• Last week the trainings and discussions we had cut across the disciplines. How does the interdisciplinary nature of this program, the fact that students are focusing on such a diverse range of projects, help you think about your project and/or your academic interests more broadly?

Observing the overlaps and interactions between each of our unique projects has given me a greater appreciation for the innately interdisciplinary nature of academia, learning, and the world in general. My project, which covers the spread of disinformation through AI in Russia, combines skills and knowledge in artificial intelligence, coding, statistical analysis, international relations, journalism, and geopolitics in one project. As such, it has been fascinating to interact with the mentors who have been assigned to me: Emily Schmidt, the librarian specializing in journalism; Timothy M. Frye, my faculty mentor with a specialization in Russian politics; and Nick Deas, the PhD student with a vast background in research at the intersection of AI and politics. In my meetings with these individuals throughout the week, I have developed a greater appreciation for the inextricable nature of STEM and the humanities in any academic endeavor and the need to lean into all fields, rather than writing off one or the other, when pursuing research. The breadth and depth of knowledge these three individuals have reinforces the idea that there is no "superior" field of study or expertise -- be it STEM or the humanities -- and each academic pursuit requires a delicate balance between technical, quantitative skills and creative or critical thinking.

• As you begin your individual research projects this week, do you anticipate any challenges in getting started? If so, what are they?

This week, I have truly narrowed the topic of my research from AI disinformation broadly to looking at two specific and prominent Russian AI development companies, contrasting their chat bots and correlating their levels of bias with their involvement with the government. The biggest hurdle I had imagined a week ago was precisely this process of narrowing down the topic, given the breadth and vast uncertainty of this rapidly evolving field and my desire to tackle all of it in one project. Luckily, having had discussions with a number of experts in these fields and noting what was most viable for a college student to do in one summer, I have settled on a topic that is both accessible in recent journalistic sources, academic literature, and AI development news. From here, I anticipate my next challenge to be implementing the use of Python code into my project, which is outside of my comfort zone as a generally humanities-focused scholar. However, I am grateful for the guidance of my assigned and independently-found mentors, as the resources they have provided are giving me a solid foundation of knowledge to combine coding with humanities research. In the next few days, I will largely be self-teaching, though after that I hope to apply it to my analysis of statistical datasets created by researchers studying bias and censorship in LLMs across the world.