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
The interdisciplinary nature of this program was felt most for me in the AI talk given to us last week. In that talk, the potential harms and pitfalls of AI did not surprise me, but I did become aware of how much more pressing they are in other fields than in Neuroscience. This summit then became especially important for me as the scope of my project shifted somewhat as I now am still working with confidence but under the scope of attention, and in this broader project, AI is leveraged as a strong tool. By using AI as a tool I was forced to reckon with the broader implications of AI not just within the field of Neuroscience but across all research. I think that the talk given on AI and conversations with other scholars gave me a broader more tangible understanding on just how negative AI can be in other fields.
As you begin your individual research projects this week, do you anticipate any challenges in getting started? If so, what are they?
By far the biggest challenge I faced this week was learning R. For my new slightly altered project, statistical analysis has become all the more important, and R is almost exclusively used for this. While I have the help of my mentor and other lab members, the learning process has been a lot of trial and error. I anticipate that this will continue to be a struggle throughout the summer, but it is one that I hope will aid me in not just this project but future research as well.