Recent advances in AI raise questions about its social impacts and implementation. In response, governments and public administrations seek to develop adequate governance frameworks to mitigate risks and maximize the potential of AI development and use. Such work largely deals with questions of how challenges and risks should be managed, which values and goals should be pursued, and through which institutional mechanisms and principles these goals could be achieved. In this paper, we conduct a systematic review of the existing literature on the development of AI governance for public administration. The article describes principles and means by which public administrations could guide and steer AI developers and users in adopting ethical and responsible practices. The reviewed literature indicates a need for public administrations to move away from top-down hierarchical governance principles and adopt forms of inclusive policy-making to ensure the actionability of ethical and responsibility principles in the successful governance of AI development and use. By combining the results, we propose a CIIA (Comprehensive, Inclusive, Institutionalized, and Actionable) framework that integrates the key aspects of the proposed development solutions into an ideal typical and comprehensive model for AI governance.

Human-centricity is considered a central aspect in the development and governance of artificial intelligence (AI). Various strategies and guidelines highlight the concept as a key goal. However, we argue that current uses of Human-Centered AI (HCAI) in policy documents and AI strategies risk downplaying promises of creating desirable, emancipatory technology that promotes human wellbeing and the common good. Firstly, HCAI, as it appears in policy discourses, is the result of aiming to adapt the concept of human-centered design (HCD) to the public governance context of AI but without proper reflection on how it should be reformed to suit the new task environment. Second, the concept is mainly used in reference to realizing human and fundamental rights, which are necessary, but not sufficient for technological emancipation. Third, the concept is used ambiguously in policy and strategy discourses, making it unclear how it should be operationalized in governance practices. This article explores means and approaches for using the HCAI approach for technological emancipation in the context of public AI governance. We propose that the potential for emancipatory technology development rests on expanding the traditional user-centered view of technology design to involve community- and society-centered perspectives in public governance. Developing public AI governance in this way relies on enabling inclusive governance modalities that enhance the social sustainability of AI deployment. We discuss mutual trust, transparency, communication, and civic tech as key prerequisites for socially sustainable and human-centered public AI governance. Finally, the article introduces a systemic approach to ethically and socially sustainable, human-centered AI development and deployment.

No abstract

Grand social challenges, such as type 2 diabetes (T2D), are increasing, which creates sustainability problems for health care service systems. To reduce socio-economic burdens, changes are required in the socio-technical system. However, there is an uncertainty of the most cost-effective policy action that can create sustainability while providing health benefits. To find potential solutions to these challenges, the multi-level perspective (MLP) and health economic decision modelling was used to study socio-technical change and project potential health economic consequences of different scenarios. The study focuses on creating a vision pathway for reducing T2D in Finland. In total, 23 interviews were carried out and the results were analyzed utilizing the MLP model. As a result, five themes towards prevention of T2D were identified. Digitalization was found to be a cross-cutting theme for preventing T2D and was thus taken as the object of study and the main focus of this paper. As a result, this paper reports on the opportunities and barriers for using digital tools in a transition towards T2D prevention. A health economic decision modelling revealed that the highest expected savings could be obtained by prioritizing prevention programs based on T2D risk. Finally, the model was converted into a web-based online tool by combining vision pathway, transition-focused storylines and forward-looking health economic scenario analysis to give the policy makers an overall picture of the needed societal changes and support the impact assessment of alternative policies in a case of T2D prevention in Finland.