Goals of the Institute

While our ultimate goal is to describe the rules governing and emerging from living systems in a language as precise as possible, we recognize that we currently lack the necessary language. We wish to work toward the generation of such a language.

Bringing humanists, who have experience with rigorous analysis of complex issues in a way which is not necessarily anchored in mathematics, into a conversation with scientists, can generate the synergy necessary to advance our thinking and deepen our understanding of complex issues. Such discourse may not lead us to hard answers, but it might allow us to better understand the terrain which we must navigate in the gap between the mathematical and the biological; between a system’s structure and its behavior. This type of analysis, neither fully empirical nor fully mathematical, is much more active in the humanities; scientists, no doubt, can benefit by being in a dialogue with those steeped in these disciplines.

It's important to note, however, that we are not resigning ourselves to a permanent failure of mathematical description, nor are we suggesting that mathematical work be abandoned. But we offer that non-mathematical discourse and analysis can work in productive synergy with mathematical and empirical studies.

Indeed, consider the major scientific paradigm shifts of the past: Newton’s theory of gravity, Darwin’s theory of evolution, Einstein’s theory of relativity, etc. Each of these relied on thought experiments which may have initially appeared fanciful and imprecise and required a long “maturation period” before they could be expressed in a precise form.

These major paradigm shifts were all driven by individuals situated within a single discipline. Given the complexity of life sciences of the 21st century, such major shifts, we argue, necessitate a broader multi-disciplinary approach, gaining insight from diverse scholars each deeply situated within their discipline.

The questions we are considering are at a higher scale of complexity and, as such, may require an even greater interplay of diverse ideas. They also require more meta-thinking (philosophy) about what our goals are in the first place and what the limitations to our knowledge are that prevent us from achieving these goals. By understanding the boundaries of knowledge, we can add clarity to what can be known as well as what cannot, thus illuminating potential productive avenues of inquiry.

One can broadly distinguish between two types of problems:

• Meta-problems that are concerned with clarifying the terrain, methodology, interpretation and limits of science (e.g., ethics, truth, knowledge, the epistemic status of models.)
• Inquiries aiming to further our understanding of the “big unknowns” of the organization of living systems (e.g., organismal development, cognition, language, and communication, etc.)

These two types of problems overlap. For example, cognition involves knowledge and language involves representing and modeling reality.

In light of the great challenges posed by problems of organized complexity, it is useful to study, both philosophically and practically, the limits of what knowledge we can lay claim to. On a practical level, it is important to increase our understanding of the relationship between abstract models, which are based on only a partial distillation of biological principles, and the reality which they purport to model.

What is the proper level of abstraction needed in designing such phenomenological models of biological organization that still faithfully reflect components of reality? The philosophy of epistemology can prove a useful guide in this endeavor to understand the limits of knowledge.

But an understanding of scientific truth is not purely philosophical. Currently our politics are marked by a crisis of trust in scientific truth. We can begin to address such a crisis by clarifying our own understanding of what constitutes truth and admissible evidence, and how to effectively and ethically communicate uncertainty.

Additionally, we can investigate the extent to which the scientific method retains its privileged status in the age of big data, and whether we can add principles of scientific reasoning to reflect modern practices.

Organization refers to the ways in which a system's architecture results in its various complex functions and forms. Organization exists throughout a hierarchy of scales: from RNA and proteins to cells, from organs to organisms to societies and ecosystems. Organization also occurs through time: from the scale in which gene-regulatory dynamics play out…to "developmental time" in which an organism develops and matures..;to “somatic time” representing an individual’s lifespan..to evolutionary time, meaning the period during which all biological systems are molded and organized by the forces of evolution. As such, we seek to study the organizing principles of organization.

Furthermore, a study of organization must examine the ways in which individual systems and their development are embedded within an environmental context and within larger collectives.

We are particularly interested in the ways in which systems process and exchange information. While the concepts of cognition, knowledge, language and communication are typically applied to human or animal cognition, they are in line with concepts which are more widely applicable to general living systems, such as the coding and processing of information, and the exchange of signals across communication channels.