“We are evolved creatures. Our physical attributes, behavioural dispositions, and cognitive capacities have developed in reaction to and by using the environments in which our ancestors, from microbes to modern humans, have reproduced more successfully than their competitors.”
This is (the sketch of) a scientific, causal explanation of why we are the way we are and do the things we do.
The practice of explaining things that way has evolved, too: It has been more successful in its (cultural, intellectual, economic) environment than competing practices. And it is connected with and built upon a host of other evolved practices: Logic, statistics, a certain way of doing natural science. All of these practices can be explained scientifically, extending the above sketch.
But by doing so, we are also using these practices.1 While we account for them from a third-person perspective, they shape our thinking and thus define our perspective onto the world and, eo ipso, onto themselves: our first-person perspective.
What is distinctive about our first-person perspective, more than any form of consciousness, is its discursive structure. As evolved animals, we are discursive creatures:2 We have been evolutionary successful due – among other things – to our ability to use concepts and reason collaboratively.
This ability enables us to explain practices from the outside – but also to articulate them from the inside, from within the first-person perspective. A violin-maker, e.g., can spell out the actions and rules involved in creating a violin, even if she can’t explain why and how they work scientifically. And what’s more, she can more effectively help someone learn to build a violin by articulating the practice than by explaining it scientifically.3
This is also how science itself is learned – by following the practices other scientists are using and articulating. So are philosophy, mathematics, architecture, software development. To learn them is not about knowing something, but about knowing how to do something.4
When practices evolve, they do so not only by natural and cultural selection – they are also advanced by critique. Articulating, questioning, and validating them helps make them fitter for their environment. We can consciously change rules and actions, and test their practicability and success; we don’t have to rely on random mutation. This is what we call design.5
Practices, scientifically speaking, contain models they use to make sense of the world. When articulating a practice, we describe these models using a certain language, providing the theory of the practice.6 Its form is partly shaped by the practices used in the articulation.
The theories of our technically most advanced practices are articulated mathematically and thus shaped by the (perceived) current state of mathematics. This is why mathematical objects as different as Platonic solids and the so-called amplituhedron play similar roles in ancient and current physics’ endeavour to explain what the world “really is”, representing the current state of mathematics then and now. And it is how the intellectual edifice of modern economics could be built upon what is now seen as a misunderstanding of fundamental statistical concepts.
Theories of other practices will take different forms – they might focus on patterns described in a semi-formal language (architecture), frameworks and methods relying heavily on visualisation (collaborative sense-making), or decision procedures aiming for reflective equilibria (ethics). A theory is helpful for training and critique if it has a form that fits the practice and its practitioners’ goals and capacities.
The models at the core of our practices don’t represent the world in a way that can be meaningfully evaluated as more or less faithful – for this, we would need access to the world that is unmediated by models. The theories describing the models aren’t selected for their consistency and elegance, either – astrology, e.g., was in no way inferior to early astronomy in this respect.7 As parts of practices, models and theories are selected for the success we achieve when using them instead of their rivals. Their use increases with their usefulness.
The same goes for the criteria we use when selecting them – and thus for our understanding of rationality. We are “instrumentally rational” when our means fit our ends – when we successfully use our practices to achieve our goals. This is the scientific, third-person view of rationality. From a first-person perspective, rationality as a demand on practices can be articulated in different ways – e.g. as requiring coherence, conformity with (specific) reasons, or objectivity. Which description we prefer is a matter of evolutionary fitness – of whether a description is useful for advancing certain practices, and of whether it survives and reproduces in its intellectual environment, e.g. scientific publishing or academic philosophy.
The articulation of rationality can cover the internal structure of a particular practice, e.g. architecture or ethics, and thus describe its specific conception of rationality or “logic”. Or it can abstract away from particular practices and try to describe a general conception of rationality or a universal logic. The first is what the reflective practitioner does; the second is the philosopher’s job.
