My process of AI prompting:

• I used the Role-Output-Level-Context-Standard method, as we were shown in class. My prompt goes as follows:
  • Acting as a college student, write an essay on the industries that AI disrupts as a technology for a college-level class called New Media 100. I will give you a list of the industries to use in your research, and in the results, only those industries should be listed, as well as why/how they are disrupted. The list of industries goes as follows:
• At first, my AI did not provide nor cite its sources. So I had a dialogue with it to remedy that.
• It also formatted the essay originally with bullet points, rather than paragraphs. I asked it to change the format into three paragraphs like my essay for Task 1 was, and that did it.

Comparison of human vs. AI work:

• The thesis statement and hook of my essay I can say without a doubt are much better than what the AI produced. A hook is supposed to draw the reader in, and the AI just gave a lifeless explanation of what it was writing about. Not much to draw the reader in there.
• The AI defended the claims it made well, but there was almost a “copy-paste” quality to its responses, as if taken right off a webpage. What it did do well (after I told it to) was cite its evidence in clear APA-style citation formatting, whereas I only gave a interactive link to click on and see the source.
• I would say it is organized well, but only because I gave it the specifications to be three paragraphs. If it had it its way, it would have been a well organized bulleted list. Topic sentences are clear, but again, very dry, not very engaging. My essay, on the other hand, may have been less clear but certainly had a better flow then the AI version.
• In terms of prose, like I said, the writing was very dry and lifeless, and did not make reading it enjoyable. I feel like my essay was more engaging, but thats just my opinion. I think it had perfect grammar, and it did do that well, but it didn’t have that identifiable human touch that I feel like most writing has.
• The tone was informative, while mine was more like a story being told with facts included, I think. The AI definitely knew what it was talking about but it wasn’t saying it in a engaging way.

Task 1 version

If you look back on the state of the world before the iPhone’s release, things looked very different; it has only been roughly 17 years since its release, and it has changed countless industries, some for the better, but also some for the worse. One industry that has been disrupted by mobile devices is the filmmaking industry. Prior to mobile devices like the iPhone, people had to physically attend a movie theatre if they had any hopes of watching a new movie. While that is still sometimes the case, almost every big filmmaking studio has had to alter its distribution methods to include streaming and downloading services as well. On top of that, we have seen disruption in the form of digital streaming services such as Amazon Prime Video, Netflix, Disney+, and YouTube; each with roughly at least 50% of their content being streamed on mobile devices like the iPhone (Forbes Article).
In my mind, this is more a positive thing for filmmaking companies than a negative one. After all, mobile devices are really just another medium for them to promote their products, and when it comes down to it, mobile devices are so engrained into our society that pretty much everyone has one, and anyone with access to the Internet or cellular data can access their content anytime, anywhere. We can see the same trend in the music industry, where apps like Spotify, Apple Music, and SoundCloud reign supreme. (Second Article) However, with that being said, the people who don’t have access to the luxuries the Internet provides us all with will not benefit from this transition at all. Although the spread of information is so fast with the Internet that these kinds of products could in theory spread across the world in mere seconds, not everyone in the world has access to mobile devices, let alone the Internet.
In regards to the possibility of the “old ways” disappearing, I believe the future of the filmmaking industry in particular would look like an expanded version of what this article is referencing in our current time (Third Article). With the use of mobile devices, creativity is literally in the palms of our hands; filmmaking is no longer reserved for big filmmaking companies, and anyone can really make and subsequently view films from their smartphones or tablets. This democratization of filmmaking, as it is called, is something that I predict will only expand in the future, and we will be seeing many more independent filmmakers making their way onto the scene as “traditional gatekeeping” is no longer a factor.

Task 3 version

https://docs.google.com/document/d/1rHC-5OoQFXStuW0Uz0jP_URkWdibyXvEqyO3MGV4JVM/edit?usp=sharing
The Disruptive Impact of AI on Key Industries
Artificial Intelligence (AI) is profoundly altering the landscape of various industries, with customer service, car manufacturing, and education being notably impacted. In customer service, AI-driven chatbots and virtual assistants have become ubiquitous, handling routine inquiries and providing instant responses to customers. This constant availability significantly enhances customer satisfaction while reducing operational costs by automating routine tasks. Advanced Natural Language Processing (NLP) also allows these AI systems to offer personalized responses based on past interactions, thereby improving overall customer experience (Accenture, 2018; McKinsey & Company, 2017; Forbes, 2020).
The automotive industry is undergoing a radical transformation due to AI, particularly in manufacturing processes and the development of autonomous vehicles. AI-powered robots and automation systems have revolutionized car production lines by performing complex tasks with high precision, reducing human error, and increasing production efficiency. Predictive maintenance capabilities enabled by AI minimize downtime and extend the lifespan of manufacturing equipment by monitoring machinery in real-time and predicting failures before they occur. Furthermore, AI algorithms are at the forefront of developing self-driving cars, enabling vehicles to navigate, recognize objects, and make real-time decisions, thus promising to revolutionize both personal and commercial transportation (Boston Consulting Group, 2018; PwC, 2019; Waymo, 2021).
Education is another field where AI is making substantial inroads, transforming how teaching and learning occur. AI-driven educational platforms tailor lessons to individual students’ needs, learning speeds, and preferences, thus addressing the diverse learning styles and paces of students and enhancing educational outcomes. AI tools also streamline administrative tasks such as grading, scheduling, and resource allocation, allowing teachers to focus more on instruction and student engagement. Intelligent Tutoring Systems (ITS) provide additional support outside of regular classroom hours by offering explanations, answering questions, and identifying areas where students might be struggling, thereby significantly enhancing the learning experience (EdTech Magazine, 2019; The Brookings Institution, 2020; IEEE Transactions on Learning Technologies, 2018). These examples illustrate AI’s transformative potential across various sectors, setting the stage for future innovations and further revolutionizing the way we live.
References
Accenture. (2018). Artificial Intelligence: The Future of Customer Service. Retrieved from Accenture.
McKinsey & Company. (2017). The role of AI in customer care. Retrieved from McKinsey & Company.
Forbes. (2020). How AI is Transforming Customer Service. Retrieved from Forbes.
Boston Consulting Group. (2018). AI in Manufacturing. Retrieved from BCG.
PwC. (2019). The future of maintenance: How AI is changing the game. Retrieved from PwC.
Waymo. (2021). Autonomous Vehicles: The Future of Transportation. Retrieved from Waymo.
EdTech Magazine. (2019). How AI is Personalizing Education. Retrieved from EdTech Magazine.
The Brookings Institution. (2020). AI in Education: Promises and Implications for Teaching and Learning. Retrieved from Brookings.
IEEE Transactions on Learning Technologies. (2018). Intelligent Tutoring Systems. Retrieved from IEEE Xplore.