What is a key aspect of the risk-based approach in the EU's AI regulation passed in June 2023?

Question

BlackTom AI · Accepted Answer

When evaluating statements about the EU's risk-based AI regulation adopted in June 2023, we start by identifying the core principle: higher risk AIs face stricter requirements, while lower-risk uses have lighter obligations. 
Option 1: 'It requires AI developers and users to comply with certain obligations or exit the EU market.' This aligns with the regulation’s emphasis on achieving compliance through specific obligations (transparency, governance, risk management, conformity assessments) and includes a potential market exit for non-compliant entities, reflecting a strong enforcement framework. 
Option 2: 'It avoids any form of enforcement for active AI systems.' This is inconsistent with a risk-based approach that explicitly links requirements to risk levels and imposes enforceable obligations; avoiding enforcement would undermine the regulatory intent and the risk-based model. 
Option 3: 'It prioritizes the development of AI systems regardless of potential risk factors.' A core feature of the risk-based approach is to tailor obligations to risk, meaning higher-risk systems face more stringent controls, not an unfettered push to develop regardless of risk. 
Option 4: 'It absolves AI developers from the responsibility of demonstrating commitment to risk reduction.' The regulation does not absolve developers of responsibility; on the contrary, it requires demonstrable risk management, documentation, and accountability, making this option incorrect. 
Overall, the statements should be weighed against the regulation’s mechanism: risk categorization, obligations proportional to risk, and potential consequences for non-compliance. The first option coherently reflects that framework, whereas the other options misstate enforcement, risk sensitivity, or responsibility assumptions.

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What is a key aspect of the risk-based approach in the EU's AI regulation passed in June 2023?

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