most citedThe AI Regulatory Readiness Index ARRI: Assessing Cross-Jurisdictional Legal Preparedness for AI in Telecommunications

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7 papers

cs.CY20261 cited

The AI Regulatory Readiness Index ARRI: Assessing Cross-Jurisdictional Legal Preparedness for AI in Telecommunications

Avinash Agarwal, Peeyush Agarwal, Manisha J. Nene

As Artificial Intelligence becomes increasingly embedded in critical telecommunications infrastructure, existing legal frameworks remain ill-equipped to address the distinct risks…

cs.CY2026

A federated architecture for sector-led AI governance: lessons from India

Avinash Agarwal, Manisha J. Nene

Purpose: India has adopted a vertical, sector-led AI governance strategy. While promoting innovation, such a light-touch approach risks policy fragmentation. This paper aims to pro…

cs.CY2026

Incorporating AI incident reporting into telecommunications law and policy: Insights from India

Avinash Agarwal, Manisha J. Nene

The integration of artificial intelligence (AI) into telecommunications infrastructure introduces novel risks, such as algorithmic bias and unpredictable system behavior, that fall…

cs.CY2025

A five-layer framework for AI governance: integrating regulation, standards, and certification

Avinash Agarwal, Manisha J. Nene

Purpose: The governance of artificial iintelligence (AI) systems requires a structured approach that connects high-level regulatory principles with practical implementation. Existi…

cs.CY2025

Enhancements for Developing a Comprehensive AI Fairness Assessment Standard

Avinash Agarwal, Mayashankar Kumar, Manisha J. Nene

As AI systems increasingly influence critical sectors like telecommunications, finance, healthcare, and public services, ensuring fairness in decision-making is essential to preven…

cs.CY2025

Standardised schema and taxonomy for AI incident databases in critical digital infrastructure

Avinash Agarwal, Manisha J. Nene

The rapid deployment of Artificial Intelligence (AI) in critical digital infrastructure introduces significant risks, necessitating a robust framework for systematically collecting…