Brainstorm

What am I interested in AI wise? I looked up MTA or more general public transportation related questions but what else? Is AI being used in fashion? Is it being used in designing? In manual labor? Is there AI being developed to be more useful to specific trades? 

 

5 Topics(?)

Is AI being used in public transportation systems?

Is AI being used to design clothes in fashion? 

How will trade schools adjust to using AI?

To what length can AI affect blue collar jobs?

Can AI be biased based on the information its trained on?

 

2 PSA I like

Walk Tuah. @citiesbydiana Tiktok. (2024,September 28) Tiktok: https://www.tiktok.com/@citiesbydiana/video/7419729268629982507

(ai generated psa)

Skilled Trades College – Get The Skills to Pay The Bills (2022,December 6) Youtube: https://www.youtube.com/watch?v=Gvpig4oIV1o

Week 3

Version 1- My Writing

As society moves into a new age of AI, we see its impact in all different branches of society. Currently, AI is being developed specifically geared towards collecting and analyzing data on pharmaceutical drug development, being made to use the collected data to even possibly synthesize new drugs. With the investment being put towards this progress, we can already clearly see the benefits. One company alone has “quantitatively measured 5 billion+ lab interactions in the past 3 years–roughly 50X the entirety of all publicly available chemistry data”(Terray Therapeutics Media, 2024). With the work they’ve put into this, it’s easy to feel uneasy about the whole idea of computer-developed drugs. While sounding like something from a sci-fi movie, this product would be nearly as trustworthy as one made by humans, because while AI will be doing the bulk of the work with experiments and development, humans will always be there to point things in the right direction and make sure that he information is taken isn’t too faulty or misunderstood. All together as we continue to develop as a species and find new illnesses natural or not, AI can be a great help in collecting raw data and analyzing it at a rate humans cannot, and this can lead to a steady positive trend in the development of pharmaceuticals for the future.

APA CITATION

Tsuji, S., Hase, T., Yachie-Kinoshita, A., Nishino, T., Ghosh, S., Kikuchi, M., Shimokawa, K., Aburatani, H., Kitano, H., & Tanaka, H. (2021, May 3). Artificial Intelligence-based Computational Framework for Drug-target prioritization and inference of novel repositionable drugs for alzheimer’s disease – alzheimer’s research & therapy. SpringerLink. https://link.springer.com/article/10.1186/s13195-021-00826-3 

Terray Therapeutics Media. (2024, October 17). Terray Therapeutics closes oversubscribed $120M series B to advance its generative AI pipeline of Small Molecule Therapeutics to the clinic – terray therapeutics. Terray Therapeutics. https://www.terraytx.com/press/terray-therapeutics-closes-oversubscribed-120m-series-b-to-advance-its-generative-ai-pipeline-of-small-molecule-therapeutics-to-the-clinic 

Lohr, S. (2024, June 17). How A.I. is revolutionizing drug development. The New York Times. https://www.nytimes.com/2024/06/17/business/ai-drugs-development-terray.html?searchResultPosition=3 

 

Vesion 2 ChatGPT Prompt 1–

 Fix any grammer and make this clearer to the average reader–…-then find a good place to mention ai’s ability to specifically target and work with the 400 human genes that modern drugs target.

As we enter a new age of AI, its influence is transforming various sectors, including healthcare and pharmaceuticals. Currently, AI is being developed to collect and analyze data related to drug development and is even being trained to synthesize new drugs based on this data. With substantial investment fueling this progress, the benefits are already visible. For instance, one company, Terray Therapeutics, has recorded over 5 billion laboratory interactions in just the past three years—a data volume roughly 50 times larger than all publicly available chemistry data combined (Terray Therapeutics Media, 2024).

Despite this impressive progress, the idea of AI-driven drug development can feel unsettling, evoking images of science fiction. However, AI-developed drugs are projected to be nearly as reliable as those made by human scientists. While AI performs much of the heavy lifting—running experiments, processing data, and developing compounds—humans will guide the process, ensuring that the data is interpreted accurately and ethically.

Moreover, AI has a unique ability to target and work with the approximately 400 human genes that modern drugs focus on, offering potential breakthroughs in personalized medicine and targeting specific genetic profiles with precision.

As humanity continues to face new diseases, AI’s capacity to gather and analyze data far faster than humans could lead to a steady advancement in pharmaceutical development, providing new tools and treatments to improve health outcomes globally.

