Unit 2 Reflection

Unit 2 Reflection

For my Unit 2 project, I focused on artificial intelligence in sports, specifically the balance between data and human decision-making. When choosing an audience, I immediately thought about sports fans, especially people who actually follow teams closely and care about decisions like trades, draft picks, and roster moves. That’s where this topic actually matters. I also based this on real conversations I have with my friends, like Jack Wilkos and Ian Cohen, because we constantly talk about these types of decisions. That made them a strong audience for both my pitch and my project.

Because of this audience, I made specific choices in how I wrote the piece. I avoided overly technical explanations of AI and instead focused on how it impacts the experience of sports. For example, I wrote, “Sports are not just about efficiency or perfect decisions. They are about emotion, risk, and human error.” That line was intentional because I wanted to connect with how fans actually see sports, not just how teams operate behind the scenes. I also used subheadings like “What Fans Actually Think” and “Why This Actually Matters” to make the piece feel more like something someone would choose to read online, not just a paper for class. Structuring it this way made it easier to follow and more engaging for my audience.

In terms of research, I challenged myself to go beyond just finding sources and instead actually engage with them. One thing I realized is that the conversation around AI in sports right now is not about whether AI works, but about how far it should go. Sources like the Forbes article focus heavily on the benefits, especially how AI can “quickly analyze large amounts of data” (Walch, 2024). On the other hand, sources like The Atlantic raise concerns about AI replacing human judgment. This shows that the conversation is really about finding a balance, not choosing one side.

My perspective definitely changed from Unit 1 to Unit 2. In Unit 1, I was more focused on collecting and analyzing sources. In Unit 2, I shifted toward building an argument. I started to realize that even though AI is extremely powerful, it cannot fully capture things like pressure, leadership, or confidence. That idea became the core of my thesis, that AI should support decision-making, not replace it.

The quality of sources on this topic is generally strong, especially from business and technology perspectives. However, one gap I noticed is that there are not many sources focused on how fans feel about AI being involved in decision-making. Most sources focus on efficiency and performance, but not the emotional or human side of sports. That is where I saw an opportunity to add something through my own research.

For my primary research, I reached out to Jack Wilkos and Ian Cohen, who both follow sports closely. This directly connected to my pitch, where I asked whether fans would trust AI to make decisions like draft picks or trades. Their responses helped support my argument. Both were fine with AI being used as a tool, but neither trusted it to make final decisions. One response said it would feel “weird” if a machine had full control. This showed a clear boundary. Fans may accept AI, but only up to a certain point.

I was also able to get feedback on my draft, which helped me understand how my writing was coming across. One comment pointed out that my introduction clearly explained the impact of AI and that I did a good job presenting both sides of the argument. It also mentioned that my use of primary research strengthened my claim. This showed me that my approach was working, especially in making the argument balanced and engaging rather than one-sided.

In terms of the pitch itself, I was successful in getting responses since I sent it through text messages and group chats. This matched the audience I chose because that is how we naturally talk about sports. After getting responses, I followed up by using those opinions directly in my project, which made my argument stronger and more realistic. It also helped me refine my argument, because even people who supported AI still wanted human control in final decisions.

One of the biggest skills I developed in this unit was learning how to actually analyze quotes instead of just including them. For example, in my project I wrote, “If AI is identifying patterns and making predictions in real time, then decision-making is no longer just based on human observation, it is being guided by a system that operates faster and more consistently than any person can.” This shows how I moved beyond just explaining what AI does and instead focused on what it changes. Instead of only describing the technology, I analyzed how it shifts control away from people and toward data.

This approach shows how I began to think more critically about sources.

In my project, I didn’t just drop quotes in, I explained what they meant and why they mattered. For example, when I used the quote about AI being “better than us at divining the future,” I connected it to the idea that prediction is not the same as understanding. This helped strengthen my argument because it connected the source directly to the bigger idea about human judgment in sports.

Beyond college, this skill is also important in real-world situations, especially in business or real estate, which is my intended major. For example, in real estate, decisions are often based on data like market trends, property values, and investment projections, but those numbers do not capture everything. Factors like location feel, neighborhood development, and long-term potential still require human judgment. Being able to analyze information while also recognizing its limits is important when making those kinds of decisions. The idea of balancing data with human judgment is something that applies directly to real-world decisions, not just sports.

Overall, this project helped me improve how I use sources, how I think about audience, and how I structure an argument. It also made me think more critically about how technology is changing not just industries, but experiences that people care about.