AI ethics are ignoring children, say Oxford researchers

In a perspective paper published this week in Nature Machine Intelligence, the authors highlight that although there is a growing consensus around what high-level AI ethical principles should look like, too little is known about how to effectively apply them in principle for children. The study mapped the global landscape of existing ethics guidelines for AI and identified four main challenges in adapting such principles for children’s benefit:

• A lack of consideration for the developmental side of childhood, especially the complex and individual needs of children, age ranges, development stages, backgrounds, and characters.

• Minimal consideration for the role of guardians (e.g. parents) in childhood. For example, parents are often portrayed as having superior experience to children, when the digital world may need to reflect on this traditional role of parents.

• Too few child-centred evaluations that consider children’s best interests and rights. Quantitative assessments are the norm when assessing issues like safety and safeguarding in AI systems, but these tend to fall short when considering factors like the developmental needs and long-term wellbeing of children.

• Absence of a coordinated, cross-sectoral, and cross-disciplinary approach to formulating ethical AI principles for children that are necessary to bring about impactful practice changes.

The incorporation of AI in children’s lives and our society is inevitable. While there are increased debates about who should ensure technologies are responsible and ethical, a substantial proportion of such burdens falls on parents and children to navigate this complex landscape.

Dr Jun Zhao, lead author, Oxford Martin Fellow and Department of Computer Science 

The researchers also drew on real-life examples and experiences when identifying these challenges. They found that although AI is being used to keep children safe, typically by identifying inappropriate content online, there has been a lack of initiative to incorporate safeguarding principles into AI innovations including those supported by Large Language Models (LLMs). Such integration is crucial to prevent children from being exposed to biased content based on factors such as ethnicity, or to harmful content, especially for vulnerable groups, and the evaluation of such methods should go beyond mere quantitative metrics such as accuracy or precision. Through their partnership with the University of Bristol, the researchers are also designing tools to help children with ADHD, carefully considering their needs and designing interfaces to support their sharing of data with AI-related algorithms, in ways that are aligned with their daily routes, digital literacy skills, and need for simple yet effective interfaces.

In response to these challenges, the researchers recommended:

• Increasing the involvement of key stakeholders, including parents and guardians, AI developers, and children themselves;

• Providing more direct support for industry designers and developers of AI systems, especially by involving them more in the implementation of ethical AI principles;

• Establishing legal and professional accountability mechanisms that are child-centred; and

• Increasing multidisciplinary collaboration around a child-centred approach involving stakeholders in areas such as human-computer interaction, design, algorithms, policy guidance, data protection law, and education.

In an era of AI powered algorithms children deserve systems that meet their social, emotional, and cognitive needs. Our AI systems must be ethical and respectful at all stages of development, but this is especially critical during childhood.

Professor Sir Nigel Shadbolt, co-author, Director of the EWADA Programme, Professor of Computing Science at the Department of Computer Science 

Dr Jun Zhao, Oxford Martin Fellow, Senior Researcher at the University’s Department of Computer Science, and lead author of the paper, said: ‘This perspective article examined existing global AI ethics principles and identified crucial gaps and future development directions. These insights are critical for guiding our industries and policymakers. We hope this research will serve as a significant starting point for cross-sectoral collaborations in creating ethical AI technologies for children and global policy development in this space.’

The authors outlined several ethical AI principles that would especially need to be considered for children. They include ensuring fair, equal, and inclusive digital access, delivering transparency and accountability when developing AI systems, safeguarding privacy and preventing manipulation and exploitation, guaranteeing the safety of children, and creating age-appropriate systems while actively involving children in their development.

The study ‘Challenges and opportunities in translating ethical AI principles into practice for children’ has been published in Nature Machine Intelligence.