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cover of episode 325: Unmasking Hidden Bias in AI—Who’s Really in Control? Data Ethics & Responsibility with Dr. Brandeis Marshall, DataedX Group CEO

325: Unmasking Hidden Bias in AI—Who’s Really in Control? Data Ethics & Responsibility with Dr. Brandeis Marshall, DataedX Group CEO

2025/3/3
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Brandeis Marshall: 我认为人工智能公司应该像科学实体一样受到监管，因为它们会优化人类行为。这需要与科学过程相符的监管，并且需要对数据管道中的每个人负责。数据伦理关乎数据在特定情境下的使用方式，数据不能被武器化。许多人工智能公司实际上是科学公司，它们的目标是优化人类行为，而非人工智能本身。所有人工智能都是数据问题，数据伦理关乎如何负责任地使用数据以增强人类体验。数据管道中的每个人都对数据的处理和使用负有责任，包括开发者。开发者有责任质疑数据输入方式，控制数据处理方式，并负责任地传递数据。数据处理是一个系统工程，每个参与者都负有责任。即使是编写代码的低级别人员，也有责任质疑数据和算法中的偏差。数据管道中的每个人都对潜在偏差负责，需要积极发声。我认为人工智能可以用来揭示不平等，提供证据，并增强人类沟通。人工智能可以帮助人们理解术语，从而促进更有效的沟通。人工智能可以作为专业人士的辅助工具，帮助他们更高效地工作。人工智能可以帮助神经多样化的人克服沟通障碍，创造内容。人工智能应该被视为辅助工具，而非替代工具，可以帮助神经多样化的人。如果我们能够负责任地使用人工智能，它将成为一种强大的赋能工具。医疗保健算法决策过程应该透明，患者应该能够访问自己的完整医疗记录。患者应该拥有可携带的、属于自己的医疗记录。患者的医疗记录应该包含所有相关信息，包括算法的使用情况。我成功的秘诀在于积极的父母、全女子学校的经历以及支持我的人。 Dan Turchin: 作为主持人，我引导了与Brandeis Marshall博士的讨论，并提出了一些问题，例如人工智能公司应该如何受到监管，数据伦理的含义，以及如何应对数据中的潜在偏见。我还探讨了人工智能在医疗保健领域的应用，以及如何利用人工智能来促进公平与包容性。

Deep Dive

Chapters
This chapter explores the controversial idea of regulating AI companies like scientific entities, emphasizing the responsibility of everyone involved in the data pipeline for ethical decision-making. The discussion highlights the need for oversight to prevent harm caused by AI systems.
  • AI companies should be considered scientific entities requiring oversight and regulation.
  • Everyone who handles data has a responsibility for ethical considerations.
  • AI systems should not harm people.
  • Data ethics involves understanding the context and responsible use of data.

Shownotes Transcript

Dr. Brandeis Marshall is a leading advocate for responsible data science and the CEO of Dataedx Group, a data ethics and learning development agency dedicated to helping teams identify and address discrimination in data. Previously, she was a professor of computer science at Spelman College and a faculty associate at Harvard. Dr. Marshall holds a master’s and Ph.D. in computer science from Rensselaer Polytechnic Institute (RPI).

In this conversation, we discuss:

  • Why AI-powered companies should be regulated like scientific entities—and the hidden ways they optimize human behavior.
  • The role of data ethics in AI—how companies can prevent bias and why everyone in the data pipeline is responsible for ethical decision-making.
  • Why most businesses struggle with AI adoption—Brandeis explains how companies can bridge the AI gap and align data strategies with real business impact.
  • The future of healthcare data—how a patient-owned, portable medical record system could revolutionize access and transparency.
  • How AI can be leveraged to expose systemic inequalities and provide better opportunities for marginalized communities.
  • Why AI should be seen as a support tool, not a replacement—Brandeis shares how AI can help neurodivergent individuals and enhance human decision-making.

Resources:

  • Subscribe to the AI & The Future of Work Newsletter)
  • Connect with Brandeis on LinkedIn)
  • AI fun fact article)
  • On Using AI to Unlock Human Potential)