There is no AI without data, and that to be trustworthy, AI requires trustworthy data. An obvious manifestation the Data Divide is the separation between the data "have" and "have not" organizations. Put another way, organizations possessing relevant, clean data sets stored in modern, AI-addressable data technologies enjoy a massive advantage in what AI can do for them, and in how quickly they can bring it to bear in service of the challenges they face. This is fast becoming a critical asset for organizations. The next couple of years will see a stark separation in fortunes for these have and have not organizations.

In this conversation, Andrew Welch and Steve discuss the evolving landscape of AI, particularly focusing on the importance of trustworthy AI, governance, and the role of data. They explore the challenges faced by organizations in adopting AI technologies, the concept of vibe coding, and the differing perspectives on AI, including optimism and skepticism. The discussion highlights the need for a balanced approach to AI implementation, emphasizing the importance of technical expertise and the potential pitfalls of relying solely on AI without proper understanding and governance.

Mark Smith and Andrew Welch dive into their takeaways from the Dynamics Minds conference, exploring how artificial intelligence is reshaping the tech landscape. They break down public sentiment into three distinct mindsets: the hopeful optimists, the skeptical deniers, and those resistant to change - the 'angry camp.' Their conversation weaves through themes of technological inevitability, the quirky idea of 'vibe coding,' and the critical need to evolve alongside emerging tools. Along the way, they share nostalgic stories from their early days in tech, offering a personal lens on how far the industry has come - and where AI might take us next.

In this episode, Ana Welch and Andrew Welch discuss the recent AI for Good Global Summit, exploring the intersection of technology, law, and culture. They highlight the importance of regulation in fostering innovation while addressing the ethical implications of AI. The conversation delves into the cultural biases inherent in AI training and the need for collaboration between technologists and legal experts. The hosts reflect on the rapid technological advancements and their impact on society, emphasizing the need for responsible AI development.