Before asking what design is, we are asking how design works.
That is, how are design products interpreted by mind like ours. That a reasonably good and workable theory of the mechanics of the mind is needed is the consequence of the fact that if you do not have a theory of how the mind works, you are likely to have a theory, and the latter is invariably a kind of blank slate account. Blank slate theories Pinker claim that your mind is a sheet of wax, totally virgin and undifferentiated at birth, and that experience will write on the wax, leaving traces that constitute your mental makeup.
Today we know that things are more complicated, and we also know how much more complicated they are, but here we can make a very long story relatively short. A few theoretical results of recent cognitive science are particularly important for a discussion about design and its reception.
1. Perceptual systems follow their own logic
The first is that perceptual systems build objects out of pieces that are found in the perceptual scene, and that they do it following their own logic, without listening much to other systems such as memory or the conceptual system. For instance, vision creates three objects, Head, Tail and Box, with the black pixels and the outline in the scene on the right.
However, if you see Head and Tail move and get placed at the two sides of Box, so that their boundaries are aligned on the two sides, you will instantly see a complete but overstretched horse. Now consider: you never saw a Stretched Horse before, and you always saw non-stretched horses; you know that such an animal is biologically impossible (it would have trouble in negotiating turns); you further remember that it was built under your eyes by moving around Head and Tail; all of the above, but no matter what, still you cannot but see an overstretched horse partially occluded by Box when you are confronted with the scene. This means that vision has its own rules for deciding what is an object and what it is not, and ignores what other systems know or may think they know.
The visual system in a sense is super smart, as it makes sense of complex scenes by simplifying them, in another sense it is super stubborn, as it cannot be corrected by what we know or think we know. Stubbornness is not bad in most contexts, as the important thing for the visual system is not to give a scientifically accurate representation of reality, but to react quickly with approximate representations that in turn make quick actions possible. This implies that the system will misfire in many contexts, in particular in non-natural contexts such as those created by humans. So it is important to understand that the rules for visually assembling objects are not what we think.
What are these rules? We still do not know completely. D. Hofmman, Visual Intelligence. P. Tse. Casati and Cavanagh, The visual world of shadows You may think that the dominating rule for the stretched horse is “build an occlude object if you spot boundary alignment on the two sides of the occlusion”, and this surely will work fine in many occasions, but not in others.
Research is still ongoing.
2. Interpretive systems understands artificial objects as having intentions
The second theoretical piece that matters for the study of design in context is linked to the fact that designed objects are just that, designed objects, that is, artifacts, artificial items that end up populating and at times replacing the natural world. Now, the human mind has a powerful set of weapons for interpreting what people say and do, and it is happy to fire these weapons on whatever result of human action, in order to make sense of it. Perceptual systems simplify the scene by assembling objects from found pieces, and interpretive systems simplify the representation of the environment by understanding others not as behaving randomly but as having intentions, and further by understanding artificial objects as the results of intentions. As a result, the artificial world in which we live “talks” to us without ever stopping, telling us stories of decisions, intentions, plans, and of ways in which plans were carried out. If you find a plastic pole in the desert, you can almost feel your brain frantically trying to figure out answers to the questions such as: Who did it? Why? What does it mean? What did the maker had in mind when she planted the pole?
It can also misfire, as the perceptual systems do, and this is what prevents widespread acceptance of the theory of evolution, by finding intentions where there are none, e.g. a mind that creates complex living beings.
How does this interpreting work? The interpretive system is a powerful inferential system, that draws conclusions – about the relevance of what is said or done – without you knowing it, and delivers results you may be surprised about. If you sit next to the closed window and someone says out of the blue, looking at you, “It’s stuffy in here”, you likely interpret her as meaning that you should open the window. She never mentioned the window or opening it, but your brain maximized the relevance of that otherwise out-of-the-blue assertion. “Why did she say that? She was talking about differential equations! She should have meant something unrelated to maths. It is stuffy in here, I agree, but why draw the audience’s attention to this fact of the matter? And above all, but why does she stares at me when she says that it’s stuffy in here? Ah of course, I’m the only one sitting next to the window.”
And as for assertions and other language acts, so for artificial objects. Our world is packed with artifacts that do not sit there like stones or trees: they beg interpreting them. Some speak for themselves, others require a bit of work and other yet require even more work because they are systematically misinterpreted.
