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I went with the healthcare industry for this project because of my background and interest in biology, which I am majoring in, and my interest in the medical field. I’ve always been interested in how the body works and how we can use technology to help others. As I learn more, it’s clear that Artificial Intelligence  is playing a great role in shaping the future of medicine. AI is getting doctors to have faster diagnoses, better customize treatment plans, and even monitor patients in real time using wearable technology. These developments aren’t just technological, they’re reshaping how we define care and the healthcare industry as a whole.

This Padlet wall will cover three major applications of AI in healthcare. First, I’ll highlight AI’s role in diagnostic imaging, like IBM Watson Health’s ability to detect tumors in scans. Then I’ll explore personalized medicine, where AI analyzes genetic data to suggest treatment plans for individuals. Finally, I’ll examine AI in patient monitoring,  like Medtronic’s wearable technology that tracks health conditions around the clock.

I chose this industry not just because it fits my career path and my major, but because I see the real-life impacts. Many people I know, including family, have been affected by long diagnostic delays or unclear treatment options; my sister who spent years in the hospital due to this, made me want to look at areas where AI can make a difference.  At the same time, I want to explore and become aware of ethical concerns that come with medical data, privacy, and access. This project will explore both the opportunities and the risks of using AI into one of society’s most essential industries, the healthcare industry.

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AI is being used in diagnostic imaging to detect diseases like cancer more accurately and at a higher speed. Companies like IBM Watson Health and Zebra Medical Vision use machine learning and computer vision to analyze X-rays, CT scans, and MRIs, helping doctors catch tumors and abnormalities earlier than traditional methods. The benefit of this is faster and also more accurate diagnoses , especially in hospitals where they may not have enough workers or people to handle their demands . However, these systems require large datasets and can still diagnose somebody improperly if it is built on biased data. I find this tech promising because it could prevent delays in life saving treatments, especially in communities with limited resources or staff.

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Artificial intelligence helps create a specific treatment for a patient using genetic makeup, lifestyle, and medical history. Companies like Tempus use “predictive modeling” and machine learning to review large amounts of data and recommend treatment plans specific to each patient.Overall this leads to better treatment with less side effects than usual. One main objective is ensuring diverse data sets so the AI doesn't miss patterns unless represented populations. I;m drawn to this technology because it combines the use of science , with unique treatment personalization, and it helps us to be the best version of ourselves without getting too directed by algorithms.

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Companies like Apple Health and Medtronic use live real time monitoring coupled with AI i order to track patients’ heart rates, glucose levels, sleep and more. These devices use machine learning and data from their sensors to alert users and doctors about potential problems before they become  medical emergencies. The main benefit is  that people are consistently being monitored and taken care of  which can be very helpful for people with chronic conditions.However, the accuracy and the data privacy of these patients is still shaky .I find this very interesting because it makes it so we can prevent problems , instead of just reacting to them.

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Future Trends And Ethical considerations

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Future Trends And Ethical considerations

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Artificial Intelligence in the healthcare industry is evolving fast. This is bringing about great changes in diagnosis, treatment of patients and patient care. In the future of AI in the Healthcare industry we hope to see predictive analytics, which can enable healthcare providers to be able to anticipate disease before symptoms are seen and to improve prevention , knowledge and personalized or specialized care. Ai- driven real time monitoring for patients VIA wearable devices will become more high tech, allowing continuous health tracking and faster medical responses. Also, advancements in Genomic medicine will use AI to analyze complex genetic data, tailoring specific treatments to patients with an even higher level of precision

However , these advancements in patient ai technology in the healthcare sector can also bring about great ethical concerns. The increased use of Ai requires the  handling of patient data privacy. AIs tendency to collect info for thor massive datasets creates a  risk of unauthorized data access or misuse. Another important ethical issue is algorithmic bias, where Ai models trained on incomplete or unrepresentative data can lead to unequal treatments or outcomes for patients of different populations

I believe the future of AI in healthcare is very promising; however  it requires a strong ethical standard  to guide its introduction and its direction. Policies must prioritize data protection and bias mitigation to ensure AI benefits all populations fairly. As a bio major, I see great potential in combining biological knowledge with AI innovation but I also feel like there is great work in the security and ethical aspects of AIs use. We must learn how to balance the power of AI, while keeping it safe and ethical.

