‘No, Alexa, no!’

Designing child-safe AI and protecting children from the risks of the ‘empathy gap’ in large language models

Bibliographic Data

ID21785449
AuthorsNomisha Kurian (0000-0002-6862-0543, University of Cambridge, corresponding author)
Year2025
Volume50
Issue4
Pages621-634
Publication date2025-10-02
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueLearning Media and Technology (JOURNAL)
Journal identifiersISSN: 1743-9884 • E-ISSN: 1743-9892
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/17439884.2024.2367052
OpenAlexW4400482554
LanguageEN
Citations received11
References cited33

Rapid advancements in large language models makes child-safe design for their youngest users crucial. This article therefore offers child-centred AI design and policy recommendations to help make large language models (LLMs) utilised in conversational and generative AI systems safer for children. Conceptualising the risk of LLMs as ‘an empathy gap’, this research-based conceptual article focuses on the need to design LLMs that prevent or mitigate against the risks of responding inappropriately to children's personal disclosures or accidentally promoting harm. The article synthesises selected cases of human chatbot interaction and research findings across education, computer science and human-computer interaction studies. It concludes with practical recommendations for child-safe AI across eight dimensions of design and policy: content and communication; human intervention; transparency; accountability; justifiability; regulation; school-family engagement; and child-centred design methodologies. These eight dimensions are tailored to a variety of stakeholders, from policymakers and AI developers to educators and caregivers

Computer security · Empathy · AI in Service Interactions · Computer Science · Ethics and Social Impacts of AI · Psychology · Social Psychology · Social Robot Interaction and HRI

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