Oct 19

Assignment 1 – Proposal

Proposed Title: ChatGPT and Human Communication: Convenience, Agency, and Authenticity
For my Critical AI Analysis Paper, I would like to investigate the concept of ChatGPT as an AI and its potential influence on humanity’s ways of communication. The tool can be used to produce emails, create content for social media, compose essays, and achieve other communication-related goals. The technology has the capacity to make the lives of its users easier and their expression of thoughts and ideas more effective. Yet, such a tendency raises critical questions regarding the role of AI in human interaction and the authenticity of information and ideas delivered via such technology.
My paper will focus on the ways ChatGPT can affect the decision-making process of its users and the potential of the technology to limit the authenticity of human interaction. I aim to achieve a balanced view on the chatbot’s capabilities and its usage in cases where human power, creativity, and independence can be beneficial. Moreover, I intend to provide a list of concerns that humanity should consider when an AI tool has the power to shape and direct communication between people.
I would like my paper to investigate whether ChatGPT is a positive addition to humanity’s capacity to express itself or a challenge that can harm the individualism of ideas and the authenticity of communication as a whole.

Oct 16

Thoughts on Reading 4 and Vibe Coding

On a complete converse from the last pair of pieces. The reading we have introducing vibe coding is actually why I an not an AI dooms-dayer to the core. I have been actively and extensively using AI since I could essentially beta test GPT. In more recent times I have been using LLMs (and much of this will replicate into my AI essay for the end of this month) for doing extensive coding work. Some of it just for fun, most of it to build a concentrated community media server and archive for myself and my music scene friend. All of this code arguably fit under the umbrella of vibe coding. I have enough coding background that I am capable of auditing a lot of the work that these models do, which is very important for the scope of the projects, but a lot of it is just “I have an idea, how can we execute”.

The ability for this technology to become a tool of fracturing and power concentration I feel like it can just as much do the opposite: build and encourage community and creation. I could not craft an extensive media server to replace Netflix and Spotify and be functionally equal, and in some ways arguably better, without the use of these tools. With things like Ollama and Stable Diffusion, we can even sandbox these tools away from the big 5, granted they aren’t as capable as a Claude Pro account, but we still have the tools to develop like we have personal development teams and that is extremely powerful. The possibility of a proliferation of viable alternatives to mainstream platforms and applications  are more available than they have ever been (just look at the recent boom of really amazing and bizarre audio plugins, its like a digital version of the noise table days in the early 2000s), it really comes down to whether we intend to take advantage of that or not. We can build too, we can build cooler, and we can build more.

Also, even if not for the sake of revolutionary acts, like the article itself implies, its just fun. So, why not?

Oct 16

Readings Three: On Turkle and Chiang

These readings present two overlapping crises of the current AI moment, both of which have been on my mind a lot lately. With character.ai being sued into bankruptcy because of the multiple cases of harm resulting from engagement morphing into addiction for its users, you can easily see exactly what Turkle warns of in her piece about the breakdown of the empathetic order that connects an individual to themselves and then to others and extending out to the larger society as presented by Thoreau’s three chairs of a virtuous circle.

Compound this with the second reading on LLMs being compression agents for the whole of the internet, or arguably, all information that can be datafied, it becomes increasingly more bleak. One of my biggest fears about the very near future is the disintegration of anything that could be referred to as a consensus reality.

This isn’t a new problem, Meta has been facing lawsuits and governmental crackdowns and hit pieces for ages based on the way they essentially create a polydisperse foam of reality bubbles across their social platforms but something about the way LLMs can isolate and fabricate feels so much more troubling because we have seen it help write suicide notes and walk through instructions. Not that people don’t do these things but at least there is a person, or persons, to be held accountable not just a black box of question marks. I have watched AI take a PDF I had given it to extract text for a speech reader, instead spit me back a vaguely incorrect and conceptually deflated version of that text in which I had only caught it by accident. I have read recently in the case the AI giants are fighting against the major news organizations the claim that they aren’t stealing because AI is an aggregate that offers a legitimately competitive platform for news consumption, so much so that it is now slowly rising as the number one way people access information about the world, historically and in real-time.

