New Frontiers in Science in the Era of AI, edited by Marilena Streit-Bianchi and Vittorio Gorini, Springer Nature
At a time when artificial intelligence is more buzzword than substance in many corners of public discourse, New Frontiers in Science in the Era of AI arrives with a clear mission: to contextualise AI within the long arc of scientific thought and current research frontiers. This book is not another breathless ode to ChatGPT or deep learning, nor a dry compilation of technical papers. Instead, it’s a broad and ambitious survey, spanning particle physics, evolutionary biology, neuroscience and AI ethics, that seeks to make sense of how emerging technologies are reshaping not only the sciences but knowledge and society more broadly.
The book’s chapters, written by established researchers from diverse fields, aim to avoid jargon while attracting non-specialists, without compromising depth. The book offers an insight into how physics remains foundational across scientific domains, and considers the social, ethical and philosophical implications of AI-driven science.
The first section, “New Physics World”, will be the most familiar terrain for physicists. Ugo Moschella’s essay, “What Are Things Made of? The History of Particles from Thales to Higgs”, opens with a sweeping yet grounded narrative of how metaphysical questions have persisted alongside empirical discoveries. He draws a bold parallel between the ancient idea of mass emerging from a cosmic vortex and the Higgs mechanism, a poetic analogy that holds surprising resonance. Thales, who lived roughly from 624 to 545 BCE, proposed that water is the fundamental substance out of which all others are formed. Following his revelation, Pythagoras and Empedocles added three more items to complete the list of the elements: earth, air and fire. Aristotle added a fifth element: the “aether”. The physical foundation of the standard cosmological model of the ancient world is then rooted in the Aristotelian conceptions of movement and gravity, argues Moschella. His essay lays the groundwork for future chapters that explore entanglement, computation and the transition from thought experiments to quantum technology and AI.
A broad and ambitious survey spanning particle physics, evolutionary biology, neuroscience and AI ethics
The second and third sections venture into evolutionary genetics, epigenetics (the study of heritable changes in gene expression) and neuroscience – areas more peripheral to physics, but timely nonetheless. Contributions by Eva Jablonka, evolutionary theorist and geneticist from Tel Aviv University, and Telmo Pievani, a biologist from the University of Padua, explore the biological implications of gene editing, environmental inheritance and self-directed evolution, as well as the ever-blurring boundaries between what is considered “natural” versus “artificial”. The authors propose that the human ability to edit genes is itself an evolutionary agent – a novel and unsettling idea, as this would be an evolution driven by a will and not by chance. Neuroscientist Jason D Runyan reflects compellingly on free will in the age of AI, blending empirical work with philosophical questions. These chapters enrich the central inquiry of what it means to be a “knowing agent”: someone who acts on nature according to its will, influenced by biological, cognitive and social factors. For physicists, the lesson may be less about adopting specific methods and more about recognising how their own field’s assumptions – about determinism, emergence or complexity – are echoed and challenged in the life sciences.
Perspectives on AI
The fourth section, “Artificial Intelligence Perspectives”, most directly addresses the book’s central theme. The quality, scientific depth and rigour are not equally distributed between these chapters, but are stimulating nonetheless. Topics range from the role of open-source AI in student-led AI projects at CERN’s IdeaSquare and real-time astrophysical discovery. Michael Coughlin and colleagues’ chapter on accelerated AI in astrophysics stands out for its technical clarity and relevance, a solid entry point for physicists curious about AI beyond popular discourse. Absent is an in-depth treatment of current AI applications in high-energy physics, such as anomaly detection in LHC triggers or generative models for simulation. Given the book’s CERN affiliations, this omission is surprising and leaves out some of the most active intersections of AI and high-energy physics (HEP) research.
Even as AI expands our modelling capacity, the epistemic limits of human cognition may remain permanent
The final sections address cosmological mysteries and the epistemological limits of human cognition. David H Wolpert’s epilogue, “What Can We Know About That Which We Cannot Even Imagine?”, serves as a reminder that even as AI expands our modelling capacity, the epistemic limits of human cognition – including conceptual blind spots and unprovable truths – may remain permanent. This tension is not a contradiction but a sobering reflection on the intrinsic boundaries of scientific – and more widely human – knowledge.
This eclectic volume is best read as a reflective companion to one’s own work. For advanced students, postdocs and researchers open to thinking beyond disciplinary boundaries, the book is an enriching, if at times uneven, read.
To a professional scientist, the book occasionally romanticises interdisciplinary exchange between specialised fields without fully engaging with the real methodological difficulties of translating complex concepts to the other sciences. Topics including the limitations of current large-language models, the reproducibility crisis in AI research, and the ethical risks of data-driven surveillance would have benefited from deeper treatment. Ethical questions in HEP may be less prominent in the public eye, but still exist. To mention a few, there are the environmental impact of large-scale facilities, the question of spending a substantial amount of public money on such mega-science projects, the potential dual-use concerns of the technologies developed, the governance of massive international collaborations and data transparency. These deserve more attention, and the book could have explored them more thoroughly.
A timely snapshot
Still, the book doesn’t pretend to be exhaustive. Its strength lies in curating diverse voices and offering a timely snapshot of science, as well as shedding light on ethical and philosophical questions associated with science that are less frequently discussed.
There is a vast knowledge gap in today’s society. Researchers often become so absorbed in their specific domains that they lose sight of their work’s broader philosophical and societal context and the need to explain it to the public. Meanwhile, public misunderstanding of science, and the resulting confusion between fact, theory and opinion, is growing. This gulf provides fertile ground for political manipulation and ideological extremism. New Frontiers in Science in the Era of AI has the immense merit of trying to bridge that gap. The editors and contributors deserve credit for producing a work of both scientific and societal relevance.
