AI in Healthcare by Julia Narewski

Personalized Overview

julianarewski — 2025-10-13 01:39:14 UTC

Today I will be researching the implementation of artificial intelligence in the healthcare industry, with a specific focus on its application in medical social work. I chose this industry because I am currently studying social work and have a recent interest of working within a healthcare setting. In my Padlet wall, I will cover the ways in which artificial intelligence is utilized in patience care, case management, and personalized treatment plans. AI tools help healthcare workers by handling routine tasks, improving the accuracy of diagnoses, and offering useful information to guide treatment decisions. For medical social workers, this means they can spend more time with patients and families, and less time doing paperwork or organizing services. These applications are significant to me because I want to learn more about the ways that technology will influence my prospective career. I am particularly interested in how it can improve efficiency and patient outcomes, as well as how it may impact the client-social worker relationship. Equally important are the ethical concerns surrounding the use of AI in healthcare, including issues of privacy, bias, and the potential loss of human-centered care which is vital in social work. t is important to examine how AI might impact the client-social worker relationship, which is built on trust, empathy, and human connection. Equally important are the ethical concerns surrounding the use of AI in healthcare, including risks to patient privacy, the potential for algorithmic bias, and the loss of human-centered care. Considering a future position in this field, I believe it is essential to critically assess both the benefits and limitations of AI, so that we can use it responsibly and ensure that the core values of social work—compassion, dignity, and equity—are always upheld.

Healthcare - AI in Predictive Analysis for Patient Risk Assessment

julianarewski — 2025-10-13 01:52:16 UTC

This technology uses machine learning algorithms to analyze data from electronic health records and social work reports. By identifying patients at higher risk of health crises or social challenges, social workers can intervene earlier and provide targeted support. The benefits include improved patient outcomes, more efficient resource allocation, and reduced hospital readmissions. However, challenges include data privacy concerns, potential biases in the algorithms, and the risk of over-reliance on technology, which may reduce the essential human connection in social work.

https://youtu.be/IuNLFRqyagA?si=3DcKZzoVbEm92t6P

Healthcare - AI in Patient Engagement

julianarewski — 2025-10-13 01:55:34 UTC

Chatbots powered by natural language processing are increasingly used in healthcare social work to provide immediate emotional support and information to patients. These AI-driven chatbots can answer common questions, screen for mental health issues, and help schedule appointments. The technology helps reduce wait times and offers continuous accessibility, improving patient engagement and easing the workload for social workers. However, limitations include the inability of chatbots to fully understand complex emotions, potential misunderstandings, and the lack of personalized human empathy. Additionally, some patients may feel uncomfortable sharing sensitive information with AI, highlighting the need for the use of these tools alongside humans.

https://youtu.be/sL8ME7j6xus?si=w6g57-fxGeOVMKQm

Healthcare - AI in Training Employees

julianarewski — 2025-10-13 01:59:02 UTC

Virtual reality is used to train social workers by creating realistic practice scenarios. It lets them experience patient situations and practice skills like communication and problem-solving in a safe space. VR helps social workers gain confidence and learn how to handle difficult cases before working with real patients. The technology uses computer-generated scenes that feel like real life. Benefits include better training and preparation. However, VR can be expensive and requires well-designed scenarios to be effective. While helpful, VR cannot replace real human interactions but is a useful addition to traditional training methods.

https://youtu.be/WnpJ519Qru0?si=sjjxqyddZdd06m_l

Future Trends and Ethical Considerations

julianarewski — 2025-10-13 02:07:35 UTC

In the future, artificial intelligence is likely to become even more important in healthcare social work. AI tools may help social workers better understand patient needs by quickly analyzing medical records, social history, and risk factors. More advanced systems could also help match patients with the right resources, like housing, mental health support, or addiction services. Virtual assistants and chatbots may become more common to help answer patient questions and provide support at any time. These tools could help social workers manage heavy workloads and focus more on direct care.

However, there are important ethical issues to think about. One concern is privacy. Patients share very personal information, and it’s important that their data is kept safe. Another issue is bias. If AI systems are trained on unfair or incomplete data, they might make bad suggestions or treat some groups unfairly. Also, there is a risk that too much technology could take away from the human side of social work, which is built on trust and empathy.

