Ethical Considerations Around AI
The use of AI in healthcare presents substantial ethical challenges and therefore requires careful consideration.- A range of individual and societal harms could emerge from abuse, misuse, inadequate design, and other potentially unintended consequences of AI.
- A few major considerations are listed below.
Bias and Fairness
- Due to the nature of reliance on existing data, AI systems can perpetuate or amplify biases that are present in training data or past medical practices.
- This can lead to unfair treatment, especially among underrepresented populations.
Transparency and Interpretability
- Healthcare decisions made using AI have profound implications.
- It is important for patients and clinicians to understand and trust the AI recommendations.
- Without transparency it can be challenging to account for errors and misjudgements.
Data Privacy vs. AI Efficacy
- Vast quantities of data are required by AI for optimal function.
- This needs to be balanced against patients' rights to data privacy and protection.
- Information entered into AI models through questions and prompts are typically integrated into the models training data.
- e.g. if one asks ChatGPT a question that contains private or sensitive information, for instance about a patient, then that information becomes a part of the data searched when other users make future queries using ChatGPT
Global Access and Equity
- There is an ethical imperative to ensure that AI benefits are extended beyond wealthy and privileged
- As AI becomes more integrated, this will be required in order to prevent the widening of health disparities.
From UNM AI in Health Sciences Guide
