<p>Within the data-protection-derived legal and governance frameworks that regulate algorithmic systems (the GDPR, the EU AI Act, and the principlist codes that track them), consent and individual authorisation are the load-bearing mechanism of legitimation and redress, and the same frame organises the remedial debate over large-scale algorithmic welfare systems, the Indian Aadhaar architecture being the paradigm case. This paper argues that for a distinctive class of such systems consent is not merely practically strained but conceptually misplaced, and develops a positive alternative. Its central contribution is the concept of constitutive dependence: a condition in which an algorithmic system does not constrain or coerce agents recognised as rights-bearers but produces their operative standing as subjects of recognition and entitlement. Where it obtains, the standpoint of refusal on which consent depends is foreclosed by the system’s algorithmic architecture, which enforces its criteria of recognition without the discretionary judgement by which a human-mediated bureaucracy can recognise the manifestly entitled. Locating the condition within the recognition-theoretic tradition (Honneth, Fraser, Butler; Waelen) as a distinctively infrastructural form of misrecognition, the paper articulates the Constitutive Obligation Principle: where an institution produces its subjects’ operative standing as entitlement-bearers, its legitimacy depends not on their authorisation but on discharging non-waivable obligations of legibility, non-abandonment, and remediation. Developed through the Aadhaar case and offered as a framework for the algorithmic welfare state more broadly, the argument reads Aadhaar not as an outlier but as an early instance of an architectural form toward which algorithmic governance is converging.</p>

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Beyond consent: algorithmic welfare, constitutive dependence, and the limits of liberal AI ethics

  • Abhinav Saxena

摘要

Within the data-protection-derived legal and governance frameworks that regulate algorithmic systems (the GDPR, the EU AI Act, and the principlist codes that track them), consent and individual authorisation are the load-bearing mechanism of legitimation and redress, and the same frame organises the remedial debate over large-scale algorithmic welfare systems, the Indian Aadhaar architecture being the paradigm case. This paper argues that for a distinctive class of such systems consent is not merely practically strained but conceptually misplaced, and develops a positive alternative. Its central contribution is the concept of constitutive dependence: a condition in which an algorithmic system does not constrain or coerce agents recognised as rights-bearers but produces their operative standing as subjects of recognition and entitlement. Where it obtains, the standpoint of refusal on which consent depends is foreclosed by the system’s algorithmic architecture, which enforces its criteria of recognition without the discretionary judgement by which a human-mediated bureaucracy can recognise the manifestly entitled. Locating the condition within the recognition-theoretic tradition (Honneth, Fraser, Butler; Waelen) as a distinctively infrastructural form of misrecognition, the paper articulates the Constitutive Obligation Principle: where an institution produces its subjects’ operative standing as entitlement-bearers, its legitimacy depends not on their authorisation but on discharging non-waivable obligations of legibility, non-abandonment, and remediation. Developed through the Aadhaar case and offered as a framework for the algorithmic welfare state more broadly, the argument reads Aadhaar not as an outlier but as an early instance of an architectural form toward which algorithmic governance is converging.