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Hi, these 5 word doc is the information that needs to be in the PowerPoint. First please write me a paragraph of (Medical AI cons). that is in the file named “Christian – Medical AI pros” You can read his paragraph and write me a paragraph of cons. (he wrote pros). Thank you, I will give you the final draft of the information by this week, and those five files are just let you know what is going to be in the powerpoint. This is not a long presentation.Thank you.
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GPT LLMs and AI in general could fundamentally change the healthcare provider industry, for both
healthcare services and healthcare administration. Speech-to-text AIs are making inroads into medical
transcription coding (the transformation of healthcare diagnosis, procedures, medical services, and
equipment into universal medical alphanumeric codes). Previous transcription applications could find
key words in the text, but GPT natural language processing is more capable of understanding the full
context of the transcription, something that previously required a human. This understanding of the
context will allow for faster, and hopefully more accurate, association in coding, vs the manual method
of looking through tables of more than 8,000 five-character alphanumeric codes. Additionally, AI
predictive analytics can be used to predict patient influx, helping hospitals and clinics better manage
their resources and staff. This can lead to improved patient care and reduced waiting times.
https://hoornebert.be/2022/11/14/transforming-healthcare-with-speech-to-text-and-natural-languageprocessing/
https://www.aapc.com/resources/what-is-medical-coding
https://medium.com/llmed-ai/gpt-for-gps-an-ai-assisted-scribe-ef707c2116f5
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Cons
Data Privacy and Security: The reliance on large datasets raises significant concerns about patient privacy and data security. There’s a
risk of sensitive health information being misused or leaked.
Bias and Inequality: AI systems are only as unbiased as the data they are trained on. If the training data is not diverse, the AI might
exhibit bias, leading to disparities in care quality among different populations.
Loss of Human Touch: While AI can enhance many aspects of healthcare, it cannot replace the empathy, understanding, and comfort that
human interaction provides. There’s a concern that over-reliance on AI could lead to a depersonalized healthcare experience.
Regulatory and Ethical Challenges: The rapid advancement of AI technologies poses regulatory challenges. There’s a need for
frameworks to ensure the ethical use of AI, including issues related to consent, transparency, and accountability.
Cost and Accessibility: Implementing AI solutions requires significant investment in technology and training. This could widen the gap in
healthcare quality between well-funded and under-resourced healthcare systems.
Reliability and Accountability: When AI systems make errors, determining liability can be complex. There’s also the challenge of
ensuring that AI systems are reliable and can be trusted with life-critical decisions.
In conclusion, while AI in healthcare offers the potential to significantly improve patient outcomes, efficiency, and the speed of medical
advancements, it also presents challenges that need to be carefully managed. Balancing the benefits with the risks requires ongoing
research, ethical considerations, and robust regulatory frameworks.
In weighing the pros and cons of Large Language Models in the workplace, it is evident that
integration brings their integration brings forth a spectrum of advantages and challenges.
How AI can affect HR: Pros
Despite the drawbacks associated with employee selection and recruitment in
Human resources, there are numerous advantages. AI has the capability to
automate repetitive and time-consuming tasks, allowing HR professionals to be
able to focus on strategic approaches. AI can also enhance decision-making by
providing valuable insights through HR and predictive analytics.
AI plays a critical role in optimizing the hiring process and ensuring efficiency and
effectiveness. By streamlining the screening and selections process, AI speeds up
the overall hiring timeline. Managers benefit from automated assistance in
nurturing potential hires, while receiving notifications when people apply for open
positions. This integration of AI in HR operations not only accelerates the hiring
process but also quickly fills various positions including short-term and temporary
roles.
https://www.ibm.com/blog/artificial-intelligence-and-a-new-era-of-humanresources/
https://www.businessnewsdaily.com/how-ai-is-changing-hr
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Opening (Haley)
o Brief description of LLMs
o Why they are relevant to modern business (business management)
How are LLM/GPTs relevant to modern business
As technology is constantly growing and advancing, the modern workforce finds itself
adapting and evolving to accommodate the changes. There are both opportunities and challenges
that result from this constant growth. One prominent example of this advanced technology would
be Generative Pre-trained Transformer Large Language Models, also often referred to as GPT
LLMs. GPT LLMs are sophisticated language models powered by artificial intelligence
technology, and they have significantly impacted today’s workforce in many industries,
especially in management.
Large Language Models can be trained to analyze, produce, and predict, among other
functions, when given data. This allows a computer to perform as a human in certain
circumstances such as writing and editing reports or analyzing and translating data. While some
are grateful for the assistance LLMs provide, others are more concerned with the negative
implications including the replacement of human jobs.
https://scholar.stjohns.edu/cgi/viewcontent.cgi?article=1095&context=jga
AI’s impact on employee selection and recruitment in Human Resources brings forth several cons and
challenges. One such challenge is the opacity of many AI algorithms utilized in HR processes. These
algorithms, while powerful, often lack transparency which can sow seeds of doubt among both
applicants and HR professionals. It also becomes challenging to understand the rationale behind
candidate selection or rejection.
Additionally, there is concern regarding the potential loss of jobs within the HR sector due to the
widespread adoption of AI. While AI streamlines certain recruitment tasks, it may also lead to the
displacement of human recruiters, jeopardizing traditional roles and responsibilities. Furthermore, AI
systems may not consistently accurately assess candidates’ suitability for a position, particularly when
evaluating subjective attributes or specialized skills. This can result in the oversight of qualified
candidates or the selection of individuals who may not be the best fit for the role.
In addition, an overreliance on technology in recruitment processes can diminish the role of human
intuition and critical thinking, which remain invaluable in assessing candidates beyond the scope of AI
analysis. Lastly, AI presents promising opportunities for enhancing recruitment processes.
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