminded of those educational comics you loved as a kid. This one explains algorithm ideas in a fun, engaging way. As you flip through the pages, the colorful illustrations simplify those tricky concepts, making them feel approachable. Yet, there’s a nagging feeling that some of the depth might be missing in favor of appealing visuals.

Each of these sources, with their respective unique style, feels like a different conversation you might have with friends: one urgent and rooted in reality, the second intellectually stimulating, and the third creatively engaging.

One challenge might be thinking about how each of these approaches can be brought together to build a more well-rounded conversation about the ethics of algorithms, or even making step-by-step instructions for somebody very interested in the topic. Maybe starting with a more easy-to-understand, engaging manner to introduce the topic, slowly getting into the rather academic and thought-provoking aspect and finally rounding it up with analysis, laying out plans for future development and providing insights for public policymakers and advocacy groups on how to ensure that the public interest is best served.