3. Affordance
What is it for an artifact to speak for itself? The third important notion we get from the cognitive sciences is the notion of affordance. Some objects are particularly fit for our cognitive apparatus, which in turn is embodies in a body with very specific features. We are not 10m tall, our fingers are not 3mm or 3m long. Some objects afford more than others, given the fact that we have this body, and that we know or feel how our body is made. A 3m high door affords passage, a 23cm high door doesn’t. A 1mm long handle does not afford grasping, and neither does a 50m long handle. de Vignemont, Mind the body; Gibson, The Ecological Approach
The theme of affordances is connected to, but does not reduce to, that of ergonomic specifications which is of course crucial to design production and use. Here affordances enter our discussion on the reception side: thanks to a certain ingenuity in orchestrating them, we can create objects that speak for themselves – or not. (Ergonomy is about making objects that are optimally usable, not about making objects that speak for themselves.) So here is what is bound to happen. An object can both speak for itself and be conducive to the function it is supposed to have. “Good” handles, of course, fall into this category. They have a form that affords grasping, are placed at the right height, etc. Some objects may not speak for themselves at all; “poor” handles are hard to find and to grasp, and they fail their mission. But there also objects that afford certain actions, and thus trigger a certain interpretation, no matter what. If you plant a plastic pole in the desert, bystanders will see it a something that must be seen, as something that is typically used for supporting something else, as part of a barrier, and as the context may be not very cooperative for any of those immediate, affordance-related interpretations, they may start looking for reasons. Our brain is trying to compute the relevance of each artifact it encounters in each context.
We have thus in our minds an object-builder builder daemon and a relevance seeker daemon. They work for us, they are never at rest, and sometimes they work against us; at a minimum, by never letting us rest. A world that is crowded with artifacts is a world that is crowded with intentions to decipher, and this deciphering work is guided by the way affordances are orchestrated by designers. Pignocchi, Slate article on Intentionalization of nature. Counteradaptive consequences for science and understanding of nature
4. Two systems
The two daemons are metaphorical representations. A final lesson from the cognitive sciences is contained in a further metaphor, the image of the two systems or modes. The idea is simple: some of our engagements with the environment and with others are fast, unconscious, proprietary, mandatory once a certain stimulus is presented to us, and not modulated by the will. This is a Mode 1 (or system 1) way of working. Other engagements are slow, modulated by the will, and tap into attentional and working memory resources: this is Mode 2 (or system 2).
For instance, the Stretched Horse visual construction presented above is a Mode 1 way of functioning. But you can also visually imagine that two horses are hiding behind the Box, each of which is only partially visible: this requires careful attending, conscious imagining, and keeping actively in memory, all hallmarks of Mode 2 .
The distinction generalizes to the wider spectrum of cognition. If you learned your multiplication table, you have a Mode 1 answer to simple requests such as “6 times 6”. “36” pops out in no time. If you want instead to know the answer to “36 by 36”, you likely have to switch to a Mode 2 operation, you have to tap into memory and attention resources, so as to keep part of the computation in mind when performing another part of the computation, etc. (which means that the slightest distraction will kill or seriously impair the process).
Or, to give yet another example, if you enter a building, you do not in the norm need to look up a map or to consult a GPS based navigator to find the exit; you orientation brain does this for you in Mode 1 without you even knowing it. If on the other hand you are requested to go from where you are to a destination that you know but which is not along your normal route, say from Place de la Concorde to the Eiffel Tower in Paris, you engage in a Mode 2 navigational computation, that requires thinking of way points, imagining turns, rehearsing a sequence of landmarks, all activities that again put some strain on attention and working memory.
So here is our theoretical apparatus: focus on object building and relevance seeking, in fast or slow modes, on the background of an objectively fixed set of affordances (objectively, i.e. related to our body and movements’ specifics). It appears to be a relatively lean apparatus, but of course it is the distillation of many decades of theory advancements in the cognitive sciences. The main idea behind all this is that the mind-brain is a machine that processes environmental and bodily information so as to create internal representations of the world that are then used to guide action. This machine is not an all-purpose computer with many different pieces of software, but is actually an assembly of many submachines, each of which endorsed with a relatively specific task, proprietary software, and with very constrained intermachine communication. The resilience of the Stretched Horse to top-down knowledge is an example of this poor communication, which has a reason: you do not want your perception to be modulated at will a visual system that only sees what you want to see or what you think it should see is useless and counter adaptive. This is not to say that you cannot sharpen your viewing practices; you may not modulate your vision directly, but you can modulate your visual attention. And this is also what this book is about.
Actually, this is a notebook more than a book. We want to convey a sense of the pervasive presence of design, and of its consequences given the way our minds are shaped. In the end, we are calling for more cognitive and anthropological studies of the designed world. At the same time, we are probing this world with items that still belong to the toolbox of old-old fashioned explorer, on a mission in a distant, unknown continent.
