The first self-driving cars began to appear in the 1980s, so why aren’t we all riding in them by now?
Myplanet conducted a survey to determine consumers’ comfort levels and readiness for different AI and automation technologies that ranged from home appliance robots, virtual reality (VR) headsets and exoskeletons to restaurant automation and self-driving vehicles.
SEE: Special feature: Autonomous vehicles and the enterprise (free PDF) (TechRepublic)
“There was definitely a correlation between automation and the degree of control that was involved, and in how much people were willing to give up control in order to adopt the technology,” said Jason Cottrell, Myplanet’s CEO. “When we interviewed individuals about robotics that were more task oriented, such as automated packaging and food delivery, they were much more comfortable; but when it came to self-driving vehicles, elements like the amount of control that you had, safety, trust, ownership, individual identity and complexity of task came into play.”
Cottrell noted that some of the reluctance to embrace self-driving cars was age-related.
“For 75% of individuals whom we surveyed who were over the age of 65, car ownership, personal identity and the ability to drive your own car were highly important,” he said. “But for individuals in the18 to 34 age group who were used to rideshare solutions like Uber and who didn’t necessarily care as much about car ownership, we found much more acceptance for self-driving cars.”
For self-driving vehicles, as well as for other types of AI, robotics and Internet of Things (IoT), the challenges for the technology companies producing these solutions is adoption. How do you get consumers or companies to adopt (and pay for) the products you create?
SEE: Self-driving cars will create 30,000 engineering jobs that the US can’t fill (TechRepublic)
AI is an excellent example. It has been around since the 1950s—but it is only over the past few years that AI has begun to be accepted and adopted by consumers and by companies.
What spirited AI adoption was the introduction of first tier analytics that still used standard data reporting technologies, but that were successful in getting users’ feet wet with new data query approaches that generated ready paths into automation and AI. Users, whether they were companies or individuals, began to develop confidence in their ability to use elementary AI, and they began to get significant results from their AI use.
This same hill of technology understanding, elementary, mastery, confidence, and use must be climbed by self-driving vehicles.
“There are really three different scenarios that self-driving vehicle manufacturers can take toward adoption and product sales,” Cottrell said. “The first is product promotion to consumers and commercial vehicle fleets. The second is to build out self-driving vehicles for rideshare operations. Then, there is a third approach: You can introduce autonomous vehicle technology by breaking out piece parts that users find value in.”
SEE: 1 in 10 vehicles will be autonomous by 2030 (TechRepublic)
Self-driving car manufacturers have used all three approaches, but it seems that the one that has gained the most market traction and adoption is the piece-part approach. This approach is in use today. We use cruise control to take over the job of vehicle speed regulation, we use GPS to navigate us from place to place, we issue voice commands that the vehicle acts on, and even allow cars to park themselves and tell us when we’ve drifted out of a lane.
All are elements of self-driving cars that are being adopted and used for benefit by users, and they present a general lesson for anyone trying to sell or promote automation and IoT: You have to find ways to facilitate understanding, adoption, and use if you’re going to create product uptake, even if you must do it piece by piece.
“Companies in the autonomous vehicle space recognize this,” Cottrell said, “Because widespread acceptance of autonomous vehicles is not something you can achieve in a one- or two-year window.”