As automation from IoT, AI and robotics reshapes incomes, the paper proposes tying social security contributions to technology-generated income to shore up social protection—and warns that implementing such a scheme will face measurement, institutional and political hurdles.

Paper: IoT, artificial intelligence, cloud computing and robotics and the contributory principle on social security Author: Marco António Cabeçais de Carvalho Journal: AI and Ethics (2026) 6:213 — https://doi.org/10.1007/s43681-026-01045-y

Main Finding

The paper proposes an "Autonomous Social Contribution" (ASC) levied on income or property related to IoT, AI, cloud computing and robotics as a sustainable funding mechanism for social security systems threatened by automation-driven declines in labor income. When technology-generated income can be determined, the ASC would be collected via the existing VAT system; where income is not determinable (e.g., many embedded IoT devices), the ASC would be levied as a property-type tax.

Key Points

• Technological context: rapid diffusion of IoT + AI + cloud + robotics is transforming production, services and labour markets (many concrete examples: Flippy, Tally, Stretch, Spot); estimates cited for billions of connected devices by 2025–2034.
• Problem statement: automation reduces wage income and thus weakens traditional social security funding based on payroll contributions; ageing populations exacerbate sustainability risks and potential violations of the right to social security.
• Existing tax landscape: internet-access taxation has been restricted (e.g., US Internet Tax Freedom Act); Digital Services Taxes (DSTs) and most robot-tax proposals to date do not directly fund social security.
• Review of prior proposals: surveys Pigouvian-style robot taxes, higher VAT on robots, reduced tax incentives for automation, imputed-salary approaches (notably two related proposals [85,86]) and debates over robot legal personhood; notes limited adoption (e.g., Korea reduced automation investment deductions; Spain debated but did not implement compulsory robot contributions).
• Core policy proposal: ASC — a contributory charge tied to technology-generated value that (a) uses VAT mechanisms where income/transactions are observable, and (b) acts as a property tax when high-value systems do not generate identifiable income.
• Rationale: preserve contributory principle of social security and maintain financing neutrality as labor is displaced by capital/automation.
• Caveats noted by author: possible negative static or dynamic effects of robot taxation (risk of reduced investment or slower productivity growth), administrative and cross-border complexity, need for careful design.

Data & Methods

• Method: conceptual/legal-policy analysis and literature review. The paper synthesizes:
  • Historical and technical background on the Internet, IoT architectures and cloud computing;
  • Case examples of robotics and IoT deployments across sectors;
  • Review of academic and policy literature on robot taxes, DSTs, and social security financing.
• Evidence: secondary sources and cited estimates (device counts, firm examples, existing tax proposals and legal instruments). No original empirical estimation or econometric modelling is presented.
• Analytical approach: normative policy design grounded in contributory-principle arguments, supplemented by comparative review of national proposals and international policy constraints.

Implications for AI Economics

• Fiscal dynamics and social protection:
  • The ASC frames automation as a taxable source of social-insurance funding; economists should quantify the size of the “technology-generated” taxable base to assess revenue potential and fiscal sustainability.
  • Research needed on incidence: who ultimately bears the ASC (firms, consumers, owners of capital) and how it interacts with wages, employment and product prices.
• Tax design and efficiency:
  • Practical design questions: defining taxable events, measuring value produced by embedded AI/IoT, avoiding double taxation, setting rates to balance revenue and investment incentives.
  • Use of VAT channels is administratively attractive but raises issues of attribution across platforms and jurisdictions; property-style levies raise valuation and enforcement challenges.
• Distributional and labour-market effects:
  • Model short- and long-run labor reallocation effects, consider complementarity vs substitution between workers and automation, and evaluate how ASC revenues should be targeted (unemployment insurance, pensions, retraining).
• International coordination:
  • Cross-border provision of cloud/AI services implies risk of tax base erosion and double taxation; global or multilateral agreements (or DST-like coordination) may be required.
• Innovation and growth trade-offs:
  • Evaluate dynamic effects: could an ASC slow automation adoption and productivity growth, or could revenues fund retraining and social insurance that support long-run labor supply and demand?
• Recommended empirical work:
  • Estimate taxable base (revenues/profits attributable to automation/AI/IoT) and plausible ASC revenue streams.
  • Simulate macro and distributional outcomes under alternative ASC implementations (VAT surcharge, property tax, imputed-salary contributions).
  • Assess administrative feasibility (measurement, reporting, cross-border enforcement) and compliance costs.

Limitations of the paper: normative proposal without empirical revenue estimates or formal modelling of economic incidence and growth effects. For AI economics research and policy evaluation, the next steps are quantitative revenue estimates, incidence analysis, and international policy designs to minimize distortions while protecting social insurance finances.