Version 3 ChatGPT Prompt 2- Rewrite this PSA with one argument against the use of ai in developing new drugs. Please keep it below 200 words, you can cut out anything not relevant to the whole PSA.

As we move into the age of AI, its impact on drug development is significant. AI systems are being designed to collect vast amounts of data, analyze it, and even help synthesize new drugs. Companies like Terray Therapeutics have already recorded over 5 billion lab interactions in the past three years, far surpassing the amount of publicly available chemistry data (Terray Therapeutics Media, 2024).

AI’s ability to focus on the roughly 400 human genes targeted by modern drugs offers exciting potential for personalized medicine. However, this rapid development also raises concerns. Relying heavily on AI for drug creation could lead to unexpected risks, as these algorithms may overlook subtle but critical biological factors that only experienced human researchers might catch. While AI can speed up analysis, there is still uncertainty about how well it can predict real-world effects on the human body.

While AI’s ability to handle immense data and perform rapid analysis can accelerate pharmaceutical advancements, it’s crucial to balance this with human expertise to ensure safety and trust in these new, computer-generated treatments.

Comparison Essay

Starting this project, it was hard for me to find something to write about. I read through man articles on AI in different trades or jobs but struggled to find something that caught my attention. That was until I found an essay about a lab in California making major moves in AI by designing one that could perform and study experiments or chemical reactions on a microscopic level. After finding other interesting articles with a similar concept, writing my PSA got easier. However, I felt a problem with my PSA no matter how much I read over it I was unsure how much excess information I was including or where to fit in an important piece of information. 

I decided to address this in my first prompt, testing the efficiency of ChatGPT by asking it to correct grammatical or clarity errors and incorporate a key piece of information that I couldn’t find a place for. I was blown away that even though it seemed to write a bit more than I wanted, it had plenty of information in a much clearer way than I was able to put it. I plan to continue forward taking into account where ChatGPT helped me fit in this information in my final draft.

Then came my second prompt. I wanted to test both ChatGPTs’ ability to condense information and come up with an opposing argument without telling it one directly. I was happy to see that it worked wonderfully again, keeping my word count well below the maximum I provided while omitting almost nothing that I felt was key to the PSA altogether. I appreciated its ability to give an opposing argument, and in the end, I could say I was overly satisfied with my two results. 

Week 5

PSA FINAL DRAFT

Title- AI’s Unique Ability To Revolutionize Modern Medicine

Key Question- How can the use of AI bring out the greatest potential of human medicine and healthcare?

PSA- As society moves into a new age of AI, we see its impact in all different branches of society. Currently, AI is being developed specifically geared towards collecting and analyzing data on pharmaceutical drug development, being made to use the collected data to even possibly synthesize new drugs. The benefits of which we can already see- for instance, one company, Terray Therapeutics, has recorded over 5 billion laboratory interactions in just the past three years—a data volume roughly 50 times larger than all publicly available chemistry data combined (Terray Therapeutics Media, 2024). Even with the work that has been put into this step, it’s easy to feel uneasy about the whole idea of computer-developed drugs.  While AI performs much of the heavy lifting—running experiments, processing data, and developing compounds—humans will guide the process, ensuring that the data is interpreted accurately. Relying heavily on AI for drug creation could lead to unexpected risks, as these algorithms may overlook subtle but critical biological factors that only experienced human researchers might catch. Despite this AI’s novelty, it would be wrong to overlook its ability to soon effortlessly understand the workings of the roughly 400 human genes targeted by modern drugs. This can result in major potential breakthroughs in personalized medicine and the precision of targeting specific genetic profiles (Shingo Tsuji, 2021). As we continue to develop as a species and find new illnesses, natural or not, AI can be a great help in collecting and analyzing raw data. This can lead to a steady positive trend in the development of pharmaceuticals for a better future for us all.

Call To Action- We need to stay informed about how AI is transforming drug development, bringing both huge potential and unique challenges. By understanding its impact, even you can play a role in advocating for the safe, ethical use of this technology in creating a better future.

