Using artificial intelligence to enhance patient autonomy in healthcare decision-making

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985955%3A_____%2F25%3A00597136" target="_blank" >RIV/67985955:_____/25:00597136 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1007/s00146-024-01956-6" target="_blank" >https://doi.org/10.1007/s00146-024-01956-6</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s00146-024-01956-6" target="_blank" >10.1007/s00146-024-01956-6</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Using artificial intelligence to enhance patient autonomy in healthcare decision-making

Popis výsledku v původním jazyce

The use of artificial intelligence in healthcare contexts is highly controversial for the (bio)ethical conundrums it creates. One of the main problems arising from its implementation is the lack of transparency of machine learning algorithms, which is thought to impede the patient’s autonomous choice regarding their medical decisions. If the patient is unable to clearly understand why and how an AI algorithm reached certain medical decision, their autonomy is being hovered. However, there are alternatives to prevent the negative impact of AI opacity in shared (healthcare professional–patient) decision-making processes, and benefit from the high accuracy of such systems. Despite these ethical issues, this paper advocates for its usage and also defends the positive role that it could have in enhancing patients’ autonomy. I advocate for a system where the implementation of AI is only partial, and humans will remain in control of oversighting algorithm interpretation of medical images and patients’ data.

Název v anglickém jazyce

Using artificial intelligence to enhance patient autonomy in healthcare decision-making

Popis výsledku anglicky

The use of artificial intelligence in healthcare contexts is highly controversial for the (bio)ethical conundrums it creates. One of the main problems arising from its implementation is the lack of transparency of machine learning algorithms, which is thought to impede the patient’s autonomous choice regarding their medical decisions. If the patient is unable to clearly understand why and how an AI algorithm reached certain medical decision, their autonomy is being hovered. However, there are alternatives to prevent the negative impact of AI opacity in shared (healthcare professional–patient) decision-making processes, and benefit from the high accuracy of such systems. Despite these ethical issues, this paper advocates for its usage and also defends the positive role that it could have in enhancing patients’ autonomy. I advocate for a system where the implementation of AI is only partial, and humans will remain in control of oversighting algorithm interpretation of medical images and patients’ data.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

60302 - Ethics (except ethics related to specific subfields)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

AI and Society

ISSN

0951-5666

e-ISSN

1435-5655

Svazek periodika

40

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

10

Strana od-do

1917-1926

Kód UT WoS článku

001226910000001

EID výsledku v databázi Scopus

2-s2.0-105003236976