AI-generated images and videos are changing the way we create and interact with digital content, but this can raise ethical concern that must be addressed to ensure responsible use. One of the most pressing concerns of AI generated content is the potential for misinformation and the creation of realistic fake images or videos that can be used to deceive, manipulate public opinion, or damage reputations; these are known as deepfakes. There was a time in 2020 during the pandemic era when many social media posts (specifically on X/Twitter) were deepfakes that portrayed celebrities in inappropriate situations typically surrounding nudity. This not only threatens individual privacy and safety but also undermines trust in media and information sources.

Additionally, the data used to train AI models often reflects existing societal biases, which can result in outputs that reinforce harmful stereotypes or exclude marginalized groups. Privacy is another major issue, as AI systems may use images of real people without their consent, leading to the creation of exploitative content. Intellectual property rights are also complicated by AI content; it raises questions about whether ownership and fair use are considered when AI models are trained on copyrighted works.

To address these challenges, there should be implementation of clear guidelines; such as labeling AI content, ensuring diverse and representative training data, obtaining consent for the use of personal likenesses, and developing regulations that promote transparency and accountability. While AI-generated art can democratize creativity and provide valuable educational and accessibility tools, its use must be guided by ethical principles that prioritize transparency, fairness, and respect for individual rights, ensuring positive contributions to society.

This week’s readings got me thinking: How much is AI not just in our classrooms, but also in our future careers? It feels like we’re navigating a brand-new world, and the lines haven’t been drawn yet.

One area that stood out from the paper “Augmenting the Author” is the issue of transparency. The authors highlight the “depth of transparency in researchers’ access and utilization of AI” and the concerns this raises about the “reliability and credibility of AI-generated text.” This really resonates when we think about assignments or professional reports. How do we know if the work is truly our own or mostly AI-generated?

A key grey area lies in defining authentic authorship and intellectual contribution when AI is involved. For example, in one of my previous classes, an alumnus from Pfizer told us that they sometimes use AI to generate mock drug syntheses, which they then refine and test. I found this interesting in relation to this week’s discussion, but I didn’t get a chance to ask about it at the time AI’s usage and credited contributions can be a touchy subject.

As the researchers point out, there’s a concern that reviewers (or instructors) might end up “validating AI’s work” instead of the author’s. Moving forward, clear guidelines emphasizing transparency about AI use will be crucial. We need to foster a culture where acknowledging AI assistance isn’t seen as a weakness but as a step toward ethical and responsible innovation. 

links:https://dspacemainprd01.lib.uwaterloo.ca/server/api/core/bitstreams/40009604-deb5-4250-a341-ceccb3c6561c/content

Arriagada use terms like novel and valuable to define creativity. This is true and interesting, especially considering everything I learned this week—specifically around how AI-generated art gives off a sense of emptiness. I would now define creativity as the unique ability to move the audience with one’s work.If I had to challenge any part of the definition, it would be the new aspect. In class, we spoke about how even Shakespeare’s work was drawn from other traditions, and how rock music was drawn from blues. My mother always says, “There’s nothing new under the sun,” which means everything draws on inspiration from the old or is a manipulation of it especially nowadays.

I asked Perplexity to “write a poem that rhymes,” a very generic prompt, and it produced A Journey Beneath the Sky. Then I asked it to take that same poem and, using Shakespeare’s voice, rewrite it as a sonnet.

I really do not know what to say about this because I feel like elements of the original poem were lost, and I ended up with a completely different poem in sonnet form, full of “thy” and “thou.” Interestingly, the second time around, it explained how the sonnet structure “mirrors the Bard’s themes of cosmic wonder, mortal limitation, and the interplay of light and shadow.”

To me, this is unsatisfactory. I think AI can be creative, but it requires extensive prompting—and even then, it feels soulless. It can be used as a tool, not the author and finisher of an entire artwork

Boden, Margaret A. “Creativity and Artificial Intelligence.” Artificial Intelligence, vol. 103, no. 1, Aug. 1998, pp. 347–56, https://doi.org/10.1016/S0004-3702(98)00055-1.

