Argentina’s Ministry of Human Capital has launched the ‘Digital Twin’ initiative, an AI-based system intended to simulate potential impacts of social policies before implementation. According to the government, the project is part of broader efforts to use data analysis and predictive tools in public policy planning.
The system is designed to model scenarios related to areas including poverty, subsidies, and human capital development using large-scale datasets. Officials said the initiative could support more anticipatory and data-informed policymaking processes.
The announcement by President Javier Milei was followed by public criticism related to promotional materials associated with the initiative. Opposition representatives have requested additional information concerning the project’s legal basis, data usage, and privacy safeguards.
Privacy specialists and analysts also raised concerns about governance frameworks, data aggregation, and potential profiling risks. The government has not yet publicly detailed oversight mechanisms or specific data protection standards linked to the initiative.
Why does it matter?
Argentina’s Digital Twin project reflects a broader global shift towards using AI to simulate and predict social and economic outcomes, potentially reshaping how governments design and test public policy. If effective, such systems could improve efficiency by allowing policymakers to model interventions before implementation, reducing costly or ineffective decisions.
At the same time, the initiative raises significant governance and civil liberties concerns, particularly around large-scale data aggregation and the potential for algorithmic profiling of citizens.
Without clear transparency, oversight, and privacy safeguards, predictive governance tools risk shifting from policy optimisation instruments into systems that enable expanded state surveillance and reduced accountability.
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