Description: Today's best AIs often match human experts on routine tasks - but AI automation success requires skilled implementation. Nathan will present a field-tested, three-step method for automating cognitive work: (1) understanding what AI can do & choosing the right tasks, (2) documenting processes in the form of ""gold standard examples"", and (3) systematically optimizing AI performance – all using concrete examples from actuarial practice. Master this approach and amplify your own expertise by automating repetitive work with AI. Nathan Labenz, founder and former CEO of Waymark, is a technology entrepreneur and artificial intelligence analyst. With a background in science and an eye for innovation, Nathan led Waymark from its inception to its status as a trailblazer in generative AI-powered video creation. Currently, he hosts 'The Cognitive Revolution' podcast, where he explores the transformative impact of artificial intelligence on work, life, society, and culture. Through his conversations with notable builders, researchers, and investors, Nathan helps business, policy, and academic leaders stay up to date with AI developments and implications.

Description: This session will examine bias from a social science perspective. It will discuss the three types of systemic biases using the National Institute of Standards and Technology (NIST) model. The NIST model details the three types as historical bias, societal bias, and institutionalbias. The session will also provide several examples of each type to provide a framework for identifying the social structure of bias.

Description: The recent wave of innovation in GenAI has unlocked an entirely new category of AI applications. Whereas AI has traditionally focused on automation and predictions, LLM’s and Generative AI give us the opportunity to create AI applications that act as copilots. This emphasis on contelligence and empowering knowledge workers has already begun to change the way work is done. High expertise knowledge workers such as actuaries will be able to use this wave of AI Apps to make better decisions and dedicate more of their attention to the parts of the role that require domain expertise and judgement. Join Charles Morris, Microsoft’s Chief Data Scientist for Financial Services, as he talks about the latest advancements in this space and the opportunities it creates for expert knowledge workers. Charles Morris is the Chief Data Scientist for Financial Services at Microsoft. Charles has deep expertise in the financial services domain and works with many of the world’s leading asset managers, banks, insurance companies, and financial platforms to develop and execute their AI strategies.Currently, Charles is focused on applying Generative AI to financial services and advising many top financial institutions in building their own copilots and reimagining their businesses.Charles is a data scientist and machine learning engineer by profession and an expert in MLOps. Before joining Microsoft, Charles practiced data science, machine learning, and cloud engineering in the asset management industry. He has been a featured keynote speaker at several prestigious events and forums and is a highly sought after public speaker in the domain of AI and Innovation.

Description: Understanding how to effectively adopt AI is critical to staying competitive. This session will guide you through the five stages of AI adoption, with a deep dive into two key stages: Operational Optimization and Collaborative AI Integration. You will learn how to harness AI to streamline operations and boost efficiency, while also exploring the nuances of integrating AI in decision-making to enhance outcomes through human-AI collaboration.If you are seeking practical insights on maximizing AI's benefits while maintaining human oversight, this session will provide the tools and strategies to help you do just that—ensuring that your AI adoption journey is both effective and aligned with your business goals.

Description: Cluster modeling is emerging as a powerful technique to manage cloud costs and run time. It also enables quick responses to "what if" scenarios, and aids in attributing results between reporting cycles. In this webcast, we provide insight into cluster modeling, present case studies that focus on various key performance indicators and discuss the benefits and challenges to cluster modeling from an insurer’s perspective. We also discuss the considerations associated with moving from an on-prem based computing solution to a cloud-based approach.