Personally, I think AI has a lot of potential to support social workers and improve care, but it should never replace human interaction. I believe it’s important for social workers to stay involved in how AI tools are used, so they can speak up for their clients and make sure technology is used in fair and respectful ways. The future of AI in this field should be focused on helping people—not just making systems faster or cheaper.

Societal Impact

julianarewski — 2025-10-13 02:11:11 UTC

Artificial intelligence is changing healthcare and social work in many ways. While it can help improve services, it also has a big impact on society. One major issue is employment. As AI tools take over tasks like paperwork or data entry, some jobs may be reduced or changed. This can make workers feel unsure about their future roles. On the other hand, AI may also create new jobs that focus on managing technology or interpreting data.

Privacy is another big concern. AI systems use a lot of personal information from patients, including medical and social records. If this data is not protected properly, it could be misused or shared without permission. This can harm trust between patients and healthcare workers.

Equity is also important. If AI tools are not designed fairly, they might not work well for all people. For example, they might make worse decisions for people from minority or low-income groups. This could lead to unfair treatment or missed care.

Personally, I think AI can be a helpful tool in social work, but it must be used carefully. Social work is about helping people with respect and understanding. If AI causes harm, even by accident, it goes against those values. These societal issues make me believe that social workers need to be involved in how AI is used. We must make sure that technology is used carefully and does not replace the human care that is at the heart of our work.

Video Part 1

julianarewski — 2025-10-13 03:06:24 UTC

Video Part 2

julianarewski — 2025-10-13 03:28:08 UTC

Reflection

julianarewski — 2025-10-13 03:38:36 UTC

During my research on AI in social work, I learned that while AI can be helpful, it also brings serious risks. I found it challenging to understand how AI works, but I overcame this by reading simple articles and breaking down complex ideas. I realized that AI could support social workers by saving time, but it should never replace human care and empathy. This research helped me see that AI needs strong rules to be used safely. It also made me think more deeply about how technology affects people, especially in jobs that require understanding and compassion, like social work.

References

julianarewski — 2025-10-13 03:52:02 UTC

Harris, J. (2025, February 19). The AI revolution in social work: NASW’s call for action. Social Work Blog. https://www.socialworkblog.org/sw-practice/2025/02/the-ai-revolution-in-social-work-nasws-call-for-action/ Social Work BlogRationale: This blog post outlines how the National Association of Social Workers is urging advocacy around AI in social work, providing a current professional perspective on both opportunities and risks in the field.

National Association of Social Workers (NASW). (2021). NASW standards for technology in social work practice.https://www.socialworkers.org
Rationale: These official guidelines help explain how social workers should use technology ethically, which is vital for my research.

Reamer, F. G. (2023). Artificial intelligence in social work: Emerging ethical issues. International Journal of Social Work Values and Ethics, 20(2), 52–71. Reamer, F. G. (2023). Artificial intelligence in social work: Emerging ethical issues. International Journal of Social Work Values and Ethics, 20(2), 52–71. https://doi.org/10.55521/10-020-205

Rationale: This article directly addresses ethical challenges of using AI in social work, making it a highly relevant and authoritative source for my research on the risks and responsibilities of AI in this field.

Georgia State University. (2025, May 23). Social work professor taps into teaching potential of virtual reality tools. GSU News. https://news.gsu.edu/2025/05/23/social-work-professor-taps-into-teaching-potential-of-virtual-reality-tools

Rationale: This article provides a concrete example of how immersive technology is being used in social work education, illustrating potential innovations and practical challenges in integrating technology into the field.

Fisher, J. F. (2025, January 21). To bot or not to bot? How AI companions are reshaping human services and connection. Stanford Social Innovation Review. https://ssir.org/articles/entry/ai-chatbots-social-services

Rationale: This article critically examines the dual-edged nature of AI chatbots in social services, highlighting both their potential to expand access and the risk of diminishing human connection, which is central to my research on AI’s impact in this field.

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