Here you will find publications, presentations and other products of the Possible Life project.
Knuuttila, Tarja & Andrea Loettgers. 2017. Biology & Philosophy 32: 1185-1203
The attempt to define life has gained new momentum in the wake of novel fields such as synthetic biology, astrobiology, and artificial life. In a series of articles, Cleland, Chyba, and Machery claim that definitions of life seek to provide necessary and sufficient conditions for applying the concept of life—something that such definitions cannot, and should not do. We argue that this criticism is largely unwarranted. Cleland, Chyba, and Machery approach definitions of life as classifying devices, thereby neglecting their other epistemic roles. We identify within the discussions of the nature and origin of life three other types of definitions: theoretical, transdisciplinary, and diagnostic definitions. The primary aim of these definitions is not to distinguish life from nonlife, although they can also be used for classificatory purposes. We focus on the definitions of life within the budding field of astrobiology, paying particular attention to transdisciplinary definitions, and diagnostic definitions in the search for biosignatures from other planets.
Knuuttila, Tarja and Andrea Loettgers. 2018. in Bas van Fraassen, and Isabelle Peschard (eds.) The Experimental Side of Modeling. University of Minnesota Press, 118-147.
Collected volume's abstract: Offering a radically new conception of the role of data in the scientific modeling process, this cutting-edge volume offers a multifaceted view on experiments as designed and shaped in interaction with the modeling process. Highlighting the mediating role of models and the model-dependence (as well as theory-dependence) of data measurement, it proposes a normative and conceptual innovation in scientific modeling.
Knuuttila, Tarja and Mary S. Morgan. 2019. Philosophy of Science 86: 641-661.
Deidealization as a topic in its own right has attracted remarkably little philosophical inter- est despite the extensive literature on idealization. One reason for this is the often implicit assumption that idealization and deidealization are, potentially at least, reversible processes. We question this assumption by analyzing the challenges of deidealization within a menu of four broad categories: deidealizing as recomposing, deidealizing as reformulating, de- idealizing as concretizing, and deidealizing as situating. On closer inspection, models turn out much more inflexible than the reversal thesis would have us believe, and deidealization emerges as a creative part of modeling.
Knuuttila, Tarja and Vivette García-Deister. 2019. Studies in History and Philosophy of Science 77: 101-111.
Although the interdisciplinary nature of contemporary biological sciences has been addressed by philosophers, historians, and sociologists of science, the different ways in which engineering concepts and methods have been applied in biology have been somewhat neglected. We examine – using the mechanistic philosophy of science as an analytic springboard – the transfer of network methods from engineering to biology through the cases of two biology laboratories operating at the California Institute of Technology. The two laboratories study gene regulatory networks, but in remarkably different ways. The research strategy of the Davidson lab fits squarely into the traditional mechanist philosophy in its aim to decompose and reconstruct, in detail, gene regulatory networks of a chosen model organism. In contrast, the Elowitz lab constructs minimal models that do not attempt to represent any particular naturally evolved genetic circuits. Instead, it studies the principles of gene regulation through a template-based approach that is applicable to any kinds of networks, whether biological or not. We call for the mechanists to consider whether the latter approach can be accommodated by the mechanistic approach, and what kinds of modifications it would imply for the mechanistic paradigm of explanation, if it were to address modelling more generally.
Koskinen, Rami. 2019. Philosophy of Science 86: 1123-1133
Critics of multiple realizability have recently argued that we should concentrate solely on actual here-and-now realizations that are found in nature. The possibility of alternative, but unactualized, realizations is regarded as uninteresting because it is taken to be a question of pure logic or an unverifiable scenario of science fiction. However, in the biological context only a contingent set of realizations is actualized. Drawing on recent work on the theory of neutral biological spaces, the paper shows that we can have ways of assessing the modal dimension of multiple realizability that do not have to rely on mere conceivability.