This is a very damning thought. That not only is AI offering a tailored distillation of reality on an individual basis, that has a high risk of being a total fabrication, it is doing this at the complete detriment of any kind of shared social externalities. This could make a trillion tiny little independent worlds with no seeming crossroads. This is extremely concerning when there is a concentrated group of very wealthy and powerful people who sit atop these industries, believing in a neo-monarchic rulership that all tend to agree on a version of a shared reality despite the rest of us. Even if that shared reality feels like something out of a deeply dystopian science fiction novel.

Oct 13

Elyas Obad: Thoughts On All Readings 10/08/2026

I found Chiang’s comparison of ChatGPT to a blurry JPEG interesting because it explains how AI can produce information that appears accurate while leaving out important details. I think this raises a bigger question about how much people actually understand the information they receive from AI. Personally, I use ChatGPT quite often, not just for schoolwork but also when I am alone and need advice about decisions in my life. Sometimes I find myself asking ChatGPT questions that I would normally ask another person because it gives me an immediate response. However, Chiang’s reading made me question how much I should trust those responses, especially when they concern personal decisions. I agree with his argument about writing because I think relying too much on AI can prevent people from developing their own thoughts. At the same time, I still find ChatGPT useful because it helps me think through situations, even if I don’t always agree with its answers. As for, Turkle’s reading, it felt more personal to me because I realized how much I rely on technology when I am alone. I often use ChatGPT to talk through situations in my life, especially when I am unsure about a choice I need to make. Sometimes it feels easier to ask AI for advice because I can explain something without worrying about being judged. However, Turkle’s discussion about solitude made me question whether I am actually spending time reflecting or simply replacing quiet moments with another form of conversation. I agree with her argument that people need time alone to understand themselves, but I also think technology can sometimes help people organize their thoughts. What concerns me is the possibility of becoming too dependent on ChatGPT for personal decisions instead of trusting my own judgment. Her reading made me realize that being alone and being comfortable with my own thoughts are not necessarily the same thing.

Oct 13

Proposal

Elyas Obad
09/27/2026
Jonah Brucker-Cohen

          For the Critical Analysis paper, I would like to analyze the inherent bias within the AI platform, ChatGPT. ChatGPT is a large language model (LLM) developed by OpenAI that uses large amounts of training data to generate human-like responses. Although ChatGPT is often viewed as a neutral source of information, its responses may reflect biases found within its training data and the computational processes used to generate language. As ChatGPT becomes increasingly integrated into education and everyday research, questions arise about whether the information it produces can ever be completely objective. This paper will examine whether bias is simply a result of human influence or an inherent characteristic of how ChatGPT processes and generates knowledge.

 

Oct 10

Reminder – there is no Class on October 13, our next meeting will be  October 20

This is a reminder, there is no Class on October 13, our next meeting will be  October 20…

Jonah

Oct 08

Week 4 Readings

Chiang, ChatGPT Is a Blurry JPEG of the Web – I really liked the blurry JPEG example Chiang used because it made his idea so much easier to understand. A JPEG can look clear while losing information and Chiang compares this to how ChatGPT can give us a clear answer that is not always accurate. I was also very surprised that AI can sound confident even when it creates something that was not in the original information. This made me realize how important it is to check information instead of trusting an answer when it sounds good. I also found Chiang’s point about writing very interesting. If people use AI to write everything they might miss the chance to practice their own ideas. I agree with him because writing can help people discover what they think. I still think AI can be useful but people should use it as a tool, not as a replacement for thinking.

