This book offers a unified quantitative framework for understanding the dynamics of novelty and innovation across biological, technological, and societal systems. It explores how first-time occurrences—ranging from everyday experiences to groundbreaking discoveries—can lead to subsequent breakthroughs. The content is organized into three main parts. The first part introduces essential theoretical tools for investigating the emergence of new ideas. The second part examines both classical and modern models that capture the evolution, interaction, and competition of innovations within complex systems. This section emphasizes the importance of models based on the concept of the ‘Adjacent Possible’, i.e., all those things—ideas, molecules, technologies— that are one step away from what actually exists. The final section presents empirical case studies that utilize computational and data-driven methods to uncover hidden patterns in the diffusion of novelty. A postface summarizes the main findings and provides insight into future directions for research. By synthesizing insights from theoretical and computational physics, complexity science, and social sciences, this work challenges traditional views on predictability and control. It demonstrates that the forces driving innovation are both serendipitous and systematic, offering new perspectives on how progress unfolds. This comprehensive approach provides valuable methodologies for researchers, students, practitioners, and the general public, making it an essential resource for anyone looking to understand the complex processes that shape our ever-evolving world.This book offers a unified quantitative framework for understanding the dynamics of novelty and innovation across biological, technological, and societal systems. It explores how first-time occurrences—ranging from everyday experiences to groundbreaking discoveries—can lead to subsequent breakthroughs. The content is organized into three main parts. The first part introduces essential theoretical tools for investigating the emergence of new ideas. The second part examines both classical and modern models that capture the evolution, interaction, and competition of innovations within complex systems. This section emphasizes the importance of models based on the concept of the ‘Adjacent Possible’, i.e., all those things—ideas, molecules, technologies— that are one step away from what actually exists. The final section presents empirical case studies that utilize computational and data-driven methods to uncover hidden patterns in the diffusion of novelty. A postface summarizes the main findings and provides insight into future directions for research. By synthesizing insights from theoretical and computational physics, complexity science, and social sciences, this work challenges traditional views on predictability and control. It demonstrates that the forces driving innovation are both serendipitous and systematic, offering new perspectives on how progress unfolds. This comprehensive approach provides valuable methodologies for researchers, students, practitioners, and the general public, making it an essential resource for anyone looking to understand the complex processes that shape our ever-evolving world.

More at: academic.oup.com

Business today remains tethered to a paradigm that is long out of date. This mindset assumes that universal answers exist: Businesses can simply apply compartmentalized operations and follow linear paths to success. Experienced managers know business doesn’t work this way. Where should they turn?
In this groundbreaking book, Doug Garnett shows how complexity science reveals a new understanding of how business works that is as useful on the front lines as in the C-suite. This discipline—the study of behaviors in highly interconnected, adapting systems dominated by emergence—is revolutionizing fields from biology and economics to psychology and artificial intelligence. Recognizing a business as a complex adaptive system operating within other complex systems changes our perspective on everything from core concepts of demand, profit, and strategy to the nature of business success. Managers who grasp the order hidden within complexity discover not only a powerful new understanding of their role but also potential for dramatic contributions to success.
The Complexity Paradigm features vivid examples ranging from local coffee shops to major corporations like PepsiCo, Boeing, Mattel, Starbucks, and General Motors as well as tech giants such as Apple and AT&T. Grounding eye-opening theory in the realities of business, this foundational look at complexity offers deep insight and value for practitioners and students alike.

More at: cup.columbia.edu

This book describes the urgent need of modern humanity to renew and reinforce an open attitude to the complexity of life, above all by embracing its intrinsic indeterminacy, rather than attempting futilely to control its evolution. Oblivious to this ever-more urgent necessity, seduced by the speed and virality of digital pattern recognition, computing, and artificial simulation of human thought, society has reverted to a linear, deterministic concept of reality, under the belief that everything can be measured and managed, and that error and unpredictability will soon be eliminated from our lives and organizations. Consequently, choices and responsibilities have been delegated to technology, artificial intelligence and algorithms, even in educational institutions, which are now preoccupied with teaching mere skills and know-how, thus committing the fatal error of confusing artificial, mechanical, complicated systems with living, complex, adaptive systems. 

This volume is intended not only for complexity/social scientists, philosophers and students, but to the curious from all walks of life. It calls for learning to inhabit complexity, while recognizing and participating in its interdependent, interconnected, interactive systems of relationships. Dominici reveals the futility of endeavoring to control the uncontrollable or observe the unobservable, showing how self-organization and emergence, triggered from the smallest and most modest elements, impact the entire system.

More at: link.springer.com

Edited by Chrystopher L. Nehaniv, Peter R. Lewis, Stefano Nichele, Jitka Čejková, Christoph Salge, Imran Khan, Hanna Derets

IN MEMORIAM: Inman Harvey, 1948 – 2026. Dedicated to the memory of Inman Harvey, a towering figure with a brilliant mind and joyful, wicked wit, a mentor, and precious friend to our community.

This volume presents the proceedings of ALIFE 2026, the 27th Conference on Artificial Life, held in Waterloo, Ontario, Canada, from 17–21 August 2026. The proceedings will be available at the conference through MIT Press open access.

The conference theme, “Living and Lifelike Complex Adaptive Systems”, places at the centre of the programme the principles through which biological, computational, chemical, robotic, social, and cultural systems generate coherent, adaptive, and evolving organization.

Read the full proceedings at: direct.mit.edu

Perspectives on Machine Consciousness asks whether any AIs are conscious today, whether any future ones could be conscious, how we could know, and what implications machine consciousness would have for us and for them.

As AI improves rapidly in performance and capability, these questions are becoming increasingly important. We do not fully understand how AIs work, and even some of the leading LLM developers say they cannot be sure that today’s models are not sentient, though many people are forming relationships with them, sometimes intimate ones. The book explores consciousness alongside our interactions with AI, including the critical need to avoid committing mind crime by causing artificial minds to suffer, as well as considering that if and when superintelligence arrives, its enormous effect on humanity may be significantly determined by whether or not it is conscious. The authors show that machines becoming conscious means we may learn a great deal about our own consciousness – arguably the most important, and yet most mysterious, thing about us.

This book is required reading for anybody developing advanced AI, working in AI safety, responsible for developing AI policies at an organizational or national level, and indeed anybody concerned with the long-term future of humanity.

More at: www.taylorfrancis.com