Causal Artificial Intelligence, potential AI pitfalls, getting executive buy-in
Nov 15, 2023
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John K Thompson, co-author of "Causal Artificial Intelligence" and Global Head of AI at EY, shares insights from his extensive career in the field. He delves into the evolution of AI, emphasizing the importance of integrating various AI types for strategic decision-making. John discusses building scalable generative AI infrastructure and identifies common pitfalls, including the need for executive support. He highlights the dangers of a 'set and forget' approach and stresses the importance of collaborative ownership in AI deployment to align with business objectives.
Causal AI provides a deeper understanding of data outcomes by identifying underlying reasons, crucial for effective business decision-making.
Securing executive buy-in and fostering a supportive organizational culture are essential for the successful deployment of AI initiatives.
Deep dives
John K. Thompson's Career and Expertise
John K. Thompson has dedicated 37 years of his career to data and analytics, emphasizing his belief that understanding data is crucial for business efficiency. His extensive experience includes developing the first neural network utility at IBM and leading the AI group at CSL Bearing, a major biopharmaceutical company. Thompson's dual perspective as both a technology builder and practitioner enhances his insights into using data effectively in various industries. His passion for innovation drives him to continually seek advancements in data analytics, including the emerging field of causal AI.
The Emergence of Causal AI
Causal AI is gaining significance as it addresses the underlying reasons behind data outcomes, distinguishing itself from traditional AI that focuses primarily on predictions. Thompson recognized the potential of causal AI before it became a mainstream topic, advocating for its relevance in understanding business processes and decision-making. He collaborated with his co-author Judith Hurwitz to bring this idea to fruition in their book, which has resonated with audiences as it tackles the modern-day need for businesses to adopt AI strategies. The timing of their work aligns with the growing urgency for organizations to integrate AI into their operational frameworks.
Key Pillars of Artificial Intelligence
Thompson identifies three core pillars of artificial intelligence: traditional AI for predictions, generative AI for creating responses, and causal AI for understanding the reasons behind outcomes. Traditional AI involves techniques like classification and neural networks, while generative AI allows for the formulation of tailored narratives based on user context, enabling diverse communication strategies. Causal AI aims to offer deeper insights by analyzing data and identifying the causal relationships that drive results. The integration of all three pillars is paramount for businesses seeking to craft comprehensive strategies that enhance customer engagement and operational efficiency.
Challenges and Solutions in Implementing AI
Thompson highlights the critical importance of organizational culture and executive buy-in in successfully deploying AI initiatives. Traditional AI often encounters issues when organizations fail to adapt business practices based on analytical insights, leading to wasted investments. Generative AI poses challenges related to content accuracy, where outdated materials can yield misleading results; thus, ongoing content management is necessary. In causal AI, the complexity of the technology can deter adoption, reinforcing the need for cross-departmental collaboration to ensure effective implementation and continuous evaluation of AI systems.
John K Thompson is co-author of "Causal Artificial Intelligence: The Next Step in Effective Business AI" and Global Head of Artificial Intelligence (AI) at EY.
John's career path went from being an assembler programmer, to creating the first neural network utility at IBM, and now running the AI group at Ernst & Young. We'll unfold the pages of his acclaimed book, Causal Artificial Intelligence, and gain insights into his fascinating writing process. A relentless seeker of the 'why' behind data and analytics, John's insights are sure to fuel your curiosity.
Fasten your seat belts as we navigate through the multifaceted world of artificial intelligence. With the rise of AI, we are looking at a portfolio approach, focusing on several types such as generative and causal AI. Understand how these AI types generate context-specific responses, and the role of retrieval augmented generation in enhancing AI models. We'll also uncover how John masterly built a production generative AI infrastructure for UI, and some smart ways to sidestep pitfalls while implementing AI.
We examine how AI can be a game changer for businesses. John delivers invaluable advice on team collaboration, secure data management, and the crucial link between data, analytics, and measurable business outcomes. In an era where AI is revolutionizing industries, John's practical insights are the compass you need to chart a successful course.
What's New In Data is a data thought leadership series hosted by John Kutay who leads data and products at Striim. What's New In Data hosts industry practitioners to discuss latest trends, common patterns for real world data patterns, and analytics success stories.
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