“Context, Causality and Consequences: from robust evidence to timely action in biology, ecology, law and public policy”

A public conference

Friday 26 and Saturday 27 November 2021

“In what circumstances can we pass from this observed association to a verdict of causation?”

“The 'cause' of illness may be immediate and direct, it may be remote and indirect underlying the observed association.”

“…the decisive question is whether the frequency of the undesirable event B will be influenced by a change in the environmental feature A.”

“What aspects of that association should we especially consider before deciding that the most likely interpretation of it is causation?”

“In occupational medicine our object is usually to take action. (...) we shall wish to intervene to abolish or reduce death or disease.”

“All scientific work is incomplete – whether it be observational or experimental. All scientific work is liable to be upset or modified by advancing knowledge. That does not confer upon us a freedom to ignore the knowledge we already have, or to postpone the action that it appears to demand at a given time.”

A. Bradford Hill: "The Environment and Disease: Association or Causation?", Proc. Royal Soc. Med., p. 295 – 300, 1965, https://doi.org/10.1177/003591576505800503

Speakers

Prof. Denis Noble, University of Oxford
"20th century biology got causation in living systems the wrong way round"

20th century biology was built on three central dogmas: 1. The Weismann Barrier, which was proposed by the geneticist August Weismann in the late 19th century and then incorporated into the standard theory of evolution, the Modern Synthesis. It forbids any causal influence of the soma on the germ-line cells, the future eggs and sperm. 2. The Central Dogma of Molecular Biology, formulated by Francis Crick in 1958 and 1970, which has been interpreted to forbid any causal effect of protein and other regulatory networks on DNA sequences. Causation is assumed to be only one way DNA --> RNA --> proteins. 3. The assumption that DNA is an auto-replicator, replicating like a crystal, and is therefore the cause of all living processes. 21st century biology has shown that all three assumptions about causation in living organisms have been falsified. The consequences for biology, and for many other disciplines, including economics and sociology, that have been influenced by popularizations of 20th century biology, such as The Selfish Gene, are profound. The fundamentals of biology need rebuilding. So do the consequences for other disciplines that have taken causality in biology for granted. (Noble D (2021) The Illusions of the Modern Synthesis. Biosemiotics. 14, 5-24)

Dr. Siguna Müller, Kärnten, Austria
"Causality and SARS-CoV-2 – new findings that mandate a broader perspective"

Based on recent published work, this talk discusses difficulties with, and shortcomings of, more conventional notions of “causality” in the context of SARS-CoV-2 infection and Covid-19 disease. Specific focus will be given to · The role of structural versus sequence-based approaches and determinants involving infectivity and host range of the virus, · The relevance of viral presence alone, versus tissue-specific tolerance and immune responses, in the pathogenicity of this virus, · Beyond-sequence determined factors in the adaptive immune response and their implications for prophylactic treatments.

Dr. Thierry Paul, University of Bologna
"Causality, indeterminism and all that: a quantum entanglement"

In quantum mechanics, repeated measurements of a given quantity (position, energy, ...) on the same system in the same state will not provide the same result: the different consecutive results are randomly distributed according to a probability law depending on the state of the system. This indeterminism is a building block of the quantum paradigm, fully necessary to its consistency, and a source of a lot of misunderstandings. How can causality be handled in front of this intrinsic indeterminism, intrinsic in the sense that it does not result from a lack of "information"? In fact, the quantum evolution contains two parts, totally disjointed: the first one is the evolution of the wave function driven by a differential equation leading to a natural principle of causality, and the second is the indeterministic phenomenon of measurement, whose random result values are taken from a set of possible ones associated to the wave function. We will discuss precisely the impact of the causality of the first evolution on the indeterministic aspects of the second one. We will show that this impact is far from being complete and we will raise the question: can non-causality be considered as a causality itself? We will illustrate this question by recent results in quantum information, such as evolution given only by repeated measurements or the surprising quantum Zeno phenomenon. We will be strictly focused on the mathematical formalism of quantum mechanics – but we will carefully avoid any kind of technicality – hoping that some ideas can be exported to other scientific contexts, and show how it provides peculiarities in the behaviour of "causally" linked natural parameters, for example time and energy.

