Utilizing GenAI: Meet My Graduate Student

As a graduate student, I helped a PhD student with some research for his dissertation. We fell into a bizarre form of brainstorming. He would start with a problem statement. I would break down the problem statement and begin reciting different ways we could solve the problem. Most of the ideas were absurd and unhelpful, but about one in ten provided the PhD student with an avenue to explore. He knew the math; I knew enough to be helpful, but not enough to be bound by the expected rules usage of the math. Today, I am the PhD student and GenAI is my graduate student.  

I work at a small company. We are constantly busy moving between tasks. Sometimes, no one has the time to listen to my obscure ideas. I start with a problem statement: say writing a blog post. I know what I want to write about, but I need some information about the topic. Thanks, GenAI, it's right here. I throw out about 80% of what it gives me. (Apparently, GenAI is a better assistant than I was.) I refine and debate the information it has provided me. Once I have diagrammed the argument that I’d like to make, I give the prompt to my graduate student to write a draft. GenAI gives me an 80% solution. Coincidentally, this article is an accurate example of this process. I’ll hand it over to my graduate student to more fully breakdown this process...  

Prompt and Response: Initiating the Dialogue  

Begin by presenting GenAI with a prompt or question that is closely aligned with the problem at hand. In this role, GenAI acts as a receptive learner, absorbing the essence of your inquiry. Just as you would instruct your graduate assistant, instruct GenAI to provide a response, and it does so with its own unique perspective and insights. Much like a promising research assistant, GenAI's response serves as the catalyst for further exploration.  

Exploration and Expansion: Venturing into Uncharted Territory  

Much like a bright graduate student eager to impress, GenAI can expand on specific aspects or concepts within its response that intrigue you. It doesn't just stop at one idea; it explores different directions and perspectives, shedding light on hitherto unexplored angles or dimensions of your problem. This expansion of ideas echoes the inquisitiveness and zeal of a dedicated graduate assistant, ready to explore new avenues of knowledge.  

Challenge and Refine: The Academic Exchange  

No graduate student's work is exempt from scrutiny, and GenAI is no exception. Here, assume the role of a critical thinker, much like an experienced professor guiding a graduate student's research. Challenge GenAI's responses, seeking to unearth any flaws or inconsistencies in its reasoning. If you identify areas that need improvement, you instruct GenAI to justify its logic or suggest enhancements. This rigorous exchange mirrors the discourse and iterative refinement characteristic of mentor-student interactions.  

Synthesis: Crafting Brilliance Together  

Merge your collective insights, creating a symphony of ideas that transcend individual contributions. This act of synthesis is akin to a professor and a graduate student combining their ability to generate novel and unexpected solutions. By melding multiple AI-generated ideas or concepts into a single, coherent concept, you achieve a level of creativity and innovation that neither could achieve alone.  

Okay. I am back.  

As you can see, my graduate student has high opinions of its abilities, and that is after I removed quite a few filler sentences. Let’s be honest, I did not write “creating a symphony of ideas that transcend individual contributions.” Nor am I capable of writing such an absurdly ornate sentence. But, no grad student is perfect.

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