The world is complex, but acknowledging its complexity requires an appreciation for the many roles context plays in shaping natural phenomena. In Unsimple Truths, Sandra Mitchell argues that the long-standing scientific and philosophical deference to reductive explanations founded on simple universal laws, linear causal models, and predict-and-act strategies fails to accommodate the kinds of knowledge that many contemporary sciences are providing about the world. She advocates, instead, for a new understanding that represents the rich, variegated, interdependent fabric of many levels and kinds of explanation that are integrated with one another to ground effective prediction and action.Mitchell draws from diverse fields including psychiatry, social insect biology, and studies of climate change to defend “integrative pluralism”—a theory of scientific practices that makes sense of how many natural and social sciences represent the multi-level, multi-component, dynamic structures they study. She explains how we must, in light of the now-acknowledged complexity and contingency of biological and social systems, revise how we conceptualize the world, how we investigate the world, and how we act in the world. Ultimately Unsimple Truths argues that the very idea of what should count as legitimate science itself should change.
Illusions of Understanding in the Sciences
Scientists seek to understand the causes of observed phenomena. Beliefs that they have succeeded are based on understanding that is rarely or possibly never complete, and varies in depth and quality. Most often scientists believe they understand more than they do, making their belief an illusion. This illusion then persists in explanations scientists provide in print, in talks, or in discussions. The illusion that a scientist has a valid and complete explanation tends to be magnified when the data are well described by mathematical and computer simulation models due to the precision of such models and their ability to predict well; prediction does not imply causality, but gives the illusion that it does. The first part of this essay supports the case for the universality of partial and incomplete levels of understanding by showing the difficulty of reaching a deep level of understanding for even a simple analysis and model that most scientists use and believe they understand: linear regression. The second part highlights some implications of the existence of many levels of understanding and explanation, and their use by scientists for design, testing, analysis, and theory development. It discusses the way that deduction and induction depend on the levels of understanding and the implications of the illusion that a scientist’s understanding is deep. It makes a case that the many incomplete levels of understanding affect, often unwittingly, the ways scientists design experiments, test theories, comprehend, communicate, and teach.
Complexity Explorables
A collection of interactive explorable explanations of complex systems in biology, physics, mathematics, social sciences, epidemiology, ecology and other fields....
Ecocivilization: making a world that works for all
""One of the greatest thinkers of our age" (The Guardian) presents a new way of living-one modeled on nature's design instead of capitalism's-for fans of Guns, Germs, and Steel and Doughnut Economics It has often been said that it is easier to imagine the end of the world than it is to imagine the end of capitalism-and yet that is what the historical moment urgently calls for. Climate change has reached an emergency state, inequality continues to grow, and, for many, the future has never seemed more bleak. Incremental policy improvements are no longer enough-we need a deep transformation of our current civilization to continue to survive. In Ecocivilization, leading thinker Jeremy Lent reimagines the basis of our civilization, and argues for a new global system of living, one based on life-affirming principles modeled after nature's own design. What enfolds is a robust framework incorporating Lent's own expertise, and the lived experiences of those on the ground already putting ecological civilization's core tenants into practice-justice, mutuality, diversity, and symbiosis. From the global economy to universal housing and income, from infrastructure to agriculture, every major aspect of our society could be redesigned to work together as a coherent whole, setting the conditions for all people to flourish. Ecocivilization shows how this future on a regenerated Earth is not only desirable, but entirely feasible"--
Systems of Global Governance in the Era of Human-Machine Convergence
Technology is increasingly shaping our social structures and is becoming a driving force in altering human biology. Besides, human activities already proved to have a significant impact on the Earth system which in turn generates complex feedback loops between social and ecological systems. Furthermore, since our species evolved relatively fast from small groups of hunter-gatherers to large and technology-intensive urban agglomerations, it is not a surprise that the major institutions of human society are no longer fit to cope with the present complexity. In this note we draw foundational parallelisms between neurophysiological systems and ICT-enabled social systems, discussing how frameworks rooted in biology and physics could provide heuristic value in the design of evolutionary systems relevant to politics and economics. In this regard we highlight how the governance of emerging technology (i.e. nanotechnology, biotechnology, information technology, and cognitive science), and the one of climate change both presently confront us with a number of connected challenges. In particular: historically high level of inequality; the co-existence of growing multipolar cultural systems in an unprecedentedly connected world; the unlikely reaching of the institutional agreements required to deviate abnormal trajectories of development. We argue that wise general solutions to such interrelated issues should embed the deep understanding of how to elicit mutual incentives in the socio-economic subsystems of Earth system in order to jointly concur to a global utility function (e.g. avoiding the reach of planetary boundaries and widespread social unrest). We leave some open questions on how techno-social systems can effectively learn and adapt with respect to our understanding of geopolitical complexity.
Social Physics in the Age of Generative AI: How, Exactly, Is Society Complex?
