The panellists delved into the existing approaches to AI regulation, highlighting a fundamental divide between the principles-based approach adopted by the United States and the rules-based approach embraced by the European Union. Recognizing that AI is currently at an inflection point, the panel acknowledged the difficulty in determining which regulatory strategy will best balance the imperative for AI innovation with the paramount concern for safety and ethical considerations.

The discussion emphasised that, despite the emergence of new AI technologies like generative AI, existing responsible AI principles remain pertinent. However, the panellists stressed the need for practical tools and methodologies to effectively implement these principles in real-world applications.

Panellists underscored the pivotal role of downstream developers in the responsible implementation of AI. The discussion highlighted the need for these developers to actively engage with and incorporate responsible AI principles into their work.

Panellists highlighted the significance of diversity, both in thought and people, when evaluating AI use cases. They emphasised that diverse perspectives contribute to a more comprehensive understanding of potential ethical concerns and benefits. Simultaneously, the panel cautioned against the current shortcomings in AI auditing, citing a lack of common standards as a hindrance to effective evaluation.

Panellists stressed the importance of maintaining transparency in AI systems, as the regulatory environment for AI remains uncertain. They underscored that transparency not only helps mitigate potential harms associated with AI but also plays a critical role in building public trust.