Liability Framework for AI Errors In CBDC: A Comparative Socio-Legal Analysis

Most of the nation's now engage in developing their own versions of Central Bank Digital Currencies (CBDCs).The integration of Artificial Intelligence (AI) with CBDC helps in detection, validation execution.But it has its inherent biases.The researchers offer a comparative socio-legal perspective on fixing liability that arises out of this.AI CBC pilot programs across 4 jurisdictions have been analysed, i.e., India's e-Rupee, the EU's Digital Euro, China's e-CNY, and the US' Federal Reserve initiatives.Doctrinal method of review of major laws like the EU AI Act, India's IT Act, and various reports.A comparative analysis of legislation and its approaches, including fault-based models, strict liability, and state-led systems, has been conducted.For example, Chinese is more like a central system wherein AI is in a controlled setup.Despite this almost 15% to 20% problem persists in how consumers get remedies.Still, the question remains who takes the blame.A combined liability system with regular AI checks seems to be the answer as of now.Global standardisation needs to be fair, open, and policy-based for the CBDC-AI to work.