What you believe you want, may not be what the algorithm knows
Share this article
Click the icon of the social media platform on which you would like to share this article.
Email this article to a friend
If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.
Other content recommended for you
- Ethics of the algorithmic prediction of goal of care preferences: from theory to practice
- AI support for ethical decision-making around resuscitation: proceed with care
- Randomised controlled trials in medical AI: ethical considerations
- AI knows best? Avoiding the traps of paternalism and other pitfalls of AI-based patient preference prediction
- Development and validation of a deep learning system to screen vision-threatening conditions in high myopia using optical coherence tomography images
- Autonomy-based criticisms of the patient preference predictor
- Computer knows best? The need for value-flexibility in medical AI
- Use of artificial intelligence for image analysis in breast cancer screening programmes: systematic review of test accuracy
- Who is afraid of black box algorithms? On the epistemological and ethical basis of trust in medical AI
- Does “AI” stand for augmenting inequality in the era of covid-19 healthcare?