While it may be tempting to think of an output from an AI-based tool as neutral when it comes to bias, that is not the case. Since machine learning models are trained on real world datasets, and since the world contains bias, it is safe to assume that outputs from these models may replicate or even exacerbate biases we see in the world around us.
AI tools lack the specific training on the detailed requirements of medicine and healthcare, and therefore not accurately interpreting the nuances of specialized medical fields. Students should approach AI as a tool that provides broad insights, rather than a source for definitive answers. Health professionals and students have a responsibility for their actions and must evaluate the reliability of AI generated information.
Be aware of biases in the AI you are using.
Learn about bias in AI: the "GenderShade" video walks through a study of how well popular face-recognition software identifies people of different genders and skin types.
Ethics and privacy (data security): AI is useful for learning and assisting in case scenarios, but it is crucial to protect sensitive data and ensure patient confidentiality. Health students have a responsibility to ethically manage data, not to provide AI tools with highly protected data such as personally identifiable medical information, especially in real clinical scenarios and placements - to protect their own, and others’ information rights.
In a field that emphasizes individualized care and human interaction, prioritizing patient needs and ethical considerations is essential. AI cannot replace the necessary people skills in healthcare.
Healthcare professionals are responsible for their knowledge and decisions. Dependence on AI for information can limit an individuals ability to critical think, evaluate, diagnose and treat. Professionals are liable for their actions and inactions, therefore evaluating the liabilities of one's position is important when utilizing an AI.
It is safe to assume that -- in some way or another -- any information you put into an AI-based tool is being used to further train the machine learning model. If you choose to use these tools, you'll want to make sure you're never putting personal or secure information about you or anyone else in your chats. You should also read through any user agreements if you sign up to use a particular service and decide if you are comfortable agreeing to the terms. If one of your class or research projects requires the use of a particular technology that you do not wish to create an account for, you can ask your professor or mentor for an alternative way to complete the project.
