In his book, Kevin Kelly discusses a term known as the “precautionary principle”. Essentially what this term means is that “a technology must be shown to do no harm before it is embraced.” In other words “the first response to a new idea should be inaction until its safety established.” (KK.org) Obviously it is human nature for us to want our products and technologies to be safe and sound. This is why there are laboratory tests for new chemical products or safety tests for the newest vehicle, etc. However, it’s not always possible to ensure the safety of something before it is put into the public domain or market. Such is the case of driverless, or self-driving, cars.
Google believes they are solving a problem by creating a driverless car. According to Google, if driverless cars became standard “deaths from traffic accidents–over 1.2 million worldwide every year–could be reduced dramatically, especially since 94 percent of accidents in the U.S. involve human error.” (Google.com) These statistics sound well and good, but how do we know that these self-driving cars are completely safe? Google explains how its’ cars work; “they have sensors designed to detect objects as far as two football fields away in all directions, including pedestrians, cyclists and vehicles—or even fluttering plastic shopping bags and rogue birds. The software processes all the information to help the car safely navigate the road without getting tired or distracted.” (Google.com) As of May 2015, Google claims that its’ driverless cars have been involved in just 11 “minor” accidents throughout the six years they have been on the road. Chris Urmson, the head of Google’s self-driving car program, says that the accidents caused no injuries and only “light damage.” He also claims that the Google self-driving cars were not the cause of any of the accidents. (WSJ.com)
So how can we manage both the precautionary principle and technological expansion at the same time? It seems as though the two ideas are at odds with one another. On one hand we want all our products and technology to be completely safe, but on the other hand we do not want to hinder or slow down technological growth. The self-driving cars are a perfect example of what happens when the unknown safety comes up against a rapid spread of technology.
Some technological advances have the benefit of being delayed or re-designed while safety standards are measured. Unfortunately there is an epidemic in this country that has been touched on throughout multiple blogs, and that is texting and driving. According to the Department of Transportation, cell phones are involved in 1.6 million automobile accidents annually, leading to the death of upwards of 6,000 Americans. (InvestorPlace.com) 
The implementation of a self-driving car isn’t a technology that has the luxury of being delayed while we test it for safety. Google has had these cars on the road for over five years and they have a proven track record, but we do not have measurable safety data.
What’s more important: implementing technology quickly to solve a problem or delaying technology while thorough research is conducted?
References
Google Says Driverless Cars Involved in 11 ‘Minor’ Accidents in 6 Years. (n.d.). Retrieved October 14, 2015, from http://blogs.wsj.com/digits/2015/05/11/google-says-driverless-cars-involved-in-11-minor-accidents-in-6-years/
Google Self-Driving Car Project. (n.d.). Retrieved October 14, 2015, from https://www.google.com/selfdrivingcar/
Texting and Driving Statistics 2014 | InvestorPlace. (2014, June 12). Retrieved October 14, 2015, from http://investorplace.com/2014/06/texting-driving-statistics-2014/#.Vh6dxPlViko
The Technium: The Pro-Actionary Principle. (n.d.). Retrieved October 14, 2015, from http://kk.org/thetechnium/the-pro-actiona/
Technology of Communication 
I think the self-driving car is a great example for what Kelly talks about. We want our technology to continuing growing and expanding, however, we also want to make sure that the growth is safe and won’t cause any severe problems for us. I’m not sure that there’s really any true way to determine whether or not a self-driving car would be safe without putting it into some kind of use. You can only test something so many times in a constrained environment before that isn’t enough anymore. This technology has to be put out into the real world so it can be properly tested in the environment it would actually be operating in. However, you have to be prepared for it to not work 100% right away. I liked how the head of the division was quick to say that it was never the self-driving car’s fault when there was an accident, but there’s no way to be certain about that. Sure, humans are more likely to cause errors, but with something this new, the technology is still being developed and would still have bugs that need to be worked out. I’m interested to see how this car will develop and how long it will be before they’re for sale to the public. I know one thing for sure: I won’t be able to afford one when they come out!
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As Kelly (2010) (https://drive.google.com/file/d/…/view?usp=sharing) noted as we incorporate technology into our lives, it is going to pose issues that were once thought of as impossible or unimaginable. What might work well in tests (no matter how many they do) may not always work well in reality. This is true for three reasons: 1. differing road conditions, 2. the unpredictability of human drivers and 3. how the adoption is integrated by the users. Surely, when the cellular telephone was conceived, no one would be able to predict how it is being used today due to its capability to collapse multiple layers of interactions/experiences (texting, email, apps and games) (Park & Sundar, 2015) (http://www.researchgate.net/publication/269777490_Can_synchronicity_and_visual_modality_enhance_social_presence_in_mobile_messaging) and the subsequent distractions it can cause while driving.
In theory, self-driving cars could be very beneficial to someone like me, who is physically disabled and did not passed my adapted driving evaluation, but technology grows in all the ares Kelly(2010) (https://drive.google.com/file/d/…/view?usp=sharing) described, it will eventually outpace human understanding because the technium grows and adapts at a more rapid rate than our biological evolution. This would mean that we would encounter problems that we do not understand how to fix and it would be up to machine’s artificial intelligence to figure out. Machines, as it would seem can and will develop rational thought, will have an advantage over humanity, in the fact that they control our infrastructure and our way of life, and we will be at their mercy.
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