I think many of the ethical considerations surrounding AI-generated images and videos are closely tied to the discussion of creativity we had in class. Reflecting on the reading about ChatGPT generating images in the style of Studio Ghibli, it raises concerns about copyright and the importance of giving credit to original creators. As someone who experimented with generating images in the Studio Ghibli style, I found it fun and understood why it has become so popular. However, from a creator’s perspective, it would feel unfair to see AI replicate your artistic style and produce numerous images for free and potentially without acknowledging the original source. It’s important to recognize that these works of art require significant time, effort, and creativity to produce, and they should not be so easily used by AI and distributed to others without proper consideration.

Source: The artifact isn’t the art: Rethinking creativity in the age of AI

For this extra credit prompt, I read Alfredo Deambrosis article titled “The 8 Ethical Concerns Raised by AI Images and Video.” We all know Artificial Intelligence (AI) as a cool tool that’s used to enhance our brains with thinking and learning, or so we think. A big issue with AI imaging and video creation is training. Important internet figures like athletes and celebrities, often find random videos or images of themselves online that are made by AI, and do not reflect good upon them. These AI systems learn from these images online, spreading or making them in the wrong way for people to see. This also reflects upon privacy, which is a big topic of our class and this article. It seems as if AI is violating these rules of privacy.

My future job is something I’ve wanted to revolve around sports media or broadcasting. Photography is a large part of the media aspect, as many sports organizations have their own photographers who bring in tons of money each year for the team. With AI now being able to generate images faster and more efficiently, maybe the sports world could soon move away from hiring professional photographers/videographers. This could put people in this field out of a job, and they are left trying to find something else to do. This goes back to when the article and our class refer to AI being unethical, because they may be putting many jobs at risk in the future.

Many users see things online and instantly believe them without knowing the true backstory. Artificial intelligence can publish fake or biased videos/pictures, which is scary. This makes AI unethical, and it can cause people to believe false propaganda that is only up for clicks and views. I hope some rules and regulations will follow in behind this, and that hopefully more serious laws about artificial intelligence publishing fake content become more intense. Overall, I believe there are many unethical features while using AI, I’m sure someone could name at least five off the top of their head. The future is hard to predict, and AI will only continue to get smarter and smarter, which is troubling to consider.

Cite: Imgix. “8 Ethical Concerns Raised by AI Images and Video.” Imgix Blog, https://www.imgix.com/blog/8-ethical-concerns-raised-by-ai-images-and-video. Accessed 30 Apr. 2026.

AI image generation is honestly wild. It’s fast, it’s fun, and once you start playing with it, it’s kind of hard to stop. But these models are all being trained on billions of images scraped from the internet such as your photos, artists’ portfolios, news footage, and usually without anyone’s permission. It’s not about that AI can copy a style; it’s that it can swallow someone’s face, their work, and their memory without asking, then spit it back out as something “new.” That’s not innovation, that’s extraction.

And it gets way worse when people use this tech to generate images of someone who’s dead, such as like Kobe Bryant——honestly it’s kind of shame because it was a trend in China. I totally understand that people miss him, but Kobe can’t consent to having his likeness dragged out of old footage and turned into a digital being because he is dead. It’s super disrespectful.

So how can we actually fix this? I think there should be a regulation for data that used to train AI, as we discussed a lot. First, these models need to be trained on opt-in data, not just everything scraped off the web. Second, every AI image needs a permanent watermark or label that can’t be cropped out, and platforms need to actually enforce it. And third, there should be a hard rule: you don’t generate identifiable images of real dead people without explicit family consent. So we need to stop treating “we can do it” as the same thing as “we should do it.”.

Before this week, I assumed generative AI would either feel like a shortcut or a threat to originality. What surprised me instead was how useful it can be without actually replacing the creative process. When I asked it to write a poem in the style of Edgar Allan Poe, the result was convincing on the surface, but it did not feel fully alive. That gap made me realize AI is better suited as a tool for expanding perspective than as a substitute for creativity.

To me, creativity is the ability to transform personal experience, emotion, and interpretation into something meaningful and original. It is not just about making something new. It is about making something that reflects a point of view. This builds on Mihaly Csikszentmihalyi’s idea that creativity involves meaningful contribution, but I think perspective is just as important as contribution. Without a perspective, creative work feels interchangeable.

Here is a short excerpt from an AI generated poem I received:

“A tapping rose — a hollow sound, like knuckles made of bone,
As though some soul beneath the ground sought solace in my home.
I dared not breathe; my heart became a prisoner in my chest,
For in that knock I heard my name, in sorrowful unrest.”

What made this interesting is how well it imitates Poe’s style. The dark imagery, rhythm, and tone are all there. But it feels more like a blend of familiar patterns than a unique expression. This connects to the article The artifact isn’t the art: Rethinking creativity in the age of AI, which argues that AI can generate convincing outputs without engaging in the deeper human processes like struggle, ambiguity, and lived experience that shape real creativity. In that sense, the poem is stylistically creative, but not deeply original.

Because of this, I would use AI to augment my creativity by helping me explore different perspectives rather than replacing my own voice. For example, if I were writing about a theme like grief, I could ask AI to generate interpretations of that theme from different angles, such as historical, psychological, or even from different fictional voices. This would expose me to ideas I might not have considered, almost like having multiple brainstorming partners. Then, instead of copying those ideas, I would filter and reshape them through my own experiences and intentions.

The benefit of this approach is that it pushes me beyond my default way of thinking. It helps me see blind spots, challenge my assumptions, and experiment with styles or viewpoints I would not normally try. However, the risk is that I might start leaning too much on AI generated perspectives and lose confidence in my own instincts. There is also the danger of blending too many external ideas and ending up with something that lacks a clear, personal voice.

That week definitely shifted how I thought about AI and creativity. I did not see AI as something that replaces creativity, but as something that can expand it, especially by offering new perspectives. At the same time, it made me more aware that creativity ultimately depends on human input. Our experiences, interpretations, and willingness to refine ideas are what give work meaning. AI can suggest possibilities, but the meaning behind the work still has to come from me.

One issue related to generative AI that I think does not get enough attention is its impact on the environment. A lot of people use AI tools every day without realizing how much energy and water are needed to keep them running. Even though it feels like you are just typing into a simple chat box, there are large data centers behind it that require constant electricity and cooling to operate.

A good example of this is how large AI models are trained. They process huge amounts of data using powerful computers that can run for weeks at a time. These data centers use a lot of electricity and also need water for cooling so the systems do not overheat. In some areas, this can put pressure on local resources, especially during times when energy or water demand is already high.

This matters because AI is becoming more common in everyday life, whether it is for school, work, or basic online searches. If we do not pay attention to the environmental cost, the convenience of AI could come with a serious downside. One solution is to improve how efficient AI systems are and to use cleaner energy sources for data centers. People can also be more mindful about when and how often they use AI tools so that they are not relying on them unnecessarily.

Going forward, I plan to use AI as a tool that can help improve my effort instead of replacing it. The main problem is that AI makes everything easier but if you rely on it too much, you can lose your ability to think and actually learn. For example, if I use AI to write my entire paper, I might get it done faster, but I won’t really understand the topic or be able to explain it fully. A better way to use it is by doing my own work first, then using it to fix certain things or give a better idea based on my work, that way I’m still doing the thinking and learning, and Ai is just helping me. I think it’s important because AI is becoming part of school, jobs, and something people use every day, so deciding not to use it isn’t a realistic option anymore and the real focus should be on how we are using it. My solution would be to always do it yourself first and use AI as a tool for feedback.