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When you live in Mountain View, Google's self-driving cars are a common view. The white Lexus SUVs with ever changing sensors sticking out on both sides and a LIDAR-system - either a rotating "pot" or most recently a glass-covered half-dome - on the roof, keep roaming the city to gather experience in different traffic situations.
I effectively stopped taking and posting pictures of videos of my encounters with the cars, as my Facebook friends let me know that it started annoying them. Which of course contributes to the overall traffic safety, as this is one of the most common - and dangerous - things that drivers of other cars do: getting out their phones and snapping pictures while driving.
But I am getting distracted. The questions is: is Google really going to build and sell self-driving cars, and if yes, why?
To answer this question, let me go back to the time when Google launched Google Maps. When I first saw Google Maps, I couldn't wrap my mind around why Google would do a mapping service. After all, Google's mission was to collect and make information accessible. What does a map service have to do with this?
The answer came after I saw the first use of the Google Map API. A real estate company had put markers on Google Maps listing their open houses. And that made it so obvious. Google just had made the step from virtual world information to real world information.
As a search engine, Google's bots had crawled websites to collect information and bring it back to Google's servers. With Google Maps the virtual information could be merged with real world information. Location information such as addresses of restaurants, schools, parks and many other things popped up on maps. And then Google Street View enhance the offering. Cars, bikes, bag packs, and even diving sets equipped with cameras roamed the streets and planet to collect images of the real world. Even more information was put on the maps and mashed with other information.
The Stanford Prison Experiment is one of the most infamous research experiments that has ever been done in peace time. Stanford professor Philip “Phil" Zimbardo assigned students to be guards and prisoners in a fictitious jail. What you may already know is how the relationship between students serving in the roles of prison guards and prisoners deteriorated within a few days into the experiment to such a degree, that Phil had to stop it. The students role-playing the guards had started to display authoritarian behaviors towards the students role-playing the prisoners and after a few days several students had nervous breakdowns.
What may be unknown to you is that the two dozen students were selected from over 70 applicants. They mostly were from wealthier backgrounds, well educated, and displayed anti–authoritarian behaviors. Don’t forget that this was the middle of the hippie and peace-movement and those students were part of it.
Given that it is even more astonishing how the students had developed attitudes and behaviors that dehumanized the situation for the “prisoners” within a few days. By giving power and insignia of power such as uniforms and titles to the guards, the researchers were forced to prematurely stop the experiment.
In real life we easily blame one side or the other for being bad, evil or sadistic. But that’s a too easy way out. In fact, not that the students aimed at turning into evil creatures, it was the framework that nudged them to display behaviors and attitudes that led to the downhills development of the situation.
Innovation and Attitude
When we consider innovation and why it is so hard for many companies, we can take some cues from this experiment. Behaviors are a result of how the framework was set up. Selecting the wrong titles, roles, or guidelines dooms an innovative environment in your organization. Let me give you an example from Brazil:
The SAP HCP Gamification Service will be publicly available at SAPPHIRE (May 2015). You will then be able to try out the new gamification platform as service in your SAP HANA Cloud Platform Trial account. The service comes with a web-based gamification workbench for modelling game mechanics and arbitrary complex rules. The underlying gamification engine is designed for real-time processing of sophisticated gamification concepts, e.g. involving time constraints and cooperation.
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