REFLECTIVE JOURNAL SESSION 11

Pre-workshop

Healthy economy should be designed to thrive, not grow | Kate Raworth

Kate Raworth reimagines economic progress, challenging the traditional belief in constant growth. She argues that modern economies, especially in wealthy countries, should focus on thriving sustainably rather than pursuing endless growth. Raworth critiques the historical obsession with GDP growth, tracing it back to W.W. Rostow's 1960 model, which emphasized perpetual economic expansion. This growth dependency has become ingrained financially, politically, and socially, driven by financial systems, political aspirations, and consumer culture.

Raworth introduces the "doughnut" model for economic progress. The inner ring represents the minimum standards for human well-being, while the outer ring signifies the ecological limits of our planet. The goal is to operate within this safe and just space, ensuring everyone meets their basic needs without exceeding the planet's boundaries.

To achieve this, economies must become regenerative and distributive by design. Regenerative economies mimic natural processes, recycling resources continuously. Distributive economies ensure wealth, knowledge, and power are shared broadly, leveraging technologies like renewable energy and digital platforms to empower communities.

Raworth concludes by rejecting the notion of endless growth, advocating for economies that mature and stabilize. This shift requires financial, political, and social innovations to overcome growth dependency, focusing instead on sustainable development within the doughnut's boundaries. This balanced approach promises a future of creativity, participation, and meaning for all.

What is Swarm AI ?

Dr. Louis Rosenberg explores the concept of swarm intelligence, emphasizing how birds, bees, fish, and ants enhance their intelligence by operating in highly interconnected systems. This collective intelligence, called swarm intelligence, enables these creatures to solve complex problems more efficiently than any individual member could.

He provides an example of honeybees, which use a process known as a "waggle dance" to collectively select the best new home. They consider various factors such as size, insulation, and location. Despite their tiny brains, bees achieve optimal solutions 80% of the time by forming a swarm intelligence.

Rosenberg contrasts this with human decision-making, which often relies on polarizing methods like polls and votes, leading to gridlock and suboptimal outcomes. He suggests that humans can also form swarm intelligences, using modern technology to create artificial super experts that make more accurate predictions and decisions.

He shares examples of human swarms outperforming individuals and even experts in tasks such as predicting the Kentucky Derby and the Oscars. By combining the diverse perspectives and knowledge of groups in real-time systems, these swarms achieve significantly higher accuracy.

Rosenberg argues that the potential of human swarm intelligence is immense, potentially leading to true superintelligence that is not only smarter but also wiser, incorporating human values and sensibilities. This could help address major global challenges such as poverty, inequality, and sustainability.

He concludes by encouraging a positive view of hive minds, suggesting that if honeybees observed human decision-making, they might consider us primitive. However, through swarm intelligence, humans have the potential to significantly advance and solve complex problems more effectively.

Post workshop

Linda Hill: How to manage for collective creativity

Linda Hill, a business professor and ethnographer, shares insights on leading innovation, derived from nearly a decade of research. Along with her team, she studied 16 exceptional innovation leaders across seven countries and 12 industries. Through extensive field observations, Hill discovered that conventional notions of leadership often fail to foster innovation.

Hill emphasizes that innovation is not about solo genius or visionary leadership. Instead, it involves collective genius, where diverse teams collaborate through a messy, iterative process. Using Pixar as an example, she illustrates that creating a successful animated movie requires the contributions of around 250 people over several years, with no part considered finished until the entire project wraps.

Hill identifies three capabilities essential for innovative organizations:

1. Creative Abrasion: Encouraging constructive debates to generate a diverse range of ideas. It involves amplifying differences rather than minimizing them and fostering an environment where people actively listen and advocate for their viewpoints.

2. Creative Agility: Quickly testing and refining ideas through experimentation. This approach prioritizes learning over being right, allowing for rapid adjustment based on feedback.

3. Creative Resolution: Combining even opposing ideas to create new, useful solutions. This involves inclusive decision-making that avoids compromise and dominance by any single individual or group.

Hill highlights examples from Pixar and Google's infrastructure group to illustrate these capabilities in action. At Google, parallel teams were allowed to pursue different approaches to solving a critical data storage problem, ultimately selecting the best solution through collaborative problem-solving.

She concludes by emphasizing the need for a new kind of leadership—one that creates an environment where everyone's talents and passions can flourish. Leaders should act as social architects, nurturing bottom-up innovation and enabling the collective genius of their teams. Hill urges leaders to set the stage rather than perform on it, fostering a space where creativity and collaboration can thrive, leading to innovative solutions.

By reimagining leadership in this way, organizations can consistently innovate and achieve collective genius.