Winter 2020 – Ryan Holiday – speaks about “Ancient Wisdom, Modern Life”

https://youtu.be/41-gTa1qowg February 27th, author Ryan Holiday was the guest speaker at the 2020 Honor Courage and Commitment Luncheon, sponsored by the Stockdale Center, through the generous funding of Dr. Ernst and Sarah Volgenau. The Luncheon invites prominent national thought leaders and influencers to reflect on ethical leadership principles they have found powerful in their own […]

Artificial Intelligence and its Impact on Leaders and Leadership

Artificial Intelligence and its Impact on Leaders and Leadership January 30, 2022 Authored: Yannick Peifer, Tim Jeske, Sven Hille Published: Institute of Applied Industrial Engineering and Ergonomics, Düsseldorf, Germany Summary: The article explores the impact of Artificial Intelligence on companies, particularly in terms of leadership and work environment. AI’s integration creates challenges for leaders, including […]

Principled Artificial Intelligence

Principled Artificial Intelligence January 15, 2020 Authored: Jessica Fjeld & Adam Nagy Published: MAPPING CONSENSUS IN ETHICAL AND RIGHTS-BASED APPROACHES TO PRINCIPLES FOR AI Summary: The article discusses the development of AI principles by various organizations and highlights eight key themes found in these principles: Privacy, Accountability, Safety and Security, Transparency and Explainability, Fairness and […]

Fall 2019 – Brad Snyder – Retired EOD officer, and Paralympic World Record Holder speaks about “Triumph over adversity.”

https://youtu.be/-ryM_ehdxa4 Mr. Brad Snyder, wounded warrior and medalist athlete, was the guest speaker for the 2019 Honor Courage and Commitment Luncheon, an event that invites faculty, staff and midshipmen for an afternoon of inspiration and fellowship. Leaders, innovators and people who make a difference through service are invited to share their stories with the group. […]

7 Common Myths About AI

Sebastian Schaal – Medium

This article debunks several myths about artificial intelligence (AI), machine learning (ML), and deep learning (DL). It clarifies the distinctions between these terms, the role of data in ML, and the limitations of neural networks compared to the human brain. It also emphasizes that superintelligence is still a distant concept and that open-source initiatives have democratized ML research beyond major tech companies.