Dr. Elena Rocca, Norwegian University of Life Sciences
"Difference-maker, mechanism or disposition? How explicating and critically discussing basic assumptions about causality improves scientific evaluations of risk"

Risk assessment is traditionally considered as a discipline-specific matter, requiring different tools and approaches depending on the area of application. In the last years, it became clear that this is problematic since different experts give often diverging risk evaluations, even in the cases where there is empirical agreement over the available data. This suggests that scientists base their conclusions on some premises that are not stated explicitly. We called such premises Philosophical BIAS (Basic Implicit Assumptions in Science), of which one important assumption is about the nature of causality, and one strictly connected the nature of complexity. In this talk, I will use cases of environmental risk assessment of oil pollution and GM technologies to show that depending on the basic understanding of causality and complexity scientists evaluate the available evidence of risk differently. In conclusion, I will present our preferred view on causality and explain why it makes a difference in the approach to risk assessment.

Dr. Maël Montévil, French National Centre for Scientific Research (CNRS)

Organisation, historicity and causality

Two models dominate reflection on causality, namely mechanisms and physics. The former focuses on very local processes, while the latter focuses on ahistorical systems. We argue that neither is a sufficient framework for biology. Instead, in biology, parts of a system collectively maintain each other, which enables us to understand how biological systems maintain themselves. This perspective corresponds notably to autopoiesis and closure of constraints, and is sometimes called organization. In this view, the parts maintain each other, leading to circularities. It implies that a systemic mode of thinking is critical to understand these phenomena. However, they are also historical: the organization they maintain is the singular result of evolution, and they change over time. It follows that causality in biology has two distinct features. First, it has a circular dimension: how do singular organizations maintain themselves? Second, it has to include historical changes: how do we understand the appearance of novelty?

Prof. Giuseppe Longo, Centre Cavaillès (République des Savoirs), CNRS and Ecole Normale Supérieure, Paris
Causality and novelty production in biology

Physics has been framing causality in fundamental principles of “conservation” (energy, momentum…); in some cases, the “causal” terminology may be even avoided (a body falls for “symmetry reasons” according to Einstein, which frames/avoids referring to the “cause” – gravitation). These conservation properties gave unity to a diversity of theories, often incompatible with each other (quantum and relativistic fields, but hydrodynamics and known theories of elementary particles as well …). Causality seems an unavoidable concept in biology: we need to understand how an endocrine disruptor affects an organism and if (and possibly how) it may cause cancer. Can we frame causality in more general principles? Are the first Darwinian principle, “reproduction with variation”, and “enablement” sufficient principles for this purpose? Organisms are not spontaneous self-organization of flows of matter and energy, like hurricanes and flames that are fully described by conservation laws applied to flows, but they are historical objects using flows, canalized by self-generated constraints. What causes what, then?

Prof. Thomas Vondriska, University of California Los Angeles
Chromatin biology and cardiovascular disease (title + abstract to follow)

 

Prof. Ana Soto, Tufts University School of Medicine, Boston
Endocrine disrupting compounds (title + abstract to follow)

 

Further speakers and programme will follow


Practical information

Dates: Friday 26 November 2021, 8:30 – 12:30 and 14:30 – 18:00 CET & Saturday 27 November 2021, 9:00 – 12:30 and 14:30 – 18:00 CET

Venue: EventForum, Fabrikstrasse 12, CH-3012 Bern, Switzerland

Fee: online participation – 10€ (reduced), 50€ (regular), 80€ (solidary) on site participation - 50€ (reduced), 150€ (regular), 250€ (solidary) including lunch on both days

If the fees are still a problem, please contact us.

Recording: The entire conference (lectures and discussion sessions, both on site and online) will be recorded and published.

