A robot can do amazing things, but could it hold down a desk job?

A colleague of mine, a roboticist, recently proclaimed that if one could teleoperate the robot he developed in his lab, it could hold down a desk job. It’s a common sentiment among roboticists that existing mechanical hardware is sufficient to replace humans in many of the tasks by which we earn a living. Rather than the hardware, the last, golden step to having human-like machine counterparts is in the development of appropriate algorithms. But this is wrong. There is in fact little evidence that robots have the mechanical features necessary to hold down a desk job, regardless of the algorithms.

Roboticists such as my colleague love algorithms. Many of them grew up playing video games where the challenge was thinking through the correct set of actions, out of a predefined set of options, corresponding to little, discrete buttons on a gamepad, in a virtual world. To beat a video game is to find the right sequence of actions.

What many roboticists don’t realise is how incredible, and incredibly complex, their own movement is in the real world – even in the most frequently encountered tasks. They tend to divide the world of movement into convenient, opposing categories:

• movement (what you do when you’re in a dance or exercise class, breathing heavily) versus stillness (what you do when you’re ‘just’ sitting, breathing lightly);
• hard, rarified tasks (a backflip) versus easy, common ones (successfully catching a ring of keys suddenly tossed by a friend);
• expressive tasks (communicating anger) versus functional tasks (walking across a room);
• strength, precision, repeatability (features on which robots have long out-performed humans) versus softness, variability, surprise (odd quirks of human movement that need to be eliminated for optimal performance).

These categories have their uses, but they also create blind spots for those looking to quantify and replicate the movement of natural systems – or predict the future impact that these machines will have on our lives.

In dance, my other professional home, the quirks of human behaviour are something to be celebrated, explored and even exploited. Dance resists and actively thwarts such easy categorisation. The idea of ‘stillness’ is not present in the Laban/Bartenieff movement system, a taxonomy that formalises a set of interrelated, overlapping features of movement, connected through dualities that make rigid categorisation of bodily action impossible. This system describes the process by which dancers and choreographers create their innovative designs of human movement through the lens of Laban movement analysis. This embodied form of qualitative analysis describes the idea of ‘active stillness’, which acknowledges the amount of motor activity involved in holding any particular posture. Under the academic lens of dance, all of the above polarities break down:

humans are never still, requiring constant breath via the motion of the diaphragm, which reverberates into every part of the body, especially the ribcage, heartbeats and postural adjustment;
while robots can achieve a backflip, they cannot catch objects in varied environments, shifting a conventional idea of what is ‘hard’ and ‘easy’;
walking across the room expresses information about the internal state of a living counterpart, therefore it is both functional and expressive; and
a human onstage next to a machine can create many more textural qualities, easily outperforming their mechanical counterparts.
So what does it take to ‘hold down a desk job’? Let’s assume the robot has a wheeled base and two robotic arms attached, operating inside the relatively controlled environment of an office building with a custom desk to accommodate the unusual, if somewhat anthropomorphic, shape of this machine. The robot will not be autonomous; it will be teleoperated by a human. As analysts breaking down choreography, let’s look at all the things that a human does – that a human moves – in order to stay employed at a seemingly ‘sedentary’ desk job. For these tasks, even if given the correct series of instructions from a human operator, extant robots would fail.

Fold precisely a large piece of paper in one try: there are factories where specialised mechanical structures fold paper autonomously every day, but they do not employ humanoid robots. My colleague’s robot would be ridiculous in such a space; it’s advantage is meant to be in multipurpose activity. But, today’s humanoids would easily fail at the kind of folding that humans do, gently navigating the crease down at the exact moment that the whole paper will bend, using haptic and visual feedback. In the images below, an elbow, the surface of a forearm and the tips of several fingers guide the unwieldy sheet in concert. Today’s robots would ruin the paper by creasing at the wrong time, or simply not be able to control the large flexible surface.