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Kate O'Neill

Tech humanist, business writer, and speaker. Founder of KO Insights and author of 'What Matters Next?'.

Top 3 podcasts with Kate O'Neill

Ranked by the Snipd community
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16 snips
Dec 15, 2025 • 40min

367: Inside the Tech Humanist Playbook: Kate O’Neill on AI, Purpose, and Meaningful Work

In this conversation with Kate O’Neill, a tech humanist and author, the focus is on the intersection of AI and meaningful work. Kate shares insights on how tech humanism guides the design of human-centered AI systems. She addresses the fear of automation, urging workers to view AI as an opportunity to enhance their roles. Leadership's role in fostering psychologically safe environments for experimentation is emphasized. Ultimately, the discussion highlights the importance of embedding purpose and meaning in the workplace as automation evolves.
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8 snips
May 7, 2025 • 0sec

Navigating the Nuances of AI and Climate Action with Kate O'Neil

In a captivating discussion, Kate O'Neill, a tech humanist and CEO of KO Insights, shares her expertise on the intersection of AI and climate action. She emphasizes the need for ethical AI deployment to tackle climate challenges, advocating for 'strategic optimism' in project management. Kate highlights the power of casual conversations at conferences to inspire ideas and solutions. She also addresses the emotional aspects of climate grief and the proactive role individuals can play, especially the youth, in driving impactful change.
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Jul 20, 2025 • 43min

3353: Why the Human Experience Still Matters in a Machine-Led World

Join Kate O’Neill, the "Tech Humanist" and founder of KO Insights, as she discusses the importance of aligning technology with human values. She emphasizes the need for organizations to define their purpose clearly before adopting AI. Kate introduces the concept of ethical acceleration and the significance of human oversight in tech deployments. With real-world examples from companies like Apple and Duolingo, she argues for a shift from traditional efficiency metrics to more meaningful measures of success, reminding us that asking "should we?" is vital in the age of AI.

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