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The rush to understand new socio-economic contexts created by the wide adoption of AI is justified by its farranging consequences, spanning almost every walk of life. Yet, the public sector's predicament is a tragic double bind: its obligations to protect citizens from potential algorithmic harms are at odds with the temptation to increase its own efficiency -or in other words -to govern algorithms, while governing by algorithms. Whether such dual role is even possible, has been a matter of debate, the challenge stemming from algorithms' intrinsic properties, that make them distinct from other digital solutions, long embraced by the governments, create externalities that rule-based programming lacks. As the pressures to deploy automated decision making systems in the public sector become prevalent, this paper aims to examine how the use of AI in the public sector in relation to existing data governance regimes and national regulatory practices can be intensifying existing power asymmetries. To this end, investigating the legal and policy instruments asssociated with the use of AI for strenghtening the immigration process control system in Canada; "optimising" the employment services" in Poland, and personalising the digital service experience in Finland, the paper advocates for the need of a common framework to evaluate the potential impact of the use of AI in the public sector. In this regard, it discusses the specific effects of automated decision support systems on public services and the growing expectations for governments to play a more prevalent role in the digital society and to ensure that the potential of technology is harnessed, while negative effects are controlled and possibly avoided. This is of particular importance in light of the current COVID-19 emergency crisis where AI and the underpinning regulatory framework of data ecosystems, have become crucial policy issues as more and more innovations are based on large scale data collections from digital devices, and the real-time accessibility of information and services, contact and relationships between institutions and citizens could strengthen -or undermine -trust in governance systems and democracy.

Most of the definitions of a “smart city” make a direct or indirect reference to improving performance as one of the main objectives of initiatives to make cities “smarter”. Several evaluation approaches and models have been put forward in literature and practice to measure smart cities. However, they are often normative or limited to certain aspects of cities’ “smartness”, and a more comprehensive and holistic approach seems to be lacking. Thus, building on a review of the literature and practice in the field, this paper aims to discuss the importance of adopting a holistic approach to the assessment of smart city governance and policy decision making. It also proposes a performance assessment framework that overcomes the limitations of existing approaches and contributes to filling the current gap in the knowledge base in this domain. One of the innovative elements of the proposed framework is its holistic approach to policy evaluation. It is designed to address a smart city’s specificities and can benefit from the active participation of citizens in assessing the public value of policy decisions and their sustainability over time. We focus our attention on the performance measurement of codesign and coproduction by stakeholders and social innovation processes related to public value generation. More specifically, we are interested in the assessment of both the citizen centricity of smart city decision making and the processes by which public decisions are implemented, monitored, and evaluated as regards their capability to develop truly “blended” value services—that is, simultaneously socially inclusive, environmentally friendly, and economically sustainable.

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