There is often something in an artifact which does not conform to the cognition and working mode of humans. Take, for instance, a glass door without handles. This door, in itself, opens and closes just as it is supposed to be. But people, searching for visual and tactile clues, for protrusions or moulds suggesting how that door is intended to be opened, have, in the absence of a clue, troubles with it. Donald Norman labeled this phenomenon “affordance”.
The ideal “alien” object provides no clue
The distance, or difference, between artifacts and humans is mediated by design. Designers deal with it in subject areas such as ergonomics, human factors and user interface design, with designs ranging from door handles to car interiors and the “hamburger” symbol on websites. The difference is best exemplified in objects which provide no anthropological cue, no layer of code for human perceptive access. The monolith in Stanley Kubrick’s 2001: A space odyssey is the ideal “alien” object. It does not, how lesser Sci-Fi movies approach the theme, express alienness as something contorted and aesthetically grotesque. It is simply an object which provides no clue for human perception.
Artifacts follow their own technical evolution, which tends to gradually diminish the distance between humans and objects. Mechanic parts have been replaced by electronics, making the inner workings of technical objects smaller and the space allocated for interfaces larger.
Humans mediated this difference by adapting themselves. Rock climbers scan the rock for usable dents and protrusions, stretching their body so that fingers and toes find footing. Rock walls occuring in nature are not designed to be used by rock climbers for thrill and entertainment. Yet rock climbers say that they are more fun than designed climbing walls. The motivation here is a drive which must have been useful in human evolution: the motivation to overcome an obstacle.
This distance between humans and artifacts brings forth desirable qualities: solving problems, adaptation, learning, mastering skills
This idea is also present in a piano: Not a natural object, it is still a challenge to master. The design of a piano is determined by its function. Its keys are arranged in a linear manner, corresponding to the arrangement of the strings inside the piano. When we play a piano, it is not the piano keys who adapt to our fingers, it is our fingers which adapt to the keys. The distance or difference between humans and artifacts is not necessarily convenient, but it brings forth a whole range of desirable human qualities: solving everyday problems, adaptation to a given situation, learning, mastering skills. Last but not least, it is this difference which made us design machines which are more intelligent and more convenient.
For philosopher Guenther Anders, the Promethean slope is an effect in which the factual constraints given by machines can at some point not any longer be cognitively and emotionally comprehended by humans. With the increasing sophistication of Digital Machines, the inner workings of devices and services are increasingly hidden from view.
Early machines could be recognized by way of their own limitations: Instrument panels with levers and buttons, waiting for human intent expressed in physical action, have been the interfaces of early machines. In the beginning of the digital age, computers could only be manipulated by writing code into a command line interface. A combination of peripheral hardware (the computer mouse) and an additional layer of programming for graphical interfaces eliminated the need to know code.
With touch screens, the interaction with the elements on the screen became even more immediate. With gesture tracking devices and intelligent language processing interfaces, technology is not any more signified by its own limits: Personal assistants such as Amazon Echo only need a name to be uttered, followed by a question or instruction.
Humans use the same parts of the brain to interact with machines as they do to interact with humans and attach gender, racial or other stereotypes to machine voices just as they do to human voices (Nass 2007). Once the limits that signified technology disappear, humans do not know that they are interacting with technological devices and software.
People mostly do not realize when they are interacting with an algorithm
The Japanese robot Paro, designed for senior citizens in homes for the elderly, simulates emotional affection so convincingly that it can make elderly people cry. Similarly, ‘followers’ can be recruited with ‘bots’, algorithms that search through online data such as Twitter and Instagram hashtags to add random ‘likes’ and comments, thus simulating personal engagement. People mostly do not realize that they are interacting with an algorithm:
“Except for a single user …nobody …seemed to mind the extra likes or comments (created by bots).
In fact, most of them would respond immediately with comments of their own. “Thanks dude!” they’d say. Or they’d simply give me a “[Praying Hands emoji].” I got hundreds of comments like this.” (Chafkin, 2015)
The evolution of voice-enabled personal assistants leads to autonomous social agents, “evolving intelligent communicative machines that are capable of truly understanding human behavior” (Moore 2015). With emotion recognition – the analysis of facial expressions, words and tone of language – Digital Machines are able to understand the state of human emotions.
We may have reached a point on the Promethean slope where the Digital Machine is ceasing to be a switchboard – it is becoming a Digital Machine persona. The Digital itself is about to be further intertwined with everyday human experience, to a point where its boundaries with perceived reality become blurred. The Digital is already a ‘natural’ environment for people connected to their smartphone 24 hours a day (Steeves, 2014). External devices with visible interfaces might eventually make place for direct connections to the brain, thus eliminating the border between the Digital and perceived reality. Elon Musk’s Neuralink project is “….centered on creating devices that can be implanted in the human brain, with the eventual purpose of helping human beings merge with software and keep pace with advancements in artificial intelligence.”
A digital persona can eventually become a proxy of its user
Once a Digital Machine has learned your habits and preferences, it could communicate on your behalf – with a friendly tone on the phone, in a business tone in emails with business partners. Digital designs and virtual realities could adapt in structure, shape and color to what individuals find most pleasing at the moment. Information could be presented with tones of voices modified to suit individual moods, study material could be presented to suit individual degrees of alertness, and entertainment could be preselected and generatively adapted for you by Digital Machines. A Digital Machine persona can eventually become a proxy of its user, engaging in complex conversations, making decisions and taking over a multitude of tasks humans find bothersome to do by themselves (Waters 2015). Deep learning processes, trained in social media territories on the expressions and behaviors of billions of individuals, might predict larger patterns of behavior indicative of political trends and opinion shifts.
The quest to reduce the distance between humans and artifacts finally led us to design machines which eliminate this distance
These developments create a double-edged sword. Already Doug Engelbart, the inventor of the computer mouse, asked if “the computer screen could be turned into a new method to enslave the user” or transformed into a means to “augment man’s intellect”.
The quest to reduce the distance between humans and artifacts finally led us to design machines which succeed in eliminating this distance. It was the operational limits of machines which made us know that they are machines in the first place. Once these operational limits, and with it the distance between human and machine, disappear, we can, by the very way our cognition works, not any more distinguish the actions of machines from the actions of fellow humans.
The final answer to the quest of human factors
The “perfect” machine, in the sense of ergonomics and human factors, would be just that: the machine perfectly adapted to humans. Solving the long quest of ergonomics and human factors, it does away with all difficulty. This brings with it troubling questions: As we get used to increasingly “perfect” machines which adapt to us, what happens to the human qualities the distance between people and artifacts motivated from the beginning: solving everyday problems, adaptation, learning, mastering skills? Once we lose our distance to the machines we created, once our machines answer our everyday questions and solve our everyday problems, we might eventually forget our own ability to independently solve problems and to freely navigate our world.
Part of this article was published as chapter 4.1 in “Analysing the Digital: Transformations, Territories, Frames and Uses” by Mario Gagliardi, Proceedings of the 12th European Academy of Design Conference, Sapienza University of Rome 2017.