Algorithmic Governance

Governance operations are increasingly relying on algorithmic systems to assist with everything from democratic processes and daily operations to critical life decisions, such as credit applications, hiring, and criminal sentencing. This growing dependence has given rise to the emerging field of Algorithmic Governance (AG), which systematically examines how social and economic processes are shaped by these algorithmic systems.

There are contrasting views on the impact of algorithmic governance. On one hand, proponents believe that algorithms have the potential to address systemic flaws in politics, such as bias, and to improve decision-making by overcoming limitations in human knowledge. On the other hand, critics warn that algorithms could amplify existing power imbalances and increase control by unaccountable entities, posing significant risks to society.

Algorithmic governance is distinct from the governance of algorithms (GA), which focuses on controlling and regulating algorithmic behavior. While both are related, AG specifically emphasizes the role and agency of algorithms in decision-making processes within existing governance structures, such as networks, hierarchies, and bureaucracies.

The current global debate around algorithmic governance is largely driven by legal and policy perspectives, often lacking a deep understanding of the technological developments and engineering solutions available in this space. Although there are significant technical research efforts in areas like algorithmic fairness, transparency, accountability, and adaptability, these initiatives often react to emerging issues and are limited to specific contexts. They do not always address the broader governance challenges posed by the widespread use of algorithms in society.

To effectively navigate the complexities of algorithmic governance, there is a pressing need for a unified intellectual framework that transcends disciplinary boundaries. This holistic approach is essential for providing thought leadership in this critical area, ensuring that the development and implementation of algorithmic systems are aligned with societal values and governance principles.