Designing problems by designing solutions
The case of autonomous vehicles.
Part 1 — Deconstructing systemic biases
During his 2018 Peace Nobel Price acceptance speech, Denis Mukwege states “When you drive your electric car; when you use your smartphone or admire your jewellery, take a minute to reflect on the human cost of manufacturing these objects”. He refers to the social and political situation in Congo, and how by using a mode of consumption relying on electricity and batteries we are encouraging this situation.
While the scientific community is trying to attract attention on the imminent danger of global warming, partially caused by CO2 emission (Nasa), governments are taking actions in favour of electrical mobility. Among those policies, grants to purchase electric vehicles and investments to develop charging infrastructure network are among the most popular. However, this situation is converging toward a heavy reliance on Congo and creates its own impact on ecology and local population by draining minerals, creating its own recycling problem and relying on a dictatorship exploiting its population. This situation highlights a naked solutionism mindset in innovation. We could summarize it as following: By solving issues of today, we are creating the ones of tomorrow. However, from a business perspective, we are creating new opportunities as those issues will have to be solved one day; enter the famous negative externalities.
We are displacing issues in new contexts which we don’t know about yet. Those issues might be harder to solve and/or will ask for urgent solutionism when the threats to societies and therefore governments and businesses, will become too important. This behaviour creates a new loop of arising issues and required problem-solving; a vicious circle.
This is how I’ve introduced my third Master Thesis conducted in 2018 at Hyper Island in Manchester. I’ve researched the potential impact of autonomous vehicle’s onboard experience on its users and at large scale society. After two years of improving my English and fighting my postponer syndrome, I finally rewrote it in a way which is more compliant to publish.
This thesis started when I realised that in the case of radical innovation, we often oversee the future impact of what we design, for the sake of short term profitability. Users become passengers and the principles of human centred design disappear for the profit of optimising its process, the same way we optimised open spaces. I understood that short term business viability frames products and services by implementing its set of conditions from the very start.
In an article published in Stanford Social Innovation Review in 2018, Thomas Both sums-up the consequences of short-terminism;
But a human-centered approach has its shortcomings. You might create solutions that address the symptoms of a problem, but in turn overlook opportunities to address root causes of the problem. You could get preoccupied with solving for human needs that are not highly impactful. You might overlook downstream consequences of your creations — not only for your beneficiaries, but also for other stakeholders or society as a whole.
That behaviour gives ground for unintended consequences and in that case, as Franco Berardi calls it, The Age of Impotence. However, I wanted to turn the table, and simply ask, what if we designed for empowerement? What would that look like from a business perpective. Spoiler alert, using current tools for ideation and concept design, we were able to come with more and stronger business ideas when we decided to empower users.
Ready? Buckle up, here we go for part 1, deconstructing the innovation process to understand how it inputs biases straight up from the beginning.
Framed innovation, how the way we conduct innovation sets a frame for unintended consequences: the case of Autonomous Vehicles.
Feasibility as ignition
In the precise case of autonomous vehicles, the development process relies in the reason that we are capable of doing it. The developement of multiple technologies, from lidar to AI powered image recognition, are allowing the developement of autonomous vehicles by subsituting human inputs with digital technologies. Without those said innovations, autonomous vehicles wouldn’t be able to operate.
Viability as a driver
An autonomous vehicle is a tool. A tool for mobility. As a tool, it should be studied in its context to understand its purpose. For instance a hammer in the hand of a carpenter and in the hand of a bank robber doesn´t have the same purpose.
We are currently in a free economy that relies on the free market. The free market atmosphere drives competition as a mean for companies to stay relevant in their market. On my right, we have researchers wanting to innovate but need money. On my left, we have companies needing innovation to stay relevant and have the money to invest.
Companies invest in research as long as it meets their need to be competitive, but will expect a return on investment. The context is framing the innovation purpose and sets expectations: Needs to be profitable.
In the human-centred design terms, we are not asking the question “how to make desires feasible and viable?” but “how to drive desires to ensure the viability of what is feasible?”. That change of paradigm comes with its own biases.
Let’s make a stop at the restaurant for a minute
In his book “The productivity dilemma: roadblock to innovation in the automobile industry”, William Albernathy explains that companies are subjected to an Exploration/Exploitation dilemma.
Also called the restaurant dilemma, the Exploration/Exploitation dilemma stresses the behaviours araising from the need to make a decision between exploring new restaurants or going to the same safe bet.
The dilemma lies in possibly exploring and finding an excellent new place, but risking to stumble on the worst one, or exploiting the same restaurant, but being sure about the result. Applied to a company, this dilemma is relative to the moment a company considers the development of a product to be good enough, so the companies can stop the exploration (spend money) to start the exploitation (earn money).
