Description: In this video Jing Lang emphasizes the importance of ethical considerations in AI utilization, particularly focusing on privacy, bias, transparency, and creativity. It highlights the need for collaboration among various stakeholders to address these concerns through regulations, diversity promotion, and ongoing discussions. Sources of bias in AI, such as underrepresented datasets and historical biases, are identified along with strategies to mitigate bias, including careful assessment of inputs and retaining algorithms. Contributors: Jing Lang, FSA, FCIA, MAAA FLMI; Scott Allen, FSA, MAAAA, Henry Chen FSA, FCIA, MAAA; Jon Forster ASA, MAAA

Description: Dana M. Peterson, chief economist for the Conference Board, has established herself as a visionary, and the go to expert providing insightful analysis and predictions to corporations, associations, and government organizations looking for clarity and foresight into how economic drivers might impact their businesses in the short- and long-term. With over two decades of experience in the field, she serves as the globally recognized think tank’s public face and primary spokesperson on all things related to the economy.

Description: "Discuss research conducted at the Cleveland Clinic to understand levels of anxiety and depression across Northeast Ohio. Specifically, learn how advanced analytical techniques were utilized with social media data from Twitter and Google to estimate the need for psychological support by geography and overtime. The panel will go further to demonstrate how natural language processing (NLP) and machine learning could be used to make operational decisions at a leading health care provider."

Description: Data science is being used to create more algorithms used across a variety of applications, including underwriting and pricing. As data science gains traction, it is imperative that we as actuaries consider the ethical implications of use of these algorithms. This session will discuss techniques for evaluating whether your algorithms are inadvertently making biased decisions and considerations for ensuring that your algorithms minimize risk of making biased decisions. Learn to identify potential ethical issues with their algorithms and techniques to address them.

Description: A drive to push through the fear of failure is one of the traits that separates successful entrepreneurs from the pack. And as Nazir Valani learned early in his career, that drive is especially important when doubts come from people he looked to for encouragement.

Description: Yi-Ling Lin, FSA, MAAA, FCA, started the SOA’s Predictive Analytics Certificate Program to keep pace with the impact big data and predictive modeling is having on the health care industry

Description: Actuarial concepts of credibility can be extended to encompass additional information provided by new machine learning estimates. New statistical ideas also indicate how to generalize to blend arbitrarily many estimators, while not double-counting common information. For example, historical claim costs and risk scores both leverage diagnosis code information. We introduce two new estimators, one based on partial correlation and the other based on the machine learning-derived Shapley statistic, to address these limitations.

Description: Analyze the market volatility behavior in context with historical extreme events during this webcast. There will be a focus on understanding volatility clustering and relationships, both contemporary and temporal, in addition to key economic and capital market variables. You'll also learn from a comprehensive attribution analysis, which uses economic data, asset data, retail investor data and event data as explanatory variables. Dive into investment-related Reddit comments used to capture features of retail investors and tree-based models, including Random Forests and Gradient Boosting Machines to justify changes in volatility modeling. Expect this webcast to end with an example of liability-driven investment optimization that illustrates the potential impact of increased volatility assumption, how to adopt stochastic volatility models, how to reflect volatility clustering and return jumps.

Description: "Examine the exciting possibilities for artificial intelligence (AI) in health care and its potential to transform the patient journey. You will learn about the various touchpoints where AI is being applied along the patient/care journey, including provider search tools, claims analysis, and fraud detection. By attending the session, you will be able to: Have a comprehensive understanding of the opportunities and challenges presented by AI in health care Evaluate the potential impact of AI on their own organizations Be equipped with strategies for effectively implementing AI solutions and maximizing their benefits for patients, providers, and payers"

Description: This session will present the results of a case study investigating the impact of genetic testing on the reduction of health care costs. This will present both actuarial and clinical analysis of genetic testing in addition to researchers who are applying this approach.