It is now well established that algorithms are transforming our economy, institutions, social relations and ultimately our society. This paper explores the question – what is the role of law in the algorithmic society? We draw on the law-jobs theory of Karl Llewellyn and on William's Twining refinement of Llewellyn's work through the perspective of a thin functionalism to have a better understanding of what law does in this new context. We highlight the emergence of an algorithmic law, as law performs jobs such as the disposition of trouble-cases, the preventive channelling and reorientation of conduct and expectations, and the allocation of authority in the face of algorithmic systems. We conclude that the law-jobs theory remains relevant to understanding the role of law in the algorithmic society, but it is also challenged by how algorithms redefine who does or should do what law-jobs, and how they are done.

Launched in April 2018, the Association of Southeast Asian Nations' Smart Cities Network (ASCN) initiative raises important issues regarding the tensions between achieving smart city objectives on the one hand and protection of human rights on the other. The aim of this paper is to explore these tensions using a Knowledge Commons Framework analysis. I first analyse the three key pillars of the ASCN pilot city knowledge commons – knowledge resources, community attributes and governance ‘rules in use’ – using human rights criteria. I the apply the lessons of this analysis to two fundamental aspects of human experience in smart city contexts – mobility through transport systems and access to essential services through energy supply.

This paper examines the rise of algorithmic systems – that is, systems of data-driven governance (and social-credit-type) systems – in the form of ratings systems of business respecting human rights responsibilities. The specific context is rating or algorithmic systems emerging around national efforts to combat human trafficking through so-called Modern Slavery and Supply Chain Due Diligence legal. Section 2 provides a brief contextualisation of the problems and challenges of managing compliance with emerging law and norms against forced labour and, in its most extreme forms, modern slavery. Section 3 examines the landscape of such algorithmic private legal systems as it has developed to date in the context of forced labour ratings systems. There is a focus on the connection between the power to impose the normative basis of data analytics and the increasingly tightly woven-in connection between principal actors in this endeavour.

Different organisations recently published reports identifying the challenges and potential solutions to ensure privacy in blockchain platforms. The proposed solutions frequently emphasise the role of privacy-compliance technologies to be incorporated into the blockchain design. Often, these solutions imply a techno-regulatory approach, ignoring that the level of privacy implemented in a blockchain involves legal and policy choices, disregarding the need to implement human participation and contestability in these platforms. Against this backdrop, this paper proposes to examine how privacy-compliance technologies can incorporate human participation and contestability: first, resorting to the interdisciplinary literature to examine how technological design could balance privacy with human oversight; second, discussing the challenges to ensure ex post contestability for aggrieved data subjects; third, examining the difficulties in identifying liable parties in a blockchain platform. The current disregard of the social and human element risks undermining the role of privacy-compliance technologies in the blockchain.

In an era of global sanitary, economic and ecological crisis, beliefs in the predictive power of artificial intelligence (AI) progressively penetrate the legal and political spheres, in search of new ways to anticipate and govern the future. In this context, it is critical to understand the idiosyncratic nature of the interplay between governance and algorithmic logics of prediction. This contribution discusses how the association between governance and AI makes the future knowable in the present and shapes a programmatic way of formalising, justifying and deploying action in the here and now. We focus on three principles of institutional mobilisation in the face of uncertainty and indeterminacy: precaution, pre-emption and preparedness, each of which is affected by the use of AI relying on so-called ‘real-time predictions’. Drawing from risk theory and Science and Technology Studies, we argue that the current convergence between AI and governance is shaping a new sociotechnical imaginary, promoting a distinctive conception of life and of the future in the age of the Anthropocene.