Deliberate Practice and School Update

Giving a mock interview in a simulation for my U.S. Congress and Lawmaking Class at the Harvard Kennedy School. (Note, this interview has no ties to the Economist and is a Mock Bill).

I thought I would share the progression I have had in my thesis, some of the obstacles I have had to overcome, and some of the great experiences I have had so far. Producing a thesis is a requirement in the Technology and Public Policy Program at MIT, and I am glad that I have the opportunity to conduct research that could impact this world. I am conducting my thesis on U.S. Artificial Intelligence Policy and Dr. Luis Videgaray is my research advisor. Dr. Videgaray is the Director of the MIT AI Policy for the World Project and Senior Lecturer at MIT Sloan. He has been terrific, and I am excited for what is to come.

My thesis question asks, “What type Artificial Intelligence Policy will allow the U.S. to continue to lead the world in AI innovation while doing it in an ethical way?”. I am in the process of drafting my thesis and I am expecting to release it in Spring of 2023. I have learned a lot about Artificial Intelligence and policy over the past six months. However, I have had to quickly adapt to the fast-moving pace of AI, and the rigorous classes that I have had to take.

Before I came to MIT, I actually never had opened up a python file before. I also no knowledge on AI Policy. Next thing I know, I was expected to build, train, and deploy machine learning algorithms on python. I was extremely out of my comfort zone and had to put in a lot more time than some of my classmates to learn about machine learning.

One of my favorite podcasts that I have listened to is a Freakocomics episode called, “How to Become Great at Just About Anything”. My former wrestling coach at West Point, Coach Ward shared this podcast edition with me, and it has stuck with me for a long time. One of my favorite quotes from the podcast states,

“Deliberate practice involves well-defined, specific goals, and often involves improving some aspect of the target performance. It is not aimed at some vague, overall improvement…

Deliberate practice takes place outside one’s comfort zone and requires a student to constantly try things that are just beyond his or her current abilities… it demands near-maximal effort, which is generally not enjoyable.”

Deliberate practice is something I try to do often at school and in life. Deliberate practice has been the key to success for me. I came into MIT with no knowledge on a lot of these AI topics, and I have had to focus in on specific tasks that make me uncomfortable and force me to grow and learn. Sometimes these specific tasks involve reading books geared towards specific AI topics or trying to code specific algorithms. I am also grateful that I have had great classmates to help me learn and grow along the way.

The video above is another example deliberate practice. I was a little uncomfortable talking about an AI Policy Bill that I have proposed in a simulation for one of my classes. I have learned how to talk about these issues and explain how AI Policy topics As a side note, this interview was taken in one of the best classes I have ever taken –  U.S. Congress and Lawmaking at the Kennedy School.

To conclude, my greatest takeaway so far at graduate school is that I must conduct deliberate practice as much as possible if I want to become great at something. I truly believe that you can become great at anything, as long as you are willing to put in deliberate practice and make yourself uncomfortable. This is how you grow. I am by no means an expert on AI Policy yet; however, I will continue to apply deliberate learning in my life and produce a thesis that will hopefully give great insight on U.S. AI Policy moving forward.

Also, here is the link to the Freakoconomics Podcast called “How to Become Great at Just About Anything”

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