Spillover Effect Details
- Policy
-
EU AI Act
- Alternative
-
AI Accountability Training and Certification Program
- Dimension
- Health
- Criteria
-
- Patient outcomes improvement
- Time Frame
- 0
- Score
-
- PositiveImpact
- The AI Accountability Training and Certification Program (AATCP) could lead to enhanced competency among AI professionals, resulting in better adherence to ethical practices in healthcare AI applications. With improved training, AI systems could deliver safer and more effective health interventions, ultimately enhancing patient outcomes and building trust in AI's role in healthcare.
- NegativeImpact
- However, the program may fall short in addressing the immediate and critical compliance void left by current AI regulations. It might also lead to complacency among stakeholders, with reliance on training without robust enforcement of actual compliance measures. This could perpetuate existing biases in AI systems and lead to safety issues for patients, worsening healthcare outcomes in the interim.
- Description
- The AATCP proposes to empower AI developers and users in the EU with necessary training to ensure compliance with the EU AI Act, especially in healthcare. While fostering understanding may reduce compliance violations, three critical areas of failure are likely: first, the training may not keep pace with the rapid evolution of AI technology, rendering it outdated; second, reliance on self-certification may lead to a lack of accountability; and third, it risks prioritizing education over urgent needs for strict operational guidelines, potentially delaying necessary safeguards against harmful AI applications. Compared to alternatives like the AI Ethics and Impact Assessment Framework for SMEs, which address fundamental compliance needs more directly and could support broader public trust in AI, the AATCP appears to be a less effective approach. As such, it receives a score of 'bad' for its limited positive impact on current and future patient outcomes.