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For this assignment, I used ChatGPT to generate a short blog post about political apathy in the United States. At first glance, the response actually seemed pretty solid. It was structured well, stayed on topic, and covered some of the main reasons people don’t engage with politics, like distrust in government, lack of education, and barriers to voting. If I didn’t know better, I probably could have taken it at face value.
But once I started reviewing it more closely, I realized that a lot of the information was vague. For example, the AI used phrases like “according to studies” without actually citing any real sources. That’s a big issue, because it sounds credible, but there’s nothing there to verify. I had to go in and replace those general statements with actual data from sources like Pew Research Center, Ballotpedia, and the U.S. Election Assistance Commission. That alone made a big difference in the credibility of the post.
Another thing I noticed is that while the AI response was clear, it didn’t really have much depth or personality. It felt very surface-level. I had to rewrite several parts to make the ideas more specific and to better reflect how misinformation and media influence contribute to political disengagement. This connected directly to what we’ve been learning in this module about not blindly trusting information, even when it sounds convincing.
Overall, this exercise showed me that AI can be a useful starting point, but it shouldn’t be relied on without careful review. It’s good for generating ideas and structure, but it still requires human judgment to verify information, add context, and make the content more meaningful. In that sense, it reminded me a lot of what we learned about Wikipedia: it’s helpful, but you have to dig deeper and check the sources.
You can view my full editing process here: [Google Doc Link]
