Description: The authors suggest that mastering 'star performer' skills and work strategies is simply a matter of learning and practicing the outlined techniques. From The Stepping Stone, February 2012, Issue No. 45.

Description: This article covers the importance of letting teams lead you as a leader, that it's okay to admit you're not okay even at work, and that it's important to find informal ways for virtual teams to connect.

Description: Effective strategic planning can have a profound effect on the development of your team and the growth and direction of your actuarial organization. This article shares the elements that will set you up for success before the meeting even begins.

Description: The article presents specific operational guidelines when managers and staff are having difficult conversations. The article reviews half a dozen "popular" guidelines but shows that they are not specific. The article then in two layers presents specific operational guidelines. First the article based on a commonality of principles of email etiquette and Jewish Speech Laws reviews five guidelines for ordinary conversations: focus on events vs. people, focus on fixes vs. blames, being holistic (acknowledge any good done), be operational (indicate outcome and how to accomplish it), and use of tentative tone. The article concludes by adding three specific guidelines for difficult conversations: shared-self-evaluation, skillful use of breaks when emotions flair, and use of open-ended lead-on questions coupled with continuous empathy and offers of collaborative support.

Description: February/March 2009 Volume 6 Issue 1 Bi-Monthly membership benefit magazine

Description: Discussion of the need to find a balance between work and career and tips on how to achieve it.

Description: An essay on how the lyrics of the Simon and Garfunkel hit song helps the author keep perspective and be a better leader by slowing down and taking the time to listen and lead.

Description: metadata for the entire issue

Description: In the insurance industry, machine learning models are increasingly used to make decisions that affect people's lives. In order to ensure that models are fair, they should be audited for bias. There are no hard and fast rules for bias audit; metrics that can be used to evaluate fairness vary depending on the context in which the model is deployed. In this session, we present a flexible framework that highlights key considerations in bias evaluation that can be adjusted to suit your process. In this session, we will learn about different metrics to assess fairness, discuss open source tools that can be used for bias audit, and walk through a case study.

Description: Resources to help actuaries advance their careers.