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Home>Blog>Podcast>Ethics, Privacy, and Responsible AI: What Every Leader Needs to Know | Episode #0011

Ethics, Privacy, and Responsible AI: What Every Leader Needs to Know | Episode #0011

  • 2025-05-23
  • Posted by: Brad Groux
  • Category: Podcast
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Building Responsible AI

In this essential episode of Start Small, Think Big, Brad Groux, Carrie Hundley, and Robert Groux take a grounded, no-hype look at what it really means to build responsible AI in today’s business landscape.

The trio unpacks the real-world risks behind AI buzzwords, starting with algorithmic bias, how it forms, how it scales, and how unchecked bias can lead to legal exposure, reputational damage, and inequitable outcomes. Brad shares how even seemingly neutral hiring tools can exclude qualified candidates if trained on biased historical data, while Carrie stresses that addressing bias requires cross-functional awareness and diverse input.

The conversation then moves to data privacy, not just as a compliance issue, but as a brand trust imperative. Carrie explains how one enterprise AI assistant accidentally exposed sensitive client info due to a lack of internal access controls, and outlines how embedding privacy-by-design into AI workflows can prevent costly missteps.

Robert dives into transparency and explainability, discussing how AI systems deployed in financial and automotive settings have built credibility through clear communication, user-facing explanations, and well-documented models. He also highlights how a financial services company rebuilt user trust with dashboards that helped explain lending decisions in plain language.

All of this is set against the backdrop of increasing global AI regulation, like the EU AI Act and U.S. executive actions which are reshaping expectations for business leaders. Whether you’re building AI internally, embedding it in products, or relying on third-party tools, the message is clear: ethical AI isn’t a “nice-to-have,” it’s foundational.

This episode equips leaders with the principles: bias mitigation, data protection, and explainability – that must guide every responsible AI initiative. It’s a must-listen for anyone deploying AI today, or preparing to tomorrow.

What we cover:

  • Bias in AI: Why it’s more than a technical flaw—it’s a business risk
  • Data privacy as the foundation of trust
  • Transparency: From recording meetings to explaining model outputs
  • Global regulation highlights: EU AI Act, U.S. executive actions
  • Real stories of ethical missteps—from 23andMe to Reddit
  • The rise of ethics committees, cross-functional alignment, and proactive AI governance

New episodes are released every Friday across all major podcast platforms (direct links below), with video available on Spotify and YouTube – follow along to empower your AI journey!

Start Small, Think Big: Episode 0011 – Show Notes

Summary

In this essential episode, Brad Groux, Carrie Hundley, and Robert Groux dive deep into the real-world challenges and responsibilities of AI adoption. From biased algorithms and fragile data privacy to transparency in LLMs and emerging global regulations, this conversation arms business leaders with the knowledge they need to build responsible, trustworthy AI systems.

Whether you’re deploying AI for internal productivity or customer-facing products, this episode highlights the foundational principles – bias mitigation, data protection, and explainability – that must be in place.

Keywords

AI ethics, data privacy, responsible AI, EU AI Act, bias in AI, military AI applications, technology updates, transparency in AI, user responsibility, ethical dilemmas, AI ethics, data privacy, transparency, bias, ethical AI, trust, agency, hallucinations, data ethics, responsible AI

Takeaways

  • Ethics and AI is a vast subject that requires ongoing discussion.
  • Data shared with companies can be used in ways not initially intended.
  • Users have a responsibility to understand the data they share.
  • The EU AI Act aims to regulate AI practices for better transparency.
  • AI can be used for both military and humanitarian purposes.
  • Recent tech developments show a shift towards AI integration in business.
  • Bias in AI can lead to significant ethical and business risks.
  • Transparency in AI decision-making is crucial for accountability.
  • Privacy concerns are central to building trust with users.
  • Companies must navigate the balance between innovation and ethical responsibility.
  • Helping people weigh the cost benefit and likelihood of something bad happening is crucial.
  • Agency in data sharing is a significant topic.
  • Not protecting user privacy can erode trust.
  • Reddit’s data selling practices illustrate the risks of data privacy breaches.
  • Data privacy should be foundational for any IT organization.
  • Transparency is essential in AI, especially regarding data usage.
  • Recording meetings requires permission and transparency.
  • Generative AI’s design leads to hallucinations, which need to be addressed.
  • Bias in data can skew AI results, necessitating careful data selection.
  • Ignoring ethical AI can lead to regulatory fines and brand damage.

Titles

  • Navigating the Ethics of AI
  • Data Privacy in the Age of AI
  • The Role of AI in Military and Humanitarian Efforts
  • Understanding the EU AI Act
  • Recent Innovations in AI Technology
  • Addressing Bias in AI Systems

Sound Bites

  • “Ethics and AI is a vast subject.”
  • “Data you give to companies is so valuable.”
  • “Your data is power for these companies.”
  • “The EU is emphasizing energy-efficient AI.”
  • “Bias in AI just isn’t just a technical flaw.”
  • “Privacy is the foundation of trust.”
  • “Taking away your data is taking away agency.”
  • “Data privacy is important beyond just AI.”
  • “Bias mitigation is crucial for ethical AI.”
  • “Privacy is the new brand trust.”
  • “Transparency turns risk into trust.”
  • “Ethics isn’t a feature. It’s a foundation.”
  • “You can’t hide from data history.”

Resources

Article content
source: Reddit

Chapters

00:00 Introduction to Ethics, Privacy, and AI

00:52 The 23andMe Bankruptcy and Data Privacy Concerns

05:31 The EU AI Act: Regulations and Responsibilities

09:46 AI in Military Applications: Ethical Dilemmas

13:45 Recent Developments in AI Technology

18:41 Bias in AI Algorithms: Risks and Responsibilities

26:01 Privacy as the Foundation of Trust

27:55 Navigating Privacy and Data Ethics

30:49 The Importance of Transparency in AI

34:40 Understanding AI Limitations and Hallucinations

39:22 The Role of Bias in Data and AI

42:26 Risks of Ignoring Ethical AI

43:44 Establishing Ethical AI Practices

47:44 Final Thoughts on Ethical AI

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