Industry representatives shared insights on implementing transparency in AI systems. Daphne Tapia from ImiSight stressed the importance of explainability in AI-powered image intelligence, while Pini Usha from Buffers.ai highlighted the need for clear insights in AI-driven inventory optimization. Matan Noga from Corsight AI discussed facial recognition technology's compliance with privacy laws, and Alex Zilberman from Chamelio emphasized human oversight in AI-powered legal tools. The panel underscored the urgency of AI explainability as regulators seek stricter oversight, advocating for collaboration between academia, regulators, and industry to ensure AI remains fair, accountable, and transparent.
Key takeaways:
- Experts from academia, industry, and regulatory backgrounds discussed the importance of AI explainability for transparency and public trust.
- ISO 42001 provides a framework for responsible AI governance, balancing innovation with accountability.
- AI companies emphasize the need for transparency and human oversight to ensure trust and compliance in AI-driven systems.
- There are significant differences in AI regulations between the US and Europe, with Europe focusing more on privacy and ethical considerations.