AI and business models, Human-AI symbiosis, intelligent choice architecture, and more

📖In this issue

• Conference review: Web Directions Next

• AI in business model innovation

• Intelligence choice architecture for better decision-making

• What happens when AI eats the world

• Alexandra Diening on Human-AI Symbiosis, cyberpsychology, human-centricity, and organizational leadership in AI

• Beliefs about AI are, unfortunately, a source of division

💡Conference review: Web Directions Next

On Friday I attended the Web Directions Next conference. I used an AI-augmented approach to recording and distilling every session to create a compact summary of the major ideas at the event, completed within 2 minutes of it finishing. I think the summary format is interesting as well as the content. Check out the full distilled insights from the conference, or see the very short summary below.

I🌱 Reinvigorating Democracy and Governance: Nicholas Gruen proposed citizen assemblies and innovative governance models to restore trust and accountability in democracy.

🌍 Life-Centered Design: Martin Tomitsch and Steve Katy emphasized ethical, ecosystem-aware design, challenging short-term profit motives to foster sustainability and collaboration.

🔄 Beyond Nudges to Systemic Change: Mary Nolan highlighted the limits of nudging and called for systemic interventions that align with behavioral insights to solve global challenges.

🤖 Radically Adaptive Interfaces and AI Design: Josh Clark showcased AI as a dynamic design material for creating personalized, adaptive experiences, paired with a call for ethical responsibility.

🌐 Rewilding and Decentralizing the Internet: Maria Farrell and Rupert Manfredi envisioned a decentralized internet that nurtures collaboration, diversity, and resilience against monopolistic control.

📊 Reframing Advertising and Data: Jon Bradshaw and Jack Zhao critiqued the inefficiencies of data-driven systems, championing creativity, contextuality, and impactful visualization.

📖 The Role of Fiction and Storytelling: Joan Westenberg illustrated fiction's ability to inspire empathy and hope, countering the challenges of a polarized, post-truth world.

💪 Longevity Through Connection and Purpose: Mark Pesce inspired attendees to stay active, socially engaged, and purpose-driven to thrive in the age of extended lifespans.

🧠🤖Humans + AI

AI in business model innovation

“AI-driven business model innovation: A systematic review and research agenda" reviews 180 articles to provide a wealth of insight, but in particular two useful distillations: the four types of business model innovation, and the four roles that AI can play.

AI-driven business model innovation: A systematic review and research agenda
Summary of key insights

Intelligence choice architecture for better decision-making

"Generative AI... can surface hidden options, highlight overlooked interdependencies, and suggest novel pathways to success. These intelligent systems and agents don’t just support better decisions — they inspire them."

A new MIT Sloan Management Review article proposes that we need "intelligent choice architectures" that generate more and better options and in turn improved decisions and outcomes.

Intelligent Choices Reshape Decision-Making and Productivity (paywall)
Summary of key insights

What happens when AI eats the world

Leading technology analyst Benedict Evans' famous annual big picture slide deck is this year on 'AI eats the world'. He provides deep data-driven stories to address three critical questions:

• How far will this scale?

• How is this useful?

• How do we deploy this?

AI eats the world

🎙️This week’s podcast episode

Why you should listen

In this conversation Kevin Clark and Kyle Shannon share in detail how they have built an array of digital twins of insightful thinkers, and how they use them to think better and generate useful content. It’s a pragmatic and fun conversations.

💡Reflections

Beliefs about AI are, unfortunately, a source of division

People have different political opinions, reflecting a very broad array of beliefs about how society should be organized. This can lead to arguments at Thanksgiving, neighbours not talking to each other, and of course far worse.

Different beliefs about AI are also leading to divisions. Some see exciting potential. Others see only insane hype, dead-ends, exploitative capitalism, dehumanization, and a litany of other ills in AI’s very existence (or pretension of it).

This is also leading to arguments, strong emotions, and division, sometimes even impacting friendships, as demonstrating previously-unseen fundamental differences.

I have no easy solutions.

I am obviously an advocate for the positive possibilities of AI, and I am absolutely excited about how it can augment my other others’ potential.

A the same time I recognize and am sympathetic to many of the criticisms and potential downsides, and acknowledge the view that AI is simply hoovering up humanity to spit it out again.

I do fear the divide will grow, whatever the trajectory of AI, perhaps especially if it continues to progress apace.

I know it’s ironic, but having written the above, I pasted it in an LLM for suggested ways to respond. This is what it said.

Emphasizing Nuance and Dialogue

Polarization around AI mirrors deep societal divides. Fostering dialogue that welcomes both excitement and skepticism can create space for constructive disagreement rather than destructive division. Open conversations where differences are seen as opportunities for learning are essential.

Acknowledging Both Sides with Shared Humanity

Behind the excitement and criticisms of AI are human values—different but valid perspectives about what matters most. Bridging this divide requires empathy and recognizing that these beliefs often stem from shared desires for a better world.

Focusing on Shared Goals

Shared goals, like addressing global challenges or improving quality of life, can unite people with differing views on AI. Framing discussions around these common aspirations can reduce divisiveness while allowing for a healthy balance of enthusiasm and caution.

Inviting Collaborative Exploration

Collaboration can help transform polarized perspectives into shared efforts to shape AI responsibly. Inviting others to explore both AI’s potential and its downsides as a collective effort can foster mutual respect and understanding.

Drawing on Historical Parallels

The polarization around AI isn’t new—transformative technologies have always sparked strong reactions. Learning from history shows us that enthusiasm and caution can coexist and even lead to balanced progress, provided we engage tensions constructively.

Building Resilience to Polarization

Cultivating resilience to polarization is essential in managing the divide. Developing the ability to hold multiple, even conflicting, perspectives simultaneously encourages constructive engagement and deepens understanding.

Highlighting the Power of Personal Examples

Personal stories about how AI has augmented your potential can inspire others to see its positive aspects. Real-world examples make the benefits and risks of AI feel more relatable, sparking open and productive conversations.

Calling for Inclusive Voices

Including diverse voices in discussions about AI is critical to reducing polarization. Bringing in perspectives from those who feel excluded or exploited can enrich the conversation and foster more balanced, inclusive discourse.

Acknowledging Uncertainty Together

Admitting that none of us know where AI is heading can be a unifying approach. Starting from a place of humility about the future encourages openness to other perspectives and builds a foundation for collaboration.