Carrillo, Natalia & Knuuttila, Tarja. 2020. Forthcoming in Alejandro Cassini and Juan Redmond (eds.) Models and Idealizations in Science: Fictional and Artefactual Approaches (Cham: Springer)
There are two traditions of thinking about idealization offering almost opposite views on their functioning and epistemic status. While one tradition views idealizations as epistemic deficiencies, the other one highlights the epistemic benefits of idealization. Both of these, however, identify idealization with misrepresentation. In this article, we instead approach idealization from the artifactual perspective (Knuuttila 2005, 2011, 2017), comparing it to the distortion-to-reality accounts of idealization, and exemplifying it through the case of the Hodgkin and Huxley model of nerve impulse. From the artifactual perspective, the epistemic benefits and deficiencies introduced by idealization frequently come in a package due to the way idealization draws together different resources in model construction. Accordingly, idealization tends to be holistic in that it is not often easily attributable to just some specific parts of the model (even though it might seem so at first glance). Instead, the idealizing process tightly embeds theoretical concepts and formal tools into the construction of a model.
Koskinen, Rami. 2020. ChemBioChem 21: 2591
Besides having potential medical and biosafety applications, as well as challenging the foundations of biological engineering, xenobiology can also shed light on the epistemological and metaphysical questions that puzzle philosophers of science. This paper reviews this philosophical aspect of xenobiology, focusing on the possible multiple realizability of life. According to this hypothesis, what ultimately matters in understanding life is its function, not its particular building blocks. This is because there should, in theory, be many different ways to build the same function. The possibility of multiple realizability was originally raised in the context of AI’s hypothesized capacity to realize mental functions. Because we still do not have any incontrovertible examples of digital minds, not to mention alien life of foreign biochemistry, the best way to test this philosophical idea is to examine the recent results and practices of synthetic biology and xenobiology.
Knuuttila, Tarja & Koskinen, Rami. 2020. Synthese topical collection “What to Make of Highly Unrealistic Models”
The recent discussion of fictional models has focused on imagination, implicitly considering fictions as something nonconcrete. We present two cases from synthetic biology that can be viewed as concrete fictions. Both minimal cells and alternative genetic systems are modal in nature: they, as well as their abstract cousins, can be used to study unactualized possibilia. We approach these synthetic constructs through Vaihinger’s notion of a semi-fiction and Goodman’s notion of semifactuality. Our study highlights the relative existence of such concrete fictions. Before their realizations neither minimal cells nor alternative genetic systems were any well-defined objects, and the subsequent experimental work has given more content to these originally schematic imaginings. But it is as yet unclear whether individual members of these heterogeneous groups of somewhat functional synthetic constructs will eventually turn out to be fully realizable, remain only partially realizable, or prove outright impossible.
Knuuttila, Tarja and Andrea Loettgers. 2020. in Sune Holm and Maria Serban (eds.) Living Machines? Philosophical Perspectives on the Engineering Approach in Biology. Routledge.
One striking feature of the contemporary modeling practice is its interdisciplinarity: the same function forms and equations, and mathematical and computational methods are being transferred across disciplinary boundaries. Within philosophy of science this interdisciplinary dimension of modeling has been addressed by both analogy and template-based approaches that have proceeded separately from each other. We argue that a more fully-blown account of model transfer needs both perspectives. We examine analogical reasoning and template application through a detailed case study on the transfer of the Ising model from physics into neuroscience. Our account combines the analogy and template-based approaches through the notion of a model template that highlights the conceptual side of model transfer.
Knuuttila, Tarja. 2020. in Wenceslao J. Gonzalez (ed.) Language and Scientific Research. Palgrave McMillan.
This paper discusses modeling from the artifactual perspective. The artifactual approach conceives models as erotetic devices. They are purpose-built systems of dependencies that are constrained in view of answering a pending scientific question, motivated by theoretical or empirical considerations. In treating models as artifacts, the artifactual approach is able to address the various languages of sciences that are overlooked by the traditional accounts that concentrate on the relationship of representation in an abstract and general manner. In contrast, the artifactual approach focuses on epistemic affordances of different kinds of external representational and other tools employed in model construction. In doing so, the artifactual account gives a unified treatment of different model types as it circumvents the tendency of the fictional and other representational approaches to separate model systems from their “model descriptions”.