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AI-assisted consent in paediatric medicine: ethical implications of using large language models to support
Jemima Winifred Allen1,2, Brian David Earp3, Dominic Wilkinson4,2,3,5,6
1Department of Paediatrics, Monash University Faculty of Medicine Nursing and Health Sciences, Melbourne, Victoria, Australia.
Insights
Large language models (LLMs) can aid pediatric informed consent by providing tailored explanations for children. However, ethical considerations regarding autonomy and potential influence require careful implementation alongside human judgment.
Area of Science:
- Medical Ethics
- Pediatric Healthcare
- Artificial Intelligence Applications
Background:
- Informed consent in pediatrics is ethically complex due to children's varying autonomy.
- Traditional decision-making relies heavily on parents, but children's evolving capacities necessitate their involvement.
- Facilitating meaningful consent or assent for minors in complex medical situations remains a challenge.
Purpose of the Study:
- To examine the ethical implications of using large language models (LLMs) in pediatric informed consent.
- To explore how LLMs can support children's autonomy and aid decision-making processes.
- To address concerns about LLMs' potential influence and impact on family-provider dynamics.
Main Methods:
- Ethical analysis of LLM integration in pediatric consent.
- Exploration of LLM capabilities for age-appropriate medical information delivery.
- Discussion of potential benefits and risks associated with LLM use in clinical settings.
Main Results:
- LLMs can offer interactive, age-tailored explanations of medical information to enhance comprehension.
- Potential for LLMs to empower children, mediate disputes, and support parents.
- Concerns exist regarding LLMs' ability to fully support developing autonomy and avoid undue influence.
Conclusions:
- LLMs show promise for improving pediatric consent processes with appropriate safeguards.
- Cautious implementation is essential, integrating LLMs as complements to, not replacements for, human interaction.
- Empathy, judgment, and trust remain crucial elements in pediatric consent that LLMs cannot substitute.
Abstract:
Obtaining informed consent in paediatrics is an essential yet ethically complex aspect of clinical practice. Children have varying levels of autonomy and understanding based on their age and developmental maturity, with parents traditionally playing a central role in decision-making. However, there is increasing recognition of children's evolving capacities and their right to be involved in care decisions, raising questions about facilitating meaningful consent, or at least assent, in complex medical situations.Large language models (LLMs) may offer a partial solution to these challenges. These generative artificial intelligence (AI) systems can provide interactive, age-appropriate explanations of medical procedures, risks and outcomes tailored to each child's comprehension level. LLMs could be designed to adapt their responses to young patients' cognitive and emotional needs while supporting parents with clear, accessible medical information.This paper examines the ethical implications of using LLMs in paediatric consent, focusing on balancing autonomy promotion with protecting children's best interests. We explore how LLMs could be used to empower children to express preferences, mediate family disputes and facilitate informed consent. However, important concerns arise: Can LLMs adequately support developing autonomy? Might they exert undue influence or worsen conflicts between family members and healthcare providers?We conclude that while LLMs could enhance paediatric consent processes with appropriate safeguards and careful integration into clinical practice, their implementation must be approached cautiously. These systems should complement rather than replace the essential human elements of empathy, judgement and trust in paediatric consent.
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