The Stanford One Hundred Year Study on Artificial Intelligence postulates that AI technological advancements will be developed and fielded gradually rather than in sudden jumps. While I believe that advances will be developed gradually, I disagree that the fielding of technologies will be equally gradual in all sectors in which artificial intelligence is or will be prominent. 

Autonomous transportation is a sector in which I believe this will be the case. Human failures and biases will play a large role in this outcome. As indicated in the article and through other human interactions with AI, people are often known to trust an unearning system more than they should. This is resonated by Teslas experience with semi-autonomous transportation. Tesla was unable to prevent the first fatality involving an autonomous car even when forcing individuals to check the steering wheel at least periodically.  Google had similar issues with test drivers doing other tasks, ignoring the road, and ignoring their duty to correct the system if needed when in an autonomous car. Even in the during testing, humans trusted that the system knew what to do and how to perform the tasks correctly. Some of the blame may be rooted in recent societal acceptance of computers knowing optimal driving routes (Google Maps), which product you should buy (Amazon), what show to watch (Netflix), and even that computers can safely fly airplanes (autopilot). If AI technologies designed to aid individuals are introduced gradually, people will begin to trust the system more than they should causing high risk and suboptimal performance. To avoid this issue, self-driving capabilities will be introduced to the public, not gradually, but rather in a jump to a complete system. This will help avoid unearned and unwanted trust in co-pilot technologies.

Another area in which I believe we will see a jump in fielded technologies in the workplace, specificlly as AI technologies become more advanced. Technologies will gradually be able to perform a majority of the tasks done by an employee. However, to replace employees fully as theorized in the report, I believe we will see the jump in fielded technologies. Businesses are often known to trust technology as long as there is a human to fix any errors or to verify the results. A significant jump of improvement in AI technologies, including a reduction in price, will determine if a company will invest into AI technologies to replace human employees. This becomes even more true as the idea of a universal wage, funded by taxes on a company, become more prevalent. The cost of losing an employee to AI will become costly and AI technologies must provide significant improvements to be accepted naturally leading to a jump to a complete system rather than gradual fielding of technologies as systems advance.

As stated throughout the article, AI technology heavily depends on the sector in which it is being used  the fielding of technologies will be no different. Each sector has its own challenges for introducing AI. Responsible introduction of AI may require jumps in technologies as with self-driving cars or acceptance of technologies by firms may require jumps in capabilities. New technologies of such grand of scope across different sectors is rarely seen and challenges will be ubiquitous but variable in all sectors.

Sources.
Stone, P. et al. "Artificial Intelligence and Life in 2030." One Hundred Year Study on Artificial Intelligence: Report of the 2015-2016 Study Panel, Stanford University, Stanford, CA, September 2016. Doc: http://ai100.stanford.edu/2016-report. Accessed:  September 6, 2016.

Urmson, Chris. (2015, March). How a driverless car sees the road [video file]. Retrieved from https://www.ted.com/talks/chris_urmson_how_a_driverless_car_sees_the_road/details