The aspiration for a social physics — a science that would reveal universal laws of social life analogous to those governing the natural world—has haunted the social sciences since Comte. Each new wave of quantitative and computational methods breathes fresh life into this vision. The current moment is no exception: advances in artificial intelligence and large language models have reinvigorated attempts to model society through the methods of social physics. This essay argues that these ambitions rest on a confusion about the nature of social complexity. Drawing a distinction between systems complexity and anthropological complexity, we identify the limitations of analyzing society as a complex system akin to natural systems. One crucial obstacle for social physics is the analysis of meaning and interpretation. Generative artificial intelligence (GenAI) offers important opportunities to model language and reflexivity, inviting and perhaps compelling social physics to confront meaning and interpretation as constitutive features of the social world. At the same time, GenAI leaves untouched and may even aggravate social physics’ failure to grasp power, institutions, and inequality.
How to understand cells, tissues and organisms as agents with agendas | Aeon Essays
Biology’s next great horizon is to understand cells, tissues and organisms as agents with agendas (even if unthinking ones)
Re-Engineering Wimsatt for Limited Beings
Science is the best way to produce facts about reality. The best, at least, that limited human beings have devised so far. Yet, not even scientists quite seem to understand how scientific knowledge is generated. This is not only a philosophical but also a practical problem, as our misunderstandings affect the quality of our research and limit the directions it can take. In light of this, it may be good if we reflected a bit more on how we do science — to become better researchers through philosophy. Here, I provide an accessible introduction to a philosophical approach that achieves precisely this: William Wimsatt’s multi-perspectival realism. It disabuses us of widespread but misleading myths and idealizations about science, such as the idea that everything in the world can be reduced to a fundamental level, or that we can approach a “view from nowhere” — complete and objectively detached knowledge of the world. Wismatt proposes an alternative view based on his thorough studies of actual research practice. It cuts deeply into the layered yet messy structure of reality, and the improvised but potent tools we have available, as limited and evolved beings, to explore it. Wimsatt reframes science as an irregular yet adaptive process rather than a cumulative repository of unalterable facts. His philosophy provides a workable and grounded middle way between radical skepticism and naïve belief in the objective truth of science. It explains how knowledge is conceptually constructed by humans, but still connects us to reality in a trustworthy way. We need such a new view of science, not only to improve our research practices and outcomes but, more generally, to gain a more realistic understanding of ourselves, the world, and our place and role within it.
EPISTEMIC STIGMERGY: NATURAL VS. ARTIFICIAL INTELLIGENCE
The article\(^{1}\) defends the thesis that intelligent behavior might require not internal complexity but complex interaction. This is demonstrated by the various forms of stigmergy that can be observed both in social insects and in humans. The exposition is structured as follows: (§0) explains how the term “intelligence” is interpreted in the following text; (§1) clarifies the relation between intelligence and complexity; (§2) shows that intelligent behavior does not require internal complexity; (§3) introduces the concept of stigmergy; (§4) presents the mechanisms that give rise to this phenomenon; (§5) distinguishes several types of stigmergic interaction; (§6) briefly discusses the evolutionary mechanisms that could have produced them; (§7) sketches the possible ways in which the concept of stigmergy is used outside biology; (§8) examines collaborative stigmergy in humans; (§9) points to its epistemic projections; (§10) outlines some conclusions concerning the role of artificial intelligence systems and their place in human society.
Guest post: If you’re going to critique science, be scientific about it
Loren K. Mell Editor’s note: This post responds to a Feb. 13 article in The Atlantic, “The Scientific Literature Can’t Save Us Now,” written by Retraction Watch cofounders Adam Marcus and Ivan Oran…
The one science reform we can all agree on, but we're too cowardly to do
OR: the long overdue forest fire
Georgie Newson - Thinking Collectives: Biological Naturalism and the Problem of Group Minds
Leveraging agency for climate change mitigation
Climate debates often frame individual behaviour and systems change as distinct pathways to action. We suggest that social change arises from individuals’ agency within their roles in societal systems, and that this agency should be actively leveraged to achieve meaningful climate change mitigation.
Co-Creation: Systems Thinking Beyond the Machine
Complexity thinking is all the rage — in the arts and sciences. Yet, there are two different strands of thinking about complexity, which are often confounded. The first comes from cybernetics, focussing on control in complex situations. The second is ecological, aiming at sustainable participation in a reality beyond control. Their difference rests on a fundamental distinction: is complexity rooted in feedback regulation or collective co-creation? While feedback remains mechanistic, co-creation generates new spaces of possibilities. We need it to understand life and its evolution. And it empowers us to rewrite our future, to escape our mechanistic cage without abandoning scientific rigor. In this paper, we illustrate how we implement these powerful yet abstract principles through our artistic and philosophical practice.
Appropriate Technology, Permacomputing, Post Growth, and Ecomodernism.
To adapt to the changing climate, we need to radically rethink how and why we do the things we do. From technology, to social movements, to economics. The world is at stake. And we can change it.
The shock of the anthropocene: the earth, history and us
Dissecting the new theoretical buzzword of the "Anthrop…
An epistemology for democratic citizen science
Abstract. More than ever, humanity relies on robust scientific knowledge of the world and our place within it. Unfortunately, our contemporary view of scie
