This is the second paper of mine that was accepted to LIMITS 2020
My previous blog post was about a paper of ours that has been accepted to the upcoming Sixth Workshop on Computing within Limits. As it is, I submitted a second paper that has also been accepted, "Skill rebound: On an unintended effect of digitalization". The paper was written together with Vlad Coroamă from ETH Zürich (he is the first author).
This paper has an interesting history that started with me listening to Vlad's presentation of his paper "Digital Rebound – Why Digitalization Will Not Redeem Us Our Environmental Sins" at the 2019 ICT4S conference. That paper is written by Vlad Coroamă together with Friedemann Mattern and is available as a pdf here).
Vlad's presentation set of discussions between us at the conference and we almost immediately felt we were on to something and started to discuss the possibility of possibly writing a paper together (based on ideas we had bounced between us in these discussions). Looking at the history of the shared Google documents we have worked with, I can see we started to take notes already then and there (at the conference) and that we had a follow-up meeting at the end of Augusti. Then there was a hiatus for half a year when nothing much happened and we only stated to work on the paper in earnest in February.
This paper could easily have been aimed for and submitted to this year's ICT4S conference, but we were both busy at the start of the year and did not have any chance of meeting the early February deadline, so we instead aimed it for Computing within Limits.
The paper's backstory is that we had the idea that while self-driving cars/autonomous vehicles (AVs) will make each trip more energy-efficient, AVs will surely also lead to more trips being made. If driving becomes safer, easier, more convenient and less expensive, it's hard to imagine that the demand for (autonomous) car trips will not increase. It's in fact quite probable rather than just, say, "possible". The specific insight we had was that driving an ordinary (non-autonomous) car is limited to those who have a drivers' license, but with AVs, "anyone" can drive (or "drive"). A task that previously required training and a specific skills set will now be open to anyone (including children, pets and inanimate objects such as, say, a violin). If we think about this in terms of "rebound effects", this is a type of rebound effect that we haven't seen anyone else talk about before.
There are different kinds of rebound effects (we go through some of them in our paper), for example "time rebound". We suggest that we describe a different type of rebound effect and have chosen to call this "skill rebound". In this case the "skill bar" that is required to perform an action is lowered and this leads to more of that activity. If the activity in questions (e.g. driving a car) is detrimental to the environment then skill rebound will have "unintended" (but not necessarily unpredictable) environmental effects. For more on this, do read the paper or just start by reading the abstract:
Efficiency gains in economic processes often do not deliver the projected overall savings. Irrespective of whether the increase in efficiency saves energy, resources, time or transaction costs, there are various mechanisms that spur additional consumption as a consequence. These mechanisms are generically called rebound effects, and they are problematic from a sustainability perspective as they decrease or outweigh the environmental benefits of efficiency gains. Since one of the overarching purposes of digitalization is to increase efficiency, rebound effects are bound to occur frequently in its wake. Rebound effects of digitalization have been ignored until recently, but they have been increasingly studied lately. One particular mechanism of digital rebound, however, has been largely disregarded so far: the digitalization-induced lowered skill requirements needed to perform a specific activity. As with other types of rebound effects, this leads to an increase in the activity in question. In this paper, we propose the term skill rebound to denote this mechanism. We use the example of self-driving cars to show how digitalization can lower the skill bar for operating a vehicle, and how this opens ‘driving’ a car to entirely new socio-demographic categories such as elderly, children or even pets, leading to increased use of the (transportation) service in question and thus to rebound effects. We finally argue that skill rebound must be better understood and taken into account in the design of new technologies.