CS540 Stanford Study Challenge

	While the Stanford Study on Artificial Intelligence had many reasonable estimates about the course of AI for the foreseeable future, the study vastly overestimated the overall impact AI will have on urban life. The article begins this argument by stating that autonomous transportation will soon be commonplace. Autonomous transportation and its impact on urban life will occur much later in the future than the article implies (2020). First, the article mentioned that policy and liability would be hurdles to face before autonomous vehicles are widely used. The current perception of these vehicles is not positive. Even with major improvements in autonomous vehicle safety, people are not accepting and the lawmaking process regarding autonomous vehicles is stagnant. Additionally, there will be pushback from those who drive for a career. For example, cab drivers, truck drivers, and others who depend on driving to earn a living will not be tolerant of this major change in urban life. Once autonomous vehicles eventually become popular, they still will not create a new urban organization.

	The study suggests that because of autonomous vehicles, people will have more time to work or entertain themselves during their commutes. The article argues that extra time will convince people to live further from the city. Cars will become a service, not something people own. Therefore, the reduced need for parking would change urban landscapes. Although extra time would be an appealing feature of an autonomous vehicle, it would not have a heavy influence on where people live. The time spent commuting is still time that people are not spending with family and is a comparable experience to commuting by train to work. Furthermore, the article failed to address the potential increase in traffic flow if more people decide to move away and commute inward. The landscape of the roadways would need to change before the landscape of the city itself. Instead of the roadways, the article speculated on flying vehicles, which would face their own difficulties with regulations and safety procedures.  

	From a social angle, the Stanford study made estimates about the impact of AI in low-income (inner-city) areas, specifically regarding peer influence and public safety. It claims that AI may be able to leverage homeless youth with social networks to strategically select peer leaders to spread health-related information. AI programs need data to be successful. This idea has merit; however, it does not seem practical without significant data acquired from the homeless youth. With respect to public safety, AI may be able to help by permitting police force to only be used when necessary. However, extensive measures need to be made in coding to ensure factors that could produce bias are removed completely from the code. Additionally, the idea of using AI for behavior analysis to detect criminal activity will need more refinement than the article mentioned. The general population is currently skeptical of law enforcement and would have difficulty accepting these modifications. The study addresses the publics concerns about privacy and how personal information could be used in the programs. Until these problems are sorted and the public is convinced, AI will not have significant influence on social life in urban areas. 

	Within the other main areas that the study reviewed, it had reasonable estimates about the future capabilities of AI and the timeline to reach these capabilities. The results described with relation to urban development are less likely to be achieved or will be less influential than described. Any dramatic change and shift of perspective will take significant time for people to accept, adjust, and implement. 		