Turkle, Reclaiming Conversation – Turkle’s reading made me think about how phones can change conversations. I agree that technology can make people less focused on others. I found the three chairs interesting because it connects being alone, talking with friends and being part of society. Turkle explains that solitude gives people time to understand themselves and that can help them understand other people. I think this matters because people fill those quiet moments by checking their phones. I was also surprised by the idea that “surfing the internet” is not the same as daydreaming. I usually think of both as quiet time but Turkle shows that they can have different effects. Her reading also made me question how often people use technology when they are just bored or uncomfortable being alone. I agree that technology is not automatically bad. People just need to know when to put their phones away and give someone their full attention.

Oct 06

Reminder – Next In-Person Class Meeting – October 20

Hi Class – we are not meeting in person until October 20th  – Please use the time to work on your papers!

Sep 30

September 29th Reading Reflections

Kate Crawford’s NY Times article, “Artificial Intelligence’s White Guy Problem,” accurately describes the lack of representation currently being faced within the white male-dominated tech industries of today. These machine systems are being built with questionable ethical standards, creating biased answers as these systems replicate and reproduce the ideas and information they were originally fed, under the guise of advanced intelligence and the creation of these technologically revolutionary systems. An example can be found through the usage of widely used software within the criminal justice system, which is 2x as likely to flag black defendants for the possibility of committing (future) crimes. Automating this kind of derogatory predisposition within the justice system is extremely dangerous. That’s why, as Crawford states, “inclusivity matters — from who designs it to who sits on the company boards and which ethical perspectives are included” (Crawford). The article ends by explaining that for those who “already face marginalization,” the dangers of prejudicial bias are already real, as these systems were simply not built for them or engineered to consider them; thus making the current fear of AI taking over more of a fear for the affluent white men like Bill Gates(who recently did an interview voicing his fear of the extent AI can go).

Ruha Benjamin’s “Race After Technology: Abolitionist Tools for the New Jim Code” has a striking title, playing on the normalization of discriminatory bias within tech. Social coding, or synonymously associating risk or negative values with racially coded names. This is similar to something I refer to as the watermelon crisis of the South.  Post-Emancipation, free Black Americans of the South sold watermelon in open market areas, providing themselves with a lucrative way of earning a tax-free income by producing a crop that was relatively easy to grow and in high demand. Upon seeing their success, negative associations or stereotypes like “black people love watermelon” were floated around to hurt the business of these then successful and wealthy black watermelon sellers. In turn, Benjamin’s article highlights the dark evils that racist web programmers can cause by webbing their prejudices into their code, like engineered inequity, default discrimination, and coded exposure.



Sep 30

AI Proposal Paper Topic:

My proposal idea/topic for Assignment 1 will be to research how to ChatGPT (a multimodal generative AI system using large language models) “works”, it’s interface,  as well as analyzing potential biases and how clerical human error can be harmful when programming these systems of artificial intelligence (real world/social scientific impact). I will also include how the diversification of who’s in tech (ex: currently dominated by white men) can create a positive impact on how inclusive highly advanced chat modules have the potential to become (ex: a team of black woman may produce more accurate results about black hair care, vernacular, and culturally specific values than a team composed of those who have not been exposed to the same).

Below is the same proposal idea reworded by my chosen AI tool, ChatGPT:

My proposal idea/topic for Assignment 1 will be to research how ChatGPT, a multimodal generative AI system that uses large language models, “works,” including its interface, training, and ability to generate responses. I will also analyze potential biases within AI systems and how human decision making, errors, and assumptions during the development and programming of these systems can have harmful real world and social scientific impacts.

I will further examine how diversification within the technology industry can potentially create more inclusive and representative AI systems. For example, having people from different racial, cultural, and experiential backgrounds involved in the development and evaluation of AI may help identify biases and gaps that others may not recognize. This can be particularly relevant when examining culturally specific subjects such as Black hair care, vernacular, and other forms of cultural knowledge that may be underrepresented in technological systems.

Using sources such as Kate Crawford’s “Artificial Intelligence’s White Guy Problem” and Ruha Benjamin’s Race After Technology: Abolitionist Tools for the New Jim Code, I will examine how representation, data, and human decision making can influence the development of AI and potentially reproduce existing social biases.