Debugging the language of driverless cars
What can the great behavioural economist Daniel Kahneman teach us about the future of driverless cars?
Right now, gigantic bets are being made on this sector to accelerate technical development. GM paid ‘$581m’ for the 3-year old start-up Cruise. And Ford has put more than $1bn into Argo AI. Both of which are not much, compared to Intel’s spending $15bn on Mobileye.
But a reading of Daniel Kahneman’s work points us to a non-technical issue that will soon need fixing: the human mind.
In particular, our inclination for loss aversion.
In simple terms, people tend to think more about losing $100 than they do about gaining $100.
This means that for any brand owner offering a driverless car, they first need to work out how to overcome the purchaser’s aversion to surrendering control of their car before they can start talking about the potential gains.
Evidence? Tesla’s driving system is already statistically much safer than human driving but 67% of US consumers are still afraid to ride in a self-driving car.
How can brand owners change consumers’ attitudes to this technology? As always, the skilful use of language provides a flexible and fast route to overcoming the perceived risk.
First, use language to make new technology feel familiar.
If you want to see someone doing this well, look at Elon Musk. While other car brands regularly refer to ‘driverless’ cars, Tesla call their software ‘Autopilot’.
This one-word switcheroo is a smart – and valuable – move by Tesla. After all, we already know that having autopilot on an 8-hour flight across the Atlantic is a good idea: it keeps the pilot fresh for the tricky bits, like take-off and landing. So, Autopilot on an 8-hour drive also sounds like a good idea.
Next, focus the conversation on the experiences that the consumers can literally see.
Kahneman explained that people make a summary of an experience, or another person, based on what they can most readily see. (He called it, ‘what you see is all there is’.)
According to a 2015 report from the WEF and BCG, when people are introduced to cars with assisted-driving technology they can see two major benefits: not having to park, and being able to multitask while driving.
The challenge for brand owners will be to create a conversation strategy which focuses on these areas of observable benefits.
Finally, make the message consistent from start to finish.
Traditionally, car makers aren’t car retailers: the forecourt is owned by local entrepreneurs. And they tend to do what they want.
Smart Tesla changed that structure and the message in their well-located stores is the same as on their website. The challenge for car brands with an established distribution network will be to work with their retailers to create a clear message and a consistent hierarchy of messages.
These lessons here aren’t just for car manufacturers. They’re for anyone investing money or thinking in innovation. Which is all of us.
It’s through language that we construct our sense of the world and the things in it.
Language has the power to make the unfamiliar familiar and to reveal something new in what we see every day.
Language forms the boundaries of a product’s category and it gives us a sense of where the category’s centre of gravity lies. (After all, a penguin isn’t a ‘real’ bird, is it?)
If you want to hear more about how language can launch a new product, relaunch a familiar product into a different category, or break open the category your product already sits in, please email me.
Recently, we helped an adtech company reposition itself, we’ve helped a fintech start-up define themselves, and we’ve helped a biotech B2B business clarify how they talk about their brand, along with simple tone of voice guidelines.