For Tom Chatfield, a British technology philosopher and author, there is nothing inevitable about technological progress. In his latest book, ‘Wise Animals: How Technology Has Made Us What We Are’ he explores how humans have co-evolved with technology throughout history. In our discussion, Tom deconstructed the common narrative of technological inevitability, using examples like the Incas' use of wheels only as toys and the complex history of Gutenberg's printing press to illustrate how technological adoption is deeply intertwined with cultural values and societal choices rather than following a predetermined path.

Tom emphasizes that while AI doesn't possess true agency, it can be seductive and influential through its design and training. AI, after all, is also a piece of cultural technology. He advocates for viewing AI as a cognitive prosthesis that should complement human strengths while compensating for our weaknesses, particularly in areas like repetitive tasks and statistical analysis.

This episode concludes with some practical insights about navigating technological change, both at organizational and personal levels. Tom believes in the importance of taking time to ask the right questions in an age of instant answers, fostering constructive disagreement to avoid groupthink, and maintaining human agency in technological systems. He also shares personal perspectives on raising children in an AI-enabled world, emphasizing the need for supervised exploration and critical engagement with technology.

Key Insights

1.  Technology adoption is not inevitable but rather a negotiation between cultural values, practical needs, and societal choices - leaders should actively shape how technology serves their organization's values and goals

2. In an era of instant answers, competitive advantage comes from asking better questions and taking time to reframe problems beyond default assumptions

3. Organizations need to build in structures for constructive disagreement and cognitive diversity to avoid groupthink and maximize the benefits of both human and artificial intelligence

4. AI should be viewed as a cognitive prosthesis that complements human strengths rather than replacing human agency - focus on automation of areas where humans are naturally weak

5. Success with AI requires strong governance frameworks that enable systematic learning and accountability, similar to aviation safety systems

We talk about disruption all the time, but are we ready to embrace what that really means? Many companies set disruption as their goal, and even believe that by shaking up their market, they will achieve high levels of growth. For Charlene Li, leaders have all it all backwards. Disruption doesn't create growth; instead, growth creates disruption.

Charlene Li is the author of six books on innovation, digital transformation and leadership, including the New York Times bestseller, Open Leadership and co-author of the critically acclaimed book, Groundswell. Her latest book is the bestseller The Disruption Mindset. She is the Founder and Senior Fellow at Altimeter, a disruptive analyst firm acquired in 2015 by Prophet. Named one of the most creative people in business by Fast Company, Charlene is a graduate of Harvard College and Harvard Business School.

In this episode, you will learn

1. Newspapers, the first Internet Boom and why traditional media struggled to embrace the future (00:21)
2. Why creating an innovation division may by counterproductive (05:09)
3. How Adobe pulled off a disruptive transformation without losing their business (06:00)
4. The art of surviving a big bet, and how T-Mobile made theirs (07:48)
5. Why leaders should focus on their future customers, and where Facebook got it right and Myspace got it wrong (09:41)
6. How the pandemic changed the way we think about disruption (15:01)
7. The impact of disruption on jobs (19:50)
8. What it takes to create a movement for change in your organization (21:50)

Workplace transformation has never been more important than now, in this time of crisis. So what does it take to build and sustain a culture that is not only innovative and creative, but capable handling constant reinvention? Is the fact that it is difficult and uncomfortable, the very reason we should do it anyway? Dr Adam Fraser is a human performance researcher and consultant who studies how organizations adopt a high performance culture to thrive in this challenging and evolving business landscape. He is the author of Strive: Embracing the gift of struggle and The Third Space: Using Life's Little Transitions to find Balance and Happiness.

Now that the pandemic has plunged us into the world's largest remote work experiment, what are we learning about the kind of culture that supports distributed organizations? And how do leaders build a cultural operating system for a time of crisis and change? To answer this question, and to also understand how data is changing our understanding of performance and transformation - I spoke with Didier Elzinga, the CEO and co-founder of Culture Amp – one of the world’s fastest growing technology startups and has helped companies around the world harness the power of employee feedback to drive positive change. If you enjoyed this episode and Didier's perspectives, please take a moment to read my article on this topic in the Harvard Business Review. 

Regardless of your profession, one of the most important steps to becoming a better decision maker is knowing how to quantify uncertainty. That applies if you are a scientist, a poker player or a business leader. And while it is not unusual to apply probabilistic approaches to applications like robots or environmental monitoring - what is more challenging and potentially revolutionary is using similar strategies to more effectively fight crime or prevent bushfires. One of the leading thinkers in this field is Dr Roman Marchant, a lecturer and researcher in machine learning at the University of Sydney. I spoke with Marchant about his current research into developing new data science techniques to answer complex social questions such using AI for predictive policing and the implications for bias and discrimination.