By: Jared Gudnason

October 25, 2025

Metro State’s Master of Liberal Studies 620 involves the broad utilization of generative artificial intelligence. Unbeknownst to me, ChatGPT has only existed since 2022, simply for the reason that I don’t choose to access it. Approximately two weeks ago, two cohorts and I gave a presentation via Zoom (an unideal platform) to the rest of our class. I was aurally nervous throughout because I’d never given an arguable speech on something I’d researched minimally. It was also corroborated by the fact that our presentation template concerned eight bullet points from a Stanford rubric. I addressed four points, and my to-remain-unnamed cohorts covered the rest. One cohort covered a wholly unfamiliar topic, Datafication.

In our digital age, generative AI is very much inarguably self-sufficient. While that sentence is confusing, it’s written because after querying a search via an AI, it free-associates with the search verbiage. What’s of particular concern is if this is an overwhelming case and exponential, it therefore informs a mass translucency via just simple generative AI accessible-ness. Arguably, people show a tendency to be transparent when seeking specificities, especially with regard to the use of the internet. I digress. If a human-originated, inarguable software data system possesses the ability to free-associate unreliably, it understandably self-mitigates. Australian national Leon Furze, who published an article within the last five years, argues pointedly that if human design can subvert credibility via exploitation, dissemination of untruthful media is fully possible.

So, the next point: how can societies ethically adapt to genAI? Professor Maha Bali of Egypt’s American University argued that humans, especially in the digital age, take displayed knowledge at face value, especially regarding a search engine (AI or otherwise). She makes the point that individuals need to be critical of a generative AI with the following: “Just because they are older and more experienced does not mean they know more about AI, really.”

Bali references writer Ed Zitron as well. He addresses the double standard facing genAI skeptics and proponents. He goes so far as to note that Meta Platforms is restructuring its genAI division, including downsizing, currently for the fourth time around. Referentially, Furze addresses the innate tendency of biases via algorithms. To put it in actual regular language, this possesses the ability to present wrong results and can lead to discrimination. He demonstrates this as a form of inherent bias, which is arguably where the line of human autonomy and an AI gets blurred. If preference toward or against something like ChatGPT is discussed, either side of the coin presents factual biases.