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

The growth of online platforms is accompanied by the increasing use of automated agents. Despite being discussed primarily in the context of opinion manipulation, agents play diverse roles within platform ecosystems that raises the need for governance approaches that go beyond policing agents' unwanted behaviour. To provide a more nuanced assessment of agent governance, we introduce an analytical framework that distinguishes between different aspects and forms of governance. We then apply it to explore how agents are governed across nine platforms. Our observations show that despite acknowledging diverse roles of agents, platforms tend to focus on governing selected forms of their misuse. We also observe differences in governance approaches used by platforms, in particular when it comes to the agent rights/obligations and transparency of policing mechanisms. These observations highlight the necessity of advancing the algorithmic governance research agenda and developing a generalizable normative framework for agent governance.

Automated summary

The growth of online platforms has led to the increasing use of automated agents. While primarily discussed in the context of opinion manipulation, agents play diverse roles within platform ecosystems, necessitating governance approaches that go beyond monitoring agents' undesirable behavior. To provide a more comprehensive understanding of agent governance, an analytical framework is introduced to differentiate between different aspects and forms of governance. This framework is then applied to examine the governance of agents across nine platforms. The findings show that while platforms acknowledge the various roles of agents, they tend to focus on governing specific forms of misuse. Variations in governance approaches, particularly concerning agent rights/obligations and transparency of policing mechanisms, are also observed. These observations underscore the need for advancing research on algorithmic governance and developing a generalizable normative framework for agent governance.