Challenges, Ethical Concerns, and Pessimistic Views with AI Integration

Challenges, Ethical Concerns, and Pessimistic Views with AI Integration

Integrating new applications and technologies into your organization is not a task to be taken lightly. It is vital that we consider all aspects and possibilities for both our staff and our patients when making these decisions. Right now AI is being preached as the solution to most of our problems – like finding water after being stranded in the desert. We’re told that different AI applications and tools can reduce administrative burden and clinical burnout, improve patient experience and outcomes, and so much more. It can be very tempting to leap straight in, but we must practice caution to make sure that the water is real and not merely a mirage. We need to look at all of the challenges, ethical concerns, and pessimistic views around AI first. This way we are prepared for all of its shortcomings, failures, and reasons that may make patients and staff members distrustful.

Medigy Insights

A Generative AI platform is only as strong as the LLM (large language model) that powers it. Before a healthcare organization can use the technology to their advantage, it must have guardrails in place to ensure the generative AI application is operating as intended and not putting patient data at risk or influencing diagnoses or treatment plans based on “bad” data. When it comes to addressing these challenges, some will only be resolved with advances to the technology. But it is also critical that the organizations implementing Generative AI have the proper guardrails built into the system to catch these problems when they happen.


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