This is why doing meaningful philosophy is so hard: Articulating and critiquing rationality in toto requires a high level of abstraction as well as an acute sensibility for the border between useful generalisation and complete dissociation from particular (and particulars of) practices.8
From all of this follows that the two perspectives are complementary. Without either, our understanding of the world and us in it is incomplete: First-person articulations that don’t correspond to third-person explanations are fantastical; third-person explanations that aren’t grounded in and bounded by first-person articulations are imperialist.
Only if we avoid both traps and instead respect both perspectives9 do we find reason.
- Dennett, D. C. (2017), From Bacteria to Bach and Back: The Evolution of Minds
- Dreyfus, H. (2002), “Intelligence without representation – Merleau-Ponty’s critique of mental representation”, Phenomenology and the Cognitive Sciences 1: 367–383
- Haugeland, J. (1998), Having Thought. Essays in the metaphysics of mind
- Ismael, J. (2013), “Naturalism on the Sydney Plan”, in: Haug, M. C. (ed.), Philosophical Methodology: The Armchair or the Laboratory? 86–104
- Lance, M., and Kukla, R. (2010), “Perception, Language, and the First Person”, in: Weiss, B., and Wanderer, J. (eds.) Reading Brandom: On Making it Explicit
- Luhmann, N. (1984), Soziale Systeme. Grundriß einer allgemeinen Theorie
- Polanyi, M. (1966), The Tacit Dimension
- Rouse, J. (2015), Articulating the World: Conceptual Understanding and the Scientific Image
- Sellars, W. S. (1963), “Philosophy and the Scientific Image Man”, in: Sellars, W. S., Empiricism and the Philosophy of Mind: 1–40
I am grateful to Michael Schieben, Gregor Groß, and Phil Harvey for comments on earlier drafts of this essay.
Accounts similar to the one developed here can be found in Ismael (2007), Lance and Kukla (2010), and Rouse (2015), all of which belong in the so-called Neopragmatist camp of philosophy. ↩
Since other species’ first-person perspectives are inaccessible to us, we have no way of validating this distinction fully, but research into their linguistic capabilities shows these don’t match the abstraction, creativity, and normativity available to humans. Even if the concept of morality is particular to humans, though, this doesn’t mean other animals’ perspectives are morally discountable. ↩
This resonates with Michael Polanyi’s distinction between explicit and tacit knowledge: while explanation might be a powerful tool to convey the former, it is unsuited to transmit the latter. ↩
The relationship between these modes is controversial. A major strand in philosophy and cognitive science views knowing how as primary, arguing that propositional is derived from practical knowledge or that “competence precedes comprehension”. ↩
Daniel Dennett refers to this as “intelligent design” and also contrasts it with (Darwinian) natural selection. ↩
The theory of a practice, in my use of the expression, articulates what the practice itself and the model at its core take the world (or the part of the world they deal with) to be or to be for as it is relevant to the practice. This is not to be confused with a theory that explains from outside the practice why and how it works in terms of a different field of knowledge. For example, the violin-maker’s theory of violin-making will articulate why and how skilled actions will result in certain results (hopefully, a great-sounding violin). In contrast to that, a sociological theory of violin-making might explain why and how the skills involved were discovered, passed on, and monetised; a physical theory might explain why and how modifications of material result in a specific sound of the finished violin. ↩
In fact, when originally conceived, astronomy and astrology represented a unified way of looking at (astronomy) and explaining (astrology) celestial bodies and their motions. Only with the arrival of the Scientific Method and the demise of geocentrism, this changed and both disciplines got separated. The ensuing scientific success of astronomy was complemented much later by the resurgence and (pop-)cultural success of astrology. ↩
As an example, from this perspective, Niklas Luhmann’s rationalist systems theory is a hyper-reductionist and thus overgeneralized articulation maladapted to describe, critique and advance actual practices. ↩
This demand is similar to Wilfrid Sellars’s call for a “fusion” of the Manifest and the Scientific Image. ↩