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Ai in healthcare has a great impact . Ai in healthcare is not only changing how care is administered but also how society interacts with medicine.  Ai can automate routine tasks like medical transcription , basic diagnostics and patient intake processing, which helps doctors offices operate more easily on the back end. The fact that AI can do all this can very much help people and those in the jobs in the medical field.This can also impact people's jobs

Ai cannot replace a doctor, but it does affect nurses , technicians and researchers. Tasks that are automated can have their fields taken over by ai in the future, or require future applicants to be very well versed with AI. Another societal issue with Ai in society is privacy. Without privacy , people's information can be leaked by AI and they don't even know it. This is due to the fact that AI systems run/ are based on collecting and gathering large amounts of data from peopleThis can affect people's livelihoods and their relationships. Another societal issue is Equity. Not everyone can have access or use AI tools or are even trained to use them. This can make life seem less fair for those without access to these tools. This creates a gap in society.   Personally I believe there is great potential in AI in the healthcare industry and that the overall impact on

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Binns, R. (2020). Fairness in machine learning: Lessons from political philosophy. Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency. https://doi.org/10.1145/3287560.3287598
Explanation: This source contains content which talks about fairness in AI from a philosophical point of view. This supports the ethical part of my Padlet.

Brundage, M., Avin, S., Clark, J., Toner, H., Eckersley, P., Garfinkel, B., ... & Amodei, D. (2018). The malicious use of artificial intelligence: Forecasting, prevention, and mitigation. arXiv. https://arxiv.org/abs/1802.07228
Explanation: This talks about misuse of ai and its threats to cybersecurity and orivacy

Bughin, J., Hazan, E., Ramaswamy, S., Chui, M., Allas, T., Dahlström, P., ... & Trench, M. (2017). Artificial intelligence: The next digital frontier? McKinsey Global Institute. https://www.mckinsey.com/featured-insights/artificial-intelligence/the-promise-and-challenge-of-the-age-of-artificial-intelligence
Explanation: This references Ais effect on the job market

Harwell, D. (2020, January 18). A facial recognition company scraped billions of photos from the web. The Washington Post. https://www.washingtonpost.com/technology/2020/01/18/clearview-ai/
Explanation: This reference talks about clearview and its significance.

Hao, K. (2020, November 10). What is AI? We drew you a flowchart to work it out. MIT Technology Review. https://www.technologyreview.com/2020/11/10/1012127/what-is-artificial-intelligence/
Explanation:This was used in the intro. .

Hill, K. (2020, January 18). The secretive company that might end privacy as we know it. The New York Times. https://www.nytimes.com/2020/01/18/technology/clearview-privacy-facial-recognition.html
Explanation: This talks about clearview and their use of ai.

Marr, B. (2020, October 26). The 7 biggest ethical issues facing artificial intelligence. Forbes. https://www.forbes.com/sites/bernardmarr/2020/10/26/the-7-biggest-ethical-issues-facing-artificial-intelligence/
Explanation: this talks about ethics in Ai.

Mavroeidis, V., & Jøsang, A. (2019). Cybersecurity challenges in the era of artificial intelligence. 2019 IEEE International Conference on Cyber Security and Protection of Digital Services. https://doi.org/10.1109/CyberSecPODS.2019.8885064
Explanation: This talks about a link with ai and its effects on cybersecurity.

O'Neil, C. (2016). Weapons of math destruction: How big data increases inequality and threatens democracy. Crown Publishing.
Explanation:This talks about bias in ai and how it can affect things.

Organisation for Economic Co-operation and Development (OECD). (2021). The impact of artificial intelligence on the workplace: Evidence from OECD data. https://www.oecd.org/employment/Policy-brief-AI-and-the-labour-market.pdf
Explanation: This reference talks about how employment and Ai are linked.

Taddeo, M., & Floridi, L. (2018). How AI can be a force for good. Science, 361(6404), 751–752. https://doi.org/10.1126/science.aat5991
Explanation: This article talks about the effects or social impact of AI

Vincent, J. (2021, May 18). Why Google thinks it can outdo Apple on privacy. The Verge. https://www.theverge.com/2021/5/18/22440643/google-privacy-ads-apple-federated-learning-floc-ai
Explanation: I used this to link that tech companies are managing ai and data privacy in different ways.