Registration: by email to This email address is being protected from spambots. You need JavaScript enabled to view it. (please indicate if you wish to participate online or on site in Berne) NB By registering, you consent to your image and voice being recorded during the conference and published. Please transfer the registration fee right away via paypal or bank transfer (Bank: GLS Bank / Account holder: ENSSER e.V. / IBAN: DE21 4306 0967 4030 7947 00 / BIC: GENODEM1GLS)

Keywords: agnotology, ambiguity, causality, cause, co-causal, control, determination, direct cause, effect, evidence, hubris, ignorance, indeterminacy, indeterminism, indirect causes, multi-causality, non-target effect, precaution, Precautionary Principle, precision, probability, risk assessment, target effect, uncertainty


Content of the conference

The understanding of "causes" is at the core of scientific investigations. It underlies all current efforts to face ecosystemic challenges. Physics has framed causality within robust and unifying "conservation principles" (energy, momentum etc.). But how can we understand and verify supposed causal relations within the historicity and diversity of life in a unified manner? How can we scientifically describe the effects which appear to be caused by a chemical or physical event on an ecosystem governed by reproduction and variation and on environments enabling diversity?

A special influence on our notions of causality in biology and ecology is exerted by our advanced reliance on automation, digitization, computers, in-silico models, computational surrogates, artificial intelligence and machine learning. If life-science phenomena are viewed as caused by one or a few selected agents, how does this view align with what can be obtained from a computerized output, with less and less reliance on hands-on experience and human senses for verification?

A paradoxical situation seems to emerge, where this approach appears to enable to flip cause and effect, as exemplified in synthetic biology. Traditionally, say, cloning relied on the appropriate functioning of an entire framework system (environment), such as E. coli, to express a specific gene insert. With the advent of reverse genetics, the same technique is now publicized as being "under the control of the gene" to be expressed. It seems that modeling, and focusing on what one wants to obtain, has shifted the comprehension and understanding of what is cause and effect, demonstrating that the entire framework of causality is not only poorly understood, but little investigated.

When approaching this question from another level, one may ask what the biological influencers of causality are. Is it about material entities (e.g. genes), or also about interactions, relationships, and context (from sub-cellular to ecological)? A unique ability of life is to be able to adapt to a changing environment. So one may ask: what causes habituation and learning, and in which way do these influence the appearance of causality (in gene expression, disease and other phenomena)?

"Science is the organised attempt to discover how things work as causal systems."[1] But in current biology and ecology every cause has multiple effects and every effect has multiple causes. So at this conference we study notions of multi-causality within complex systems that encompass many variations, in time and space, of the "known" co-causal factors, whilst acknowledging the existence of many other unknown, yet possibly influential variables.

There are some current attempts to re-introduce simple causality, for example, in searches for the particular gene or environmental circumstances that are relevant to a specific biological trait, via genetic modification which is claimed to be "precise". However, other approaches are attempting to identify modifiable co-causal factors within context and time dependent complex biological and ecological systems, factors which enable both life and harms to emerge and which, if removed or reduced in a timely manner, would result in less harm to people and environments. Such approaches to identifying robust causal inferences in biology, ecology, tort law and public policy on health and environment eschew simplistic dichotomies (e.g. nature/nurture; gene/environment; acute/chronic; effects/adverse effects; statistically significant/insignificant effects; association/causation; valid/invalid arguments) in favour of continuums, or spectrums, along which choices need to be made as to where and when positions on such continuums justify robust causal inferences.

Current approaches to coaxing causality from complexity also include systematic review methodologies; systematic approaches to integrating different evidence streams; and "inferences to the best explanation" used in tort law. There are also approaches that render explicit and transparent the often implicit sources of divergent evaluations of the "same" evidence, which can be illustrated historically with: leaded petrol; low dose ionising radiations; and antibiotics as animal growth promoters; and currently with: per- and polyfluoroalkyl substances (PFAS); glyphosate; neonicotinoid insecticides; and electromagnetic fields (EMFs).

These sources of divergent evaluations include (1) different types of paradigms, assumptions and argumentation used; (2) the diverse disciplinary conventions of toxicologists, endocrinologists, epidemiologists, biologists, ecologists, and lawyers; and (3) their value based choices. Public and stakeholder involvement in helping to identify robust causal inferences for public policy interventions have also been used, sometimes including communities affected by harms. The value of these approaches will be reviewed.

[1]          Waddington, C.H. (1943), "The Scientific Attitude", second revised edition, Penguin