Description: A solicitation for letters to the editor of Expanding Horizons.

Description: Article describes best practices for teaching a course module that involves multiple parameters. A good example is hypothesis testing which requires consideration of the parameters, sample-size, population distribution, known variance and has as consequences whether a normal or t distribution should be used or whether non parametric methods are used. The articles recommends use of the Prime Implicant Normal Form as a means of teaching. It shows the superiority of this method over other forms such as heuristics, complete rules, or graduated approaches.

Description: A summary recap of the recent SOA Health Conference held in Dallas, TX in June of 2025. With the intentional use of AI to assist with the summary, this article gives a good overview of the recent conference with personal commentary from one of the attendees.

Description: Column from SOA president discussing opportunities for members of the SOA.

Description: The author discusses expectations for incoming actuarial science students, emphasizing that a solid grasp of algebra and traditional mathematical skills is not enough. In addition, the author states that today’s business environment dictates that students be well versed and that their backgrounds include familiarity with complexity science.

Description: Crossword puzzle for the readers of Risks & Rewards newsletter.

Description: A typical course has some "hard" parts. These "hard" parts are the places where weaker students begin to fail, lose interest, and give up. The paper introduces a metric by which to evaluate each course topic. High metric values indicate "hard parts" of courses. The paper recommends spending more course time on hard parts and less course time on easy parts. The paper also recommends using disclosure: Tell students - this part of the course is "hard" and they may feel uncomfortable which is why more time is being spent on it." This approach to hard parts works! Failure rates are significantly reduced, while retention, satisfaction, and student scores improve.

Description: Welcome to the future of insurance, for actuaries and non-actuaries! Discover how cutting-edge AI models are revolutionizing underwriting, risk assessment, and customer experience for the insurance industry. Experts in management consulting and actuarial consulting firms will provide valuable insights into the consideration and challenges surrounding the adoption of Generative AI.

Description: This paper is an introduction to AI technology designed for actuaries to understand how the technology works, the potential risks it could introduce, and how to mitigate risks.