In Dr. Rossi’s American Studies class, “American Experience,” we were tasked with selecting a relevant issue related to American democracy and developing a strategy to find creative solutions to this problem.
In this article, we want to inform our classmates at Fisher how and why this self-proclaimed “tool” currently impacts and will continue to impact our daily lives in ways that aren’t necessarily ideal.
We gathered dozens of credible sources and conducted an interview with Fisher’s Dr. Michelle Flood (Media and Communication / AI Literacy) to break down four main issues related to artificial intelligence (AI) and how it can affect Fisher students.
MISCONCEPTIONS:
According to an informative piece on the Bipartisan Policy Center website, one common misconception about AI is that all AI models are the same. However, there are many different models, some of which include machine learning, deep learning, generative AI and large language models.
Another common misconception is that AI is a new technology. Although generative AI was revealed to the public in 2022, many AI algorithms have been around since the 1950s.
It is frequently believed that AI does not have bias. However, the data that is fed to the AI model can replicate bias due to the information it has been trained on. Moreover, AI has an information bias; someone generating a prompt can receive biased information, further increasing the risk of harming individuals.
Dr. Flood raised a similar concern in our exchange. She explained that large language models often fall into “confirmation bias” and are “trained to agree with and validate users’ opinions and stances.” In other words, AI is not always giving users a neutral answer. It may instead be shaped by what the system predicts the user wants to hear, which makes bias an even bigger concern.
Lastly, another misconception is that AI systems work like a human brain. According to a journal article from Oxford Academic by Alain Goriely, the brain has roughly 86 billion neurons that communicate signals, whereas AI uses the data it’s been trained on to weigh information and create a response. AI has no emotions or past experiences to inform its decision-making the way that a human does.
ENVIRONMENTAL IMPACT:
Artificial intelligence is often discussed as a digital tool, but its environmental impact is rooted in the physical resources required to operate it. Our research shows that generative AI depends on large data centers that consume substantial amounts of electricity and water. As AI systems become more widely used, demand for computing power continues to rise, placing greater strain on energy grids and increasing carbon emissions.
One of the clearest concerns is electricity use. Training and running large AI models requires enormous computational power, and that power comes from energy-intensive infrastructure. According to the U.S. Government Accountability Office’s 2025 report, U.S. data centers accounted for about 4% of the nation’s electricity demand in 2022, and that figure could climb to 6% by 2026.
On a global scale, data centers already make up a meaningful share of electricity consumption, and that total is expected to grow as AI implementation expands. Water use is another major issue. Data centers rely on cooling systems to prevent servers from overheating, and those systems can require large amounts of water. In some areas, this can add pressure to local water supplies.
The environmental cost also extends beyond energy and water. Expanding AI infrastructure requires hardware production, transportation and raw materials, including rare earth metals, all of which carry environmental consequences. This shows that AI is not environmentally neutral. Although it exists in digital form, it depends on real-world systems that consume energy, water and materials at a growing scale.
COGNITIVE DECLINE:
AI can contribute to a decline in critical thinking, independent reasoning and creativity when people begin to rely on it too heavily. That argument is not presented as a medical diagnosis of cognitive decline, but as an erosion of the mental habits people develop by thinking, questioning and creating for themselves.
A Cardiff University piece argues that thinking for yourself helps build understanding, strengthens a person’s ability to respond to new information and cultivates intellectual virtues such as curiosity, humility and perseverance. In that sense, outsourcing too much thinking to AI risks weakening the very skills that come from working through problems independently.
Harvard’s Graduate School of Education makes a related point, saying “students must be taught to think critically and creatively in a world increasingly shaped by artificial intelligence, misinformation and fake content.” That supports the idea that AI can undermine judgment unless users actively practice evaluation and inquiry.
Dr. Flood warned against using large language models as a search engine. She said the output is informed by what the model predicts the user wants to receive. That raises a serious concern for students because a tool that mainly affirms its user may discourage the kind of questioning and skepticism that real learning requires.
An article written on the U.S. Army site by CPT Garett H. Pyle argues that overreliance on GPT may reduce brain activity and erode creativity and critical thinking, while an Oxford ethics piece warns that AI can threaten human creativity by replacing opportunities for people to produce original work themselves. Looking at this evidence together we can see how AI may be useful as a tool, but when it replaces human effort rather than assisting it, it can weaken the parts of the brain that support intellectual growth.
HUMAN CREATIVITY:
We see a decline in human creativity due to the use of AI. Students use AI to write their papers, and businesses use AI instead of graphic designers to make logos, advertisements and more. The commercialization of AI has led to businesses using it to create designs, but now people are recognizing that these are AI-generated designs and may be less likely to work with them.
Dr. Flood offered a more balanced way to look at this issue. She said large language models “can certainly aid in creative projects and processes,” but the outputs they generate are limited by existing coding and by what is already available in digital spaces. That distinction matters. AI can assist with creativity, but it is still drawing from what already exists rather than creating from lived experience.
Suno is an AI tool for creating your own music based on a prompt. The CEO, Mikey Shulman, said, “It’s not really enjoyable to make music now… It takes a lot of time, it takes a lot of practice, and you need to get really good at an instrument or really good at a piece of production software. I think the majority of people don’t enjoy the majority of the time they spend making music.”
As someone who has spent countless hours on music production software to practice my craft and keep getting better at it, I would say that I enjoy making music. Don’t get me wrong, it can be stressful, but an AI prompt could never match exactly what I hear when I’m producing music. There are so many different pieces of a digital audio workstation, also called a DAW. Some popular DAWs include Ableton, Logic Pro, FL Studio and even BandLab, which is free. Dissecting the pieces of these DAWs is what makes music fun. I enjoy finding new plugins to change the sound or to add effects that I can control myself.
CONCLUSION:
What’s most important for us is not for Fisher students, or anyone else, to suddenly turn on a dime in their viewpoints on AI; it’s that we simply want you all to think. Think about what we are OK with. Think about how this may affect your loved ones and your future loved ones. Think about how it may affect you.
Dr. Flood made clear that her concern is not simply that students are using AI, but how they are using it. She said it is “disheartening to see students outsource their learning to a machine,” especially when students are capable of producing stronger and more thoughtful work on their own. Her perspective helped us see that, as Fisher students, this issue pertains to learning, judgment and what we may lose when we rely on AI too heavily.
Take charge of your life, and be proud of your own capabilities. The more research we do on this topic, and every other topic that populates our social media feeds day after day, the more we understand it. To loosely paraphrase Christopher Nolan’s writing in “Oppenheimer:” We won’t fear it until we understand it. And we won’t understand it until we use it.
