Karolina La Fors

This article advocates for a hermeneutic model for children-AI (age group 7–11 years) interactions in which the desirable purpose of children’s interaction with artificial intelligence (AI) systems is children's growth. The article perceives AI systems with machine-learning components as having a recursive element when interacting with children. They can learn from an encounter with children and incorporate data from interaction, not only from prior programming. Given the purpose of growth and this recursive element of AI, the article argues for distinguishing the interpretation of bias within the artificial intelligence (AI) ethics and responsible AI discourse. Interpreting bias as a preference and distinguishing between positive (pro-diversity) and negative (discriminative) bias is needed as this would serve children's healthy psychological and moral development. The human-centric AI discourse advocates for an alignment of capacities of humans and capabilities of machines by a focus both on the purpose of humans and on the purpose of machines for humans. The emphasis on mitigating negative biases through data protection, AI law, and certain value-sensitive design frameworks demonstrates that the purpose of the machine for humans is prioritized over the purpose of humans. These top–down frameworks often narrow down the purpose of machines to do-no-harm and they miss accounting for the bottom-up views and developmental needs of children. Therefore, applying a growth model for children-AI interactions that incorporates learning from negative AI-mediated biases and amplifying positive ones would positively benefit children’s development and children-centric AI innovation. Consequently, the article explores:What challenges arise from mitigating negative biases and amplifying positive biases in children-AI interactions and how can a growth model address these?To answer this, the article recommends applying a growth model in open AI co-creational spaces with and for children. In such spaces human–machine and human–human value alignment methods can be collectively applied in such a manner that children can (1) become sensitized toward the effects of AI-mediated negative biases on themselves and others; (2) enable children to appropriate and imbue top-down values of diversity, and non-discrimination with their meanings; (3) enforce children’s right to identity and non-discrimination; (4) guide children in developing an inclusive mindset; (5) inform top-down normative AI frameworks by children’s bottom-up views; (6) contribute to design criteria for children-centric AI. Applying such methods under a growth model in AI co-creational spaces with children could yield an inclusive co-evolution between responsible young humans in the loop and children-centric AI systems.

Through the exponential growth in digital devices and computational capabilities, big data technologies are putting pressure upon the boundaries of what can or cannot be considered acceptable from an ethical perspective. Much of the literature on ethical issues related to big data and big data technologies focuses on separate values such as privacy, human dignity, justice or autonomy. More holistic approaches, allowing a more comprehensive view and better balancing of values, usually focus on either a design-based approach, in which it is tried to implement values into the design of new technologies, or an application-based approach, in which it is tried to address the ways in which new technologies are used. Some integrated approaches do exist, but typically are more general in nature. This offers a broad scope of application, but may not always be tailored to the specific nature of big data related ethical issues. In this paper we distil a comprehensive set of ethical values from existing design-based and application-based ethical approaches for new technologies and further focus these values to the context of emerging big data technologies. A total of four value lists were selected for this. The integrated list consists of a total of ten values: human welfare, autonomy, non-maleficence, justice, accountability, trustworthiness, privacy, dignity, solidarity and environmental welfare. Together, this set of values provides a comprehensive and in-depth overview of the values that are to be taken into account for emerging big data technologies.