References- 

Lohr, S. (2024, June 17). How A.I. is revolutionizing drug development. The New York Times. https://www.nytimes.com/2024/06/17/business/ai-drugs-development-terray.html?searchResultPosition=3

Terray Therapeutics Media. (2024, October 17). Terray Therapeutics closes oversubscribed $120M series B to advance its generative AI pipeline of Small Molecule Therapeutics to the clinic – terray therapeutics. Terray Therapeutics. https://www.terraytx.com/press/terray-therapeutics-closes-oversubscribed-120m-series-b-to-advance-its-generative-ai-pipeline-of-small-molecule-therapeutics-to-the-clinic 

Tsuji, S., Hase, T., Yachie-Kinoshita, A., Nishino, T., Ghosh, S., Kikuchi, M., Shimokawa, K., Aburatani, H., Kitano, H., & Tanaka, H. (2021, May 3). Artificial Intelligence-based Computational Framework for Drug-target prioritization and inference of novel repositionable drugs for Alzheimer’s disease – Alzheimer’s research & therapy. SpringerLink. https://link.springer.com/article/10.1186/s13195-021-00826-3 

Reflection Essay-

I think it’s safe to say I learned far more than I set out to about AI throughout this project. I learned the importance of clear and decisive words when communicating with something in my eyes just as intelligent as me. After learning about the thousands of hours that went into refining the pretrained aspect of ChatGPT, it’s amazing to see the ease it can receive and carry out any task given to it. I see its potential not only as a tool but also as a teacher, critic, or peer. After everything humans have accomplished, I think little comes close even to the current stage of artificial intelligence. Not only did I learn about AI, but I found such an interesting niche in AI development, I can see myself continuing to tune into its progress in the future. Learning about an AI that people put all the same effort into developing as ChatGPT can manipulate and record multiple dimensions of biomedical data is mind-blowing. Reading about an AI developed that can accurately predict the way base proteins, the base of all life, will fold and interact is inspiring. Even growing up in a world where cell phones and subway trains are normalized, I was blown away the more I read about the potential lying in the future of AI.

Thinking back, it’s easy to talk about the easiest and hardest part of this project. The hardest part is easy to talk about since it was the very start. Starting this unit I enjoyed learning all types of new things about AI, how it’s made, and how it’s used. When it came time to research and look through articles I found myself lost in too many options, as AI still is something I never put too much thought or time into learning about. I found myself reading about its effect and uses in all different types of industries and none stood out to me enough to get me to start writing. It was only when I was suggested to work backward from any interesting article and interview AI about it first that I was able to find my fascination with AI’s use in developing new drugs. This brought me to the easiest part, where I found it easy to ask questions and keep finetuning my ideas to get the results I wanted from ChatGPT. I feel the allotted time was more than enough to complete this project. Though I had trouble with it, thinking of anything more I would’ve done was difficult. I could see myself spending more time doing more research, aiming for different research articles to hear their point of view or how they’re incorporating AI into their research. I probably would’ve also spent more time adjusting my first draft, as I feel the first ChatGPT prompt and its result were things I could’ve spent the time to ask myself and ended up with a similar result. 

In the end, this is most likely what changed my opinion of AI the most. With I set the goal of better understanding such a widely available and well-known tool of ChatGPT, I was very satisfied with the progress I saw through this assignment. Everything concerning the project that I asked it isn’t included in my report, but all the conversations I had with the AI were beneficial. It was using every opportunity to fulfill my request to the best of its ability and went beyond that with whatever other changes it saw fit. (583 words)

Lohr, S. (2024, June 17). How A.I. is revolutionizing drug development. The New York Times. https://www.nytimes.com/2024/06/17/business/ai-drugs-development-terray.html?searchResultPosition=3

Terray Therapeutics Media. (2024, October 17). Terray Therapeutics closes oversubscribed $120M series B to advance its generative AI pipeline of Small Molecule Therapeutics to the clinic – terray therapeutics. Terray Therapeutics. https://www.terraytx.com/press/terray-therapeutics-closes-oversubscribed-120m-series-b-to-advance-its-generative-ai-pipeline-of-small-molecule-therapeutics-to-the-clinic 

Tsuji, S., Hase, T., Yachie-Kinoshita, A., Nishino, T., Ghosh, S., Kikuchi, M., Shimokawa, K., Aburatani, H., Kitano, H., & Tanaka, H. (2021, May 3). Artificial Intelligence-based Computational Framework for Drug-target prioritization and inference of novel repositionable drugs for Alzheimer’s disease – Alzheimer’s research & therapy. SpringerLink. https://link.springer.com/article/10.1186/s13195-021-00826-3