This post is written by Stefaan G. Verhulst, co-founder and chief research and development officer of The Governance Laboratory (GovLab), and Andrew Young, knowledge director at GovLab.
The problem: The relationship between the datafication of everyday life and child welfare has generally been under-explored.
Why it matters: Understanding data for and about children is more important than ever with the impact of climate change on the young - a lack of understanding about data collected is both a lost opportunity and a risk.
The solution: We need a framework for responsible data collection and use for children.
In our first article, we looked at the first three reasons why responsible data for and about children matters. In this second part, we will explore the final five reasons. You can read part 1 here.
4. Data violations can result in lifelong loss of trust
When data is mishandled or when data violations occur, data subjects typically lose trust in organisations or institutions (or in the broader information ecology). This, in turn, can reduce the uptake of essential services, and generally stunt the potential benefits of technology. Children may be uniquely vulnerable to a loss of trust because they generally have had fewer trust-building encounters with technology. In addition, because a loss of trust may be a formative experience, it can have a far longer impact — potentially even lasting a lifetime. The resulting distrust and privacy-protective behaviours displayed by children (or indeed their families) can have severe consequences, including a refusal of health, education, child protection and other public services. It can also impact their behaviour toward others. Increased monitoring and surveillance turns out to limit prosocial behaviour. Instead, children behave more prosocially when they have the possibility to disclose details voluntarily with trusted individuals.
5. Children’s interests can be overlooked
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As new technologies are implemented and the volumes of data increase exponentially, there is a very real risk that existing obligations and protections put in place to protect children may be overlooked. Sometimes, this can happen because these protections are impossible or difficult to maintain in a new technology ecology (though of course, this is no justification). Often, too, it is simply because the interests of children are not prioritised or adequately considered when organisations implement data collection efforts. For example, data analysis may be undertaken by people who do not have expertise in the parameters of child subject research. Similarly, service providers collecting children’s data are not always trained in how to handle it.
6. AI and algorithmic bias pose particular risks
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Much attention has been drawn in recent years to the promise and pitfalls of algorithmic decision-making. While the use of AI in decisions can in some cases expedite processes, it can also contain hard-to-detect but nonetheless, tangible biases that result in real adverse effects (e.g. on those seeking medical care, business loans, parole, or jobs). These risks are only heightened when it comes to children. Once again, children may have less agency or understanding when it comes to how AI and algorithms work; they may not even know that certain processes are the result of algorithmic assessment, modelling, or prediction. As described in UNICEF’s draft Policy Guidance on AI for Children, decision-making in international development, social service provision, and education systems are especially likely to be impacted by AI-driven mediation and filtering, often without the direct engagement or knowledge of children or their caregivers. In addition, if children do suffer algorithmic bias, they may lack the resources or knowledge to respond or seek recourse. Finally, any decision making that targets children and is based on AI that leverages population training data, may fail to take into account children’s physiological and psychological differences (from adults) resulting in potential negative implications for their physical and mental health outcomes. It is therefore imperative that any Responsible Data Use for Children framework include a component dedicated to the role of AI and algorithms.
7. Risk of revisiting trauma
Many of the children served by child welfare organisations have suffered trauma, both physical and psychological. There is a very real risk that asking children to provide data or register for services may inadvertently revisit such trauma and amount to revictimisation. This is especially true when it comes to confidential personal information, for instance, related to domestic violence or another sensitive family situation. Of course in some cases providing such information can also help protect children. The important thing is to make sure data is requested and accessed within the context of a responsible use framework.
"It is clear from this discussion that unique opportunities and risks are present across the entire lifecycle of child-related data: collecting, storing, preparing, sharing, analysing, and using. "
8. The relationship between privacy and children’s self-development
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Finally, privacy and data responsibility are essential to children’s psychosocial growth. Having the freedom and autonomy to experiment with different identities, without prying eyes or chilling dataveillance, is important for children’s self-development. Children are constantly evolving and the lack of protection from persistent, invasive data generation and handling could impact their future selves and opportunities. A sense of privacy can empower children, especially older children, to engage and build relationships with their peers more comfortably and confidently by giving them the option to decide which personal details to disclose and under what conditions. Data responsibility is thus also key when fostering civic and political engagement among young people.
It is clear from this discussion that unique opportunities and risks are present across the entire lifecycle of child-related data: collecting, storing, preparing, sharing, analysing, and using. These opportunities and risks are often distinct from those involved in the datafication of the general public or other vulnerable groups.
They cry out for new approaches to the lifecycle of child-related data. To begin with, the public sector, businesses, and civil society organisations delivering data-related services for children need to better understand the associated risks – as well as opportunities – in an environment characterised by growing quantification and datafication. The eight points we have covered aim at increasing awareness, but they are of course just a start. They are an indicative and thus not a fully comprehensive exploration of the ethical challenges involved. We welcome you to join a discussion about responsible data for children by visiting RD4C.org.
Thanks to Lara Mikocki, Andrew J. Zahuranec and Gabrielle Berman for their input and review and Jaimee Dellipoali and Michelle Winowatan for their assistance.
Stefaan G. Verhulst is co-founder and chief research and development officer of The Governance Laboratory @NYU (GovLab) where he is building an action-research foundation on how to transform governance using advances in science, data and technology. Verhulst’s latest scholarship centres on how technology can improve people’s lives and the creation of more effective and collaborative forms of governance. Specifically, he is interested in the perils and promise of collaborative technologies and how to harness the unprecedented volume of data to advance the public good.
Andrew Young is the knowledge director at The GovLab, where he leads research efforts focusing on the impact of technology on public institutions. Among the grant-funded projects he has directed are a global assessment of the impact of open government data; comparative benchmarking of government innovation efforts against those of other countries; a methodology for leveraging corporate data to benefit the public good; and crafting the experimental design for testing the adoption of technology innovations in federal agencies.
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