Article Text
Commentary
What you believe you want, may not be what the algorithm knows
Statistics from Altmetric.com
Footnotes
Contributors SS is the sole author.
Funding This study was funded by H2020 European Research Council (Grant number: 949841; European Research Council (ERC)).
Competing interests None declared.
Provenance and peer review Not commissioned; internally peer reviewed.
Linked Articles
Read the full text or download the PDF:
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?