Doing science without making any basic philosophical assumptions is impossible. But are all philosophical assumptions biases? No. Sometimes these assumptions are chosen deliberately and explicitly by the scientist, and used as auxiliary premises for theoretical purposes. For instance, one might adopt a philosophical assumption such as determinism to make a certain model work. Determinism is the assumption that, given a set of initial conditions, there is only one possible outcome. For instance, we could build a model of population growth which assumes that growth is completely determined by the initial population density: any deviations from the predictions of this model could, therefore, be taken as evidence that factors other than the initial conditions have an influence on population growth (Higgins et al., 1997). So even if one does not believe that determinism or some other philosophical assumption is true in all situations, making such an assumption can still serve a purpose.

When philosophical premises are chosen explicitly and purposely in this way, we would not call them 'biases'. In most cases, however, scientists remain unaware of these assumptions and of how they influence research. When a philosophical premise is implicitly accepted in our theories and methods, it becomes a philosophical bias. How does this affect the life sciences?

Philosophical biases are typically acquired from science education, professional practice or other disciplinary traditions that define a scientific paradigm. This is why scientists with varying backgrounds might adopt different philosophical biases. Biology, for example, is concerned with both entities and processes (Nicholson and Dupré, 2018). The standard ontological assumption is that entities (such as proteins) are more fundamental than processes, and that processes are produced by interacting entities. Molecular biologists have traditionally taken this as the default position. The ability of entities, such as proteins, to interact with each other is determined by their chemical structure, so to understand processes (such as the interactions between proteins), we need to understand the entities themselves in detail.

Doing science without making any basic philosophical assumptions is impossible. But are all philosophical assumptions biases?

However, some scientists take the view that processes are more fundamental than entities (Guttinger, 2018). In this view, entities are understood as being the result of processes that are stable over some length of time, and the best way to understand the behavior of an entity is to study the relations it has with other entities, rather than its internal structure. Ecologists tend to take this view, thinking in terms of systems in which the properties of individuals and species are determined by their relationships with each other and their environment.

The tension between these two ontological positions is not a purely philosophical or abstract point, it can have practical consequences. Ecologists and molecular biologists, for example, had different views about GM crops in early debates about their safety: ecologists focused on the unpredictability of environmental effects caused by GM crops, and had no strong opinions on similarities and differences between GM crops and conventional crops. Molecular biologists, on the other hand, stressed the fundamental equivalence between GM crops and conventional crops, while dismissing issues related to the predictability of environmental effects (Kvakkestad et al., 2007). Two of the present authors (ER and FA) have studied a similar clash of philosophical biases in the debate about the safety of stacked GM plants (that is, plants where conventional breeding techniques are applied to GM plants; Rocca and Andersen, 2017). One school of thought viewed the new plant as a conventional hybrid and argued that, in most cases, one can deduce the safety of the new plant from knowledge of the safety of its parental GM plants. This means thinking about complexity as being various combinations of unchanging parts. The other school, however, argued that one cannot deduce the safety of the new plant from the safety of the parental GM plants. Here, complexity is thought of as an emergent matter where parts lose their properties and identity in the process of interaction.

It is crucial that decision-makers (such as governments and regulatory agencies) are aware of these non-empirical aspects of science when introducing laws and regulations in controversial areas.