The concept of algocracy, or governance by algorithm, is becoming increasingly prevalent as algorithmic and machine learning systems are implemented in government and public sectors. This form of governance utilizes AI, blockchain, and algorithms to make decisions. While there are potential benefits in terms of efficiency, there are also concerns regarding transparency, bias, and the concentration of power. Public opinion on algocracy varies across European countries, with some support for AI in decision-making.
Are we heading towards an algocracy?
The rise of algorithmic and machine learning systems in the governmental and public sectors has raised questions about the possibility of governance by algorithm, or an “algocracy.”
What is algocracy?
Algocracy is a form of algorithm-driven governance that applies AI, blockchain, and algorithms to various aspects of law and society. It has evolved from using computers for primitive mathematical simulations to sophisticated self-learning models.
Early examples of algocracy
Algocracy can trace its origins back to the 1960s with the proposal of a computer network for algorithmic governance in Moscow. Projects like Chile’s Cybersyn in the 1970s and the UK’s LEGOL and US’s TAXMAN projects in the same era laid the foundation for algorithmic decision-making. The concept of algocracy was introduced in academic discourse in 2006 by A. Aneesh.
Public sector experimentation
Government agencies have been increasingly utilizing algorithmic decision-making, AI, and machine learning. This includes the adoption of these technologies in the US federal sector, with 45% of agencies experimenting with AI and ML tools by 2020. However, there have been concerns about bias, discrimination, and misuse of algorithms in areas such as healthcare, criminal justice, and welfare.
Algorithmic justice and law enforcement
Algorithmic decision-making has also been applied in justice and law enforcement. Examples include the COMPAS system in the US, software aiding asset division during divorce proceedings in Australia, and virtual AI judges in China’s internet courts. However, these systems have faced legal challenges and criticism for potential biases and lack of transparency.
Benefits and critiques of algocracy
Algocracy can bring efficiency to decision-making processes, particularly in resource-challenged departments. However, algorithms and machine learning systems are not always objective and can be unpredictable and biased. Transparency efforts have been made through open-sourcing algorithms, but there are risks of manipulation and adversarial machine-learning techniques. There are also concerns about the potential manipulation of language and public opinion by AI, as well as the risk of centralization and control by authoritarian regimes.
Public opinion of algocracy
Public support for allowing AI to make significant national decisions varies across European countries. Disillusionment with political leaders can increase the public’s inclination towards artificial agents perceived as more reliable. AI models that incorporate public opinions could potentially hold governments accountable, but most examples of algocracy are currently illustrative of state rather than democratic decision-making.
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