Algorithmic governance: A modes of governance approach

Abstract

This article examines how modes of governance are reconfigured as a result of using algorithms in the governance process. We argue that deploying algorithmic systems creates a shift toward a special form of design‐based governance, with power exercised ex ante via choice architectures defined through protocols, requiring lower levels of commitment from governing actors. We use governance of three policy problems – speeding, disinformation, and social sharing – to illustrate what happens when algorithms are deployed to enable coordination in modes of hierarchical governance, self‐governance, and co‐governance. Our analysis shows that algorithms increase efficiency while decreasing the space for governing actors' discretion. Furthermore, we compare the effects of algorithms in each of these cases and explore sources of convergence and divergence between the governance modes. We suggest design‐based governance modes that rely on algorithmic systems might be re‐conceptualized as algorithmic governance to account for the prevalence of algorithms and the significance of their effects.

Limitations of trust and legitimacy in blockchain: exploring the effectiveness of decentralisation, immutability and consensus mechanisms in blockchain governance

“…Legally, DAOs are often unable to ensure effective consensus mechanisms and thus must fall back on traditional governance mechanisms to work (Minn, 2019, p. 142). This echoes the need for developing top-down, rule-based mechanisms to ensure effective algorithmic governance in other technological applications like sharing-economy platforms (Gritsenko and Wood, 2022, pp. 54–56).…”

“…Both decentralisation and immutability, core tenets of blockchain, have been repeatedly shown to be ambitions rather than reality (Zachariadis et al ., 2019, p. 113), as illustrated in this case and the case of DAOs more widely. The ex-post rationalisation of governance decisions shown in hard forks is in contrast to the ex-ante, design-based approach seen in other technological use cases, such as algorithms designed to combat disinformation in online media (Gritsenko and Wood, 2022, pp. 53–54).…”

Limitations of trust and legitimacy in blockchain: exploring the effectiveness of decentralisation, immutability and consensus mechanisms in blockchain governance

“…Legally, DAOs are often unable to ensure effective consensus mechanisms and thus must fall back on traditional governance mechanisms to work (Minn, 2019, p. 142). This echoes the need for developing top-down, rule-based mechanisms to ensure effective algorithmic governance in other technological applications like sharing-economy platforms (Gritsenko and Wood, 2022, pp. 54–56).…”

“…Both decentralisation and immutability, core tenets of blockchain, have been repeatedly shown to be ambitions rather than reality (Zachariadis et al ., 2019, p. 113), as illustrated in this case and the case of DAOs more widely. The ex-post rationalisation of governance decisions shown in hard forks is in contrast to the ex-ante, design-based approach seen in other technological use cases, such as algorithms designed to combat disinformation in online media (Gritsenko and Wood, 2022, pp. 53–54).…”

The Covid-19 Pandemic and The Future of Work

“…Algocratic governance refers to “programming schemes embedded in global software platforms that structure possible forms of work performance.” 29 It is seen as the crossroads of digitalization, datafication, and leadership style 30 . Algocratic organizations depend on software algorithms for work allocation, decision making, motivation, and rewards for work.…”

Not all who are bots are evil: A cross-platform analysis of automated agent governance

“…Such an expansion is essential for understanding the complex role of agents within platform ecosystems better, but also for tackling other challenges, such as (re)defining the rights of both human and non-human users and developing a generalizable normative framework for their governance. It is also crucial that this expanded agenda will take into consideration the impact of different contextual factors on agent governance, which is the matter that is increasingly acknowledged by the broader field of algorithmic governance research (Gritsenko and Wood, 2022), that prompts the need for more comparative research.…”

Limitations of trust and legitimacy in blockchain: exploring the effectiveness of decentralisation, immutability and consensus mechanisms in blockchain governance

“…Legally, DAOs are often unable to ensure effective consensus mechanisms and thus must fall back on traditional governance mechanisms to work (Minn, 2019, p. 142). This echoes the need for developing top-down, rule-based mechanisms to ensure effective algorithmic governance in other technological applications like sharing-economy platforms (Gritsenko and Wood, 2022, pp. 54–56).…”

“…Both decentralisation and immutability, core tenets of blockchain, have been repeatedly shown to be ambitions rather than reality (Zachariadis et al ., 2019, p. 113), as illustrated in this case and the case of DAOs more widely. The ex-post rationalisation of governance decisions shown in hard forks is in contrast to the ex-ante, design-based approach seen in other technological use cases, such as algorithms designed to combat disinformation in online media (Gritsenko and Wood, 2022, pp. 53–54).…”

The Covid-19 Pandemic and The Future of Work

“…Algocratic governance refers to “programming schemes embedded in global software platforms that structure possible forms of work performance.” 29 It is seen as the crossroads of digitalization, datafication, and leadership style 30 . Algocratic organizations depend on software algorithms for work allocation, decision making, motivation, and rewards for work.…”

Not all who are bots are evil: A cross-platform analysis of automated agent governance

“…Such an expansion is essential for understanding the complex role of agents within platform ecosystems better, but also for tackling other challenges, such as (re)defining the rights of both human and non-human users and developing a generalizable normative framework for their governance. It is also crucial that this expanded agenda will take into consideration the impact of different contextual factors on agent governance, which is the matter that is increasingly acknowledged by the broader field of algorithmic governance research (Gritsenko and Wood, 2022), that prompts the need for more comparative research.…”

Limitations of trust and legitimacy in blockchain: exploring the effectiveness of decentralisation, immutability and consensus mechanisms in blockchain governance

“…Legally, DAOs are often unable to ensure effective consensus mechanisms and thus must fall back on traditional governance mechanisms to work (Minn, 2019, p. 142). This echoes the need for developing top-down, rule-based mechanisms to ensure effective algorithmic governance in other technological applications like sharing-economy platforms (Gritsenko and Wood, 2022, pp. 54–56).…”

“…Both decentralisation and immutability, core tenets of blockchain, have been repeatedly shown to be ambitions rather than reality (Zachariadis et al ., 2019, p. 113), as illustrated in this case and the case of DAOs more widely. The ex-post rationalisation of governance decisions shown in hard forks is in contrast to the ex-ante, design-based approach seen in other technological use cases, such as algorithms designed to combat disinformation in online media (Gritsenko and Wood, 2022, pp. 53–54).…”

The Covid-19 Pandemic and The Future of Work

“…Algocratic governance refers to “programming schemes embedded in global software platforms that structure possible forms of work performance.” 29 It is seen as the crossroads of digitalization, datafication, and leadership style 30 . Algocratic organizations depend on software algorithms for work allocation, decision making, motivation, and rewards for work.…”

Not all who are bots are evil: A cross-platform analysis of automated agent governance

“…Such an expansion is essential for understanding the complex role of agents within platform ecosystems better, but also for tackling other challenges, such as (re)defining the rights of both human and non-human users and developing a generalizable normative framework for their governance. It is also crucial that this expanded agenda will take into consideration the impact of different contextual factors on agent governance, which is the matter that is increasingly acknowledged by the broader field of algorithmic governance research (Gritsenko and Wood, 2022), that prompts the need for more comparative research.…”