Arriagada, Leonardo, and Gabriela Arriagada-Bruneau. “Ai?S Role in Creative Processes: A Functionalist Approach.” Odradek. Studies in Philosophy of Literature, Aesthetics, and New Media Theories, vol. 8, no. 1, 2022, pp. 77–110, https://philarchive.org/rec/ARRARI-2.

This week in class, we learned about the concept of prompt engineering, which is basically instructing AI with prompts to obtain a specific outcome or train it. I personally think that with the evolution and common use of AI, the name could be changed to something simpler, like instructional design.

As part of our reading, I learned about things I already do when using AI and how they have pre-existing names, like Fact Checking and Alternative Approach. One technique I haven’t tried as much is Persona because I have a hard time believing that the AI can conceptualize being put in someone else’s shoes. Another technique I find hard to use is Flipped Interaction, where the initial prompt makes the LLM ask you questions to further aid the outcome of the initial prompt.

I think the whole point of Persona is to give the LLM some perspective—to help the AI step out of its virtual world into the real one. For example, today in class, I picked the blog Advertisement prompt and asked ChatGPT for tampons. The prompt said: “Write an advertisement blog about tampons for people who enjoy using pads more.” It gave me a decent blog with subsections, each explaining a key point about how tampons are better, like mobility, among other benefits. But since I was trying to sell to a specific demographic, I used Persona and gave this new prompt: “Now I am the editor of the blog who also happens to be a woman. Try rewriting the full blog using my woman voice (mine) to convince fellow women to use tampons.”

Below are images of the introductory paragraphs for both prompts.

After persona the blog come it the from of a story/ testimonial about tampons which more engaging to reads because now other woman can relate because it comes from lived experience.In the end will Persona make LLM’s understand humans more no. but it makes the outcome of prompting so much better.

Links

https://www.dre.vanderbilt.edu/~schmidt/PDF/PLoP-patterns.pdf

https://learnprompting.org/docs/advanced/zero_shot/role_prompting?srsltid=AfmBOoqFo_yPAvOA2EyQGnIedqywHzuAOkLo3ZORjURMLI6PMwBD4zd9

I think that one of the biggest misconceptions is that AI is ChatGPT. While ChatGPT is indeed an impressive large language model developed by OpenAI, it represents just one facet of the broader field of artificial intelligence. Due to the popularization of ChatGPT, some people have associated the totality of AI with ChatGPT, forgetting that AI has been used in our lives years before ChatGPT. AI is not a recent invention, as its foundational ideas emerged between 1950 and 1955, with Alan Turing introducing the Turing Test in his 1950 paper “Computing Machinery and Intelligence,” Arthur Samuel creating a self-learning checkers program in 1952, and John McCarthy coining the term “artificial intelligence” during a seminal workshop in 1955. Aside from the fact that it is not a new concept, it is very much ingrained in our lives and affects our day-to-day activities. AI is used in online shopping through custom product recommendations, customer service chatbots, facial recognition in security cameras, and personalized music playlists (i.e., Spotify).

Because of the lack of awareness of how it affects everyone’s life, it leaves room for its advancements to remain unchecked. This leads to several problems in privacy, bias, sustainability, ethics, among others, which is dangerous. This kind of ties in with my group’s assigned reading, which highlighted critical flaws in deploying “one-size-fits-all” facial analysis systems for high-stakes applications like surveillance or medical diagnostics. It spurred industry improvements – IBM later reduced its darker female error rate to 3.46% through algorithmic updates.

In some academic and research settings, AI is being talked about, and conversations are being held about how we can use yet restrict AI so that it does not become a tool to the detriment of society.

Sources

1.https://carlsonschool.umn.edu/graduate/resources/debunking-5-artificial-intelligence-myths 2.https://www.tableau.com/data-insights/ai/history#ai-birth

Hello, I use the She series. I am a Chemistry major, and my hobbies include bead-making, singing, and crocheting. I am very interested in cosmetic and skin-related content, as well as overall lifestyle and fashion topics. I am taking this class to see if it improves my dynamic with AI. Will I appreciate it more? Will I use it less? Will I be able to instruct it better or train it well?

This is a photo of a place where are feel the most myself and the most relaxed.

I think AI plays a significant role in everyone’s life, whether they use it directly or not. For years, companies have been using AI to scan résumés during the job application process. So, in this case, you may not be actively using AI, but it is still directly affecting you.