『GovConBiz with Linda Rawson』のカバーアート

GovConBiz with Linda Rawson

GovConBiz with Linda Rawson

著者: GovConBiz
無料で聴く

このコンテンツについて

Want to learn the secrets to government contracting? Be sure and listen to Linda Rawson as she shares her experience, strategy and tidbits about government contracting.2025 by GovConBiz, LLC All rights reserved マネジメント マネジメント・リーダーシップ リーダーシップ 経済学
エピソード
  • The Ethics of Prediction
    2025/09/29

    Linda Rawson explores how AI-driven predictions are shaping destinies, not just calculating probabilities. The episode highlights that prediction is a form of power and authority, influencing decisions in areas like criminal justice, hiring, and policing. Linda reveals how prediction is a form of control, and why designing AI that honors the future requires humility, transparency, and a sense of purpose.

    続きを読む 一部表示
    19 分
  • Clarity in Contracts
    2025/08/07

    Have you ever signed something you didn’t fully understand? Maybe a software license, a medical waiver, or even a business agreement. You trusted the process, but did you trust the language? In the world of AI, contracts are everywhere. They govern how data is used, how algorithms behave, and how accountability is defined. But too often, they’re written in a language that feels distant, opaque, or emotionally disconnected. In this episode, Linda Rawson dives into the fine print. Not just the legal language of contracts, but the ethical and energetic imprint they carry. Because in the age of AI, a contract isn’t just a document, it’s a declaration of values.

    続きを読む 一部表示
    11 分
  • Can Algorithms Earn Trust?
    2025/07/29

    Can algorithms earn our trust? In this debut episode of GovConBiz, Linda Rawson delves into the heart of AI, revealing how ethics, clarity, and wisdom can transform government technology. Drawing on her background in government contracting and her emerging voice in Trusted AI, Linda explores how artificial intelligence systems can, and must, reflect ethical design, transparency, and human values. She introduces actionable principles for responsible AI, including clarity, empathy, intentionality, accountability, and how technologists can design systems that serve not only programs, but also people.

    続きを読む 一部表示
    7 分
まだレビューはありません