AI systems are solving real-world challenges and transforming industries, but there are serious concerns about how responsibly they operate on behalf of the humans that rely on them. Many ethical principles and guidelines have been proposed for AI systems, but they're often too 'high-level' to be translated into practice. Conversely, AI/ML researchers often focus on algorithmic solutions that are too 'low-level' to adequately address ethics and responsibility.
The broad accessibility of AI tools means there is a massive need for good governance both by AI providers and the organizations implementing AI systems in their products.
The Minnesota House Early Childhood Finance and Policy committee met to hear presentations and a report on early childhood family education and governance at 8:30am. The discussion was to help inform language for HF2231 (Pinto) on early childhood family education provisions. It was also to inform the committee on various governance models and approaches for […]