AI is entering clinical care and the healthcare sector in a big way, at the same time, a growing number of scholars are concerned that this technology cannot adhere to current bioethical principles. In particular, there are increasing concerns that AI poses a threat to the autonomy of patients by being irreconcilable with the practice of informed consent. In this essay, I shall defend the thesis that some applications of AI can be reconciled with a revised version of informed consent – what I call AI Adapted Informed Consent. This solution shall not rest on the idea of making black box AI more transparent or explicable. Instead, I shall argue that black box AI does not necessarily withhold the kind of information necessary for informed consent. Rather, patients can be given epistemic access to the kind of information necessary to make an informed decision, as well as being informed as to how the AI is used in the medical decision-making and in the assessment of their medical situation. Hence, this solution offers a re-interpretation of informed consent as information about contextual functioning and role of AI in medical decision-making. Drawing on republican interpretations of freedom as nondomination, I argue that demands for informed consent can only be restrained if it preserves the voluntariness of our decisions. Hence, I shall conclude that my adapted informed consent thesis allows for the possibility that some applications of black box AI in clinical care can be reconciled with informed consent and due respect for patient autonomy – if three specific conditions can be met.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:umu-214840 |
| Date | January 2023 |
| Creators | Svensson, Ellen |
| Publisher | Umeå universitet, Institutionen för idé- och samhällsstudier |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
Page generated in 0.0023 seconds