As the development of autonomous vehicles is ignited by the feasibility, the exploration is concentrated on making autonomous vehicles feasible. If feasibility is igniting the research, viability is driving it. It ends up framing research question from “what do people need” to “what do people will be willing to do in autonomous vehicles to use one?”. We’re therefore making Desirability, the passenger of the innovation process.
Desirability as a passenger of the innovation process.
Crash course in prioritisation: people don’t matter. As the developement of autonomous vehicles is the result feasibility enabled by viablity requirements, desirability has few space to blossom. Added to the fact that exploration ressources have been spent on the technology, the research on desirability is victime to the urge to make a return on investment.
MVP no more, all hail to the MDP.
Spending money on activities beyond making the innovation just desirable enough to be accepted among users therefore seems unecessary. We then start to design Minimum Desirable Products. If we take a look at the forecasted onboard experiences, we’re not really producing anything new for the user; we are aiming to enable people to work, sleep and consume entertainement as key activities.
A big chunk of the time is declared to be spent still watching the road. Probably, at first. But no one looks at their phone the first time they drive, then we get confident. Eventually, we will stop watching the road. So what are we doing?
Well, we almost become 1s and 0s. Whether we produce value by working or we consume it by shopping, streaming, gaming etc. Rougly a 1/6th of the time is spent on “me time” and more or less 1/2 of the time spent on private communication. Assuming we’re not multitasking.
Here’s that data turned into a visualisation:
On one hand, we see many business models for autonomous vehicles are scribbled, from (very) short term renting to autonomous offices and stores to sponsored dine-out; On the other hand not so new behaviours for users.
As users are passengers in this whole innovation process, they don’t have much weight in choosing the destination nor the way to get there.
So why does it matter to think about it now?
Because we’re setting standards, we’re designing a system that’ll constrain us, may that be because of the physical design of the space, but also through peer pressure and finally by supporting activitites already known to harm people.
1. Behaviours will be constrained and future onboard experiences will be framed:
The physical, social or technological structure permitting or limiting certain forms of behaviours, is defined by Lawerence Lessig as Architecture. In his book Code: And Other Laws of Cyberspace (1999) Lawrence Lessig defines four stimuli to behaviours:
- The Law, norms and standard created and enforced by some recognized social authority. (It is illegal to cross the street when the streetlight is red)
- The market, which introduce a price-setting which biases behaviours
(low income households will be less likely to eat organic products as those are more expensive) - The Social Norms, which influence behaviours on the basis of social expectation and peer pressure.
(Boys in western culture should not wear nail polish for instance) - The Architecture, which is physical, social or technological structure permiting or limitating certain forms of behaviours (It´s impossible to walk on ceilings, unless equiped with technology permiting to do so)
As the architecture influence behaviours, the design of onboard experience is constraining the possibility of developing new behaviours: New ways to work, new ways to consume entertainment, and new ways to sleep.
2. The architecture gives opportunities for Social Pressure to take place:
Maybe, working while commuting would enables people to be sooner at home with their family. I think that it gives the opportunity to increase working hours. As an example with smartphone and laptops for instance, which introduced the workplace inside the home. Thus, forcing the French, German, Italian and Philipino governments to adopt laws to cope with the impact of the workplace on the personal one.
“ When companies hand out smartphones to their employees there is an implicit agreement that those staff are on call any time, any place. Once the workers are used to being connected to the office at all hours, it can be hard for them to detach and relax”
Arnold Bakker, work and organisational psychology Professor at Erasmus University in Rotterdam.
The Guardian 2014
3. The forecasted experiences are already known as harming society
Admiting that the user won’t work. The second most popular experience is to consume entertainement. The dangers for people and therefore society of those forecasted experience are already known: consuming entertainment as a “back up” for me time, is also known as enabling problems like hazards to health and rise of loneliness. The consumption of entertainement is known as disabling cognitive behaviours, while the architectural limitation of driving pushes people to be bored and drives cognitive behaviours.
That was part 1, understanding how the innovation process inputs its own biases and frames innovation, reducing the area of possible futures. As said in the intro, I’ll explore how we can challenge the current status and design a different approach to innovation to produce virtuous circles of innovation.
That approach is what I’ll be addressing in Part 2, eventually.
Since you’re still here, to write this thesis in 2018 I’ve got support from few people I would like to mention because they are amazing:
Rita Cervetto
Paola Craveiro
Nick de Jong
Robert Potts
Lauren Purkhiser
Mike Ryan
Paul Wagner
& the teams at diffferent Berlin & Hyper Island UK
