AI sector reflections on community-driven decision making
In 2019, a social uprising in Chile ignited a nation-wide popular constitutional movement, engaging communities from the Atacama Desert to the Patagonian ice field. This movement, reminiscent of a wider trend linking systemic transformations to deliberative processes and mass mobilisation in Latin America and the Caribbean, offers valuable lessons for the AI sector.
The protests re-politicised entire segments of the population, mobilising for rights denied or not achieved through political processes. The demonstrations led to a constituent moment, opening new political horizons for future governance. Claudia Heiss, a sociologist, noted a break between social norms and overly rigid institutions inherited from the dictatorship during the protests.
The Chilean uprising exemplifies how legitimacy in governance emerges from inclusive, grassroots-driven deliberation and mobilisation. This approach can counteract technocratic, opaque decision-making. Translating these principles into AI regulation means fostering participatory mechanisms that prioritise the voices of those most affected by AI’s ethical, social, and economic impacts, thus improving accountability and trust in AI systems.
Community-led practices in mass mobilisation and deliberation can provide valuable lessons for regulating AI. Deliberative democracy and legitimacy are built through open forums, assemblies, and direct participation, fostering legitimacy as decisions emerge from collective reasoning rather than top-down imposition. Applying such models to AI regulation would mean creating spaces where users, workers, and vulnerable groups affected by AI can engage meaningfully in shaping rules and norms.
Mass mobilisation can elevate marginalised concerns to the national stage, pressuring authorities to respond. Involving communities in AI oversight can surface issues such as algorithmic bias, surveillance, or labour disruption, which may otherwise be overlooked by experts or corporations. Legitimacy arises from recognising and integrating these concerns into regulatory frameworks.
Transparency and explainability are crucial for affected individuals to understand and challenge AI decisions that impact them. Community-led deliberations can help shape standards for explainability grounded in real-world comprehension and needs rather than purely technical metrics.
Bridging digital divides is essential to ensure that affected populations can participate in AI regulation. Legal experts note that democratising AI benefits requires addressing digital divides to avoid reinforcing inequalities.
Engaging the public is crucial for governing AI, especially building legitimacy among communities most affected by AI technology. AI governance needs to be transformed from the ground up, starting with community care and dismantling hegemonic narratives.
While the rejection of the proposals in the 2022 confirmation referendum cannot be attributed to a failure of process design, it underscores the necessity of building trust and legitimacy through inclusive participation. AI regulation efforts may benefit from engaging self-organised sectors and grassroot initiatives to meaningfully reflect public views and interests.
The author(s) of this piece do not necessarily reflect the views of the website.
Technology in AI regulation could learn from the Chilean uprising's approach to mobilization and deliberation, as these grassroots-driven processes have the potential to elevate marginalized concerns and surface issues such as algorithmic bias or labor disruptions that may otherwise be overlooked. Politically, the protests in Chile re-politicized entire segments of the population, demonstrating how public engagement can lead to a constituent moment and open new political horizons.
