﻿In most cases, "Artificial Intelligence and Life in 2030" approaches societal changes that may result 
in North American cities from the advancement of artificial intelligence with little runaway speculation and
 few outlandish assertions. However, there are several instances of speculation on the past and future effects 
of artificial intelligence on entertainment media that stick out as a departure from the survey’s usual level-headedness. 
Additionally, in the final policy proposals, the survey does not go far enough in demanding accountability for civil AI systems.


 "Artificial Intelligence and Life in 2030" makes the the following 
remark regarding the possible effects of the proliferation of digital entertainment
 on human social interaction: “The enthusiasm with which humans have responded to 
AI-driven entertainment has been surprising and led to concerns that it reduces 
interpersonal interaction among human beings” (Stone 40).  "Artificial Intelligence and Life in 2030" 
does not directly assert here that it agrees with this view’s proponents, but goes on to state: “Few predicted that
 people would spend hours on end interacting with a display” (Stone 40). This comes across as an overstatement of the
 role AI played in the initial adoption digital media. Widespread adoption of digital media existed long 
before AI techniques were meaningfully applied to digital entertainment, and AI remains restricted to limited roles.  
The question of how digital media consumption affects social interaction is not so much a question of AI’s
 specific effect, but a question of how the quality of digital media affects individuals selection between
 social and nonsocial activities. AI is only relevant in the sense that it may affect the quality and 
availability of digital media.  It has not been shown that artificially intelligent systems are capable of
 providing a meaningful and complete surrogate to human socialization. Additionally, interacting with digital systems for entertainment or leisure is often 
a social activity, and AI applied to the realm of affective computing may actually increase the fidelity with which emotional
 intent is transmitted to other individuals. This may increase the quality and availability of social experiences, 
rather than detracting from them. 


While the second policy goal, outlined in "Artificial Intelligence and Life in 2030" , provides an elegant starting 
point to ensure artificial intelligence has a positive and fair impact on society in both the public and private sectors,
 it fails to deliver an explicit standard of transparency for public sector AI. This could be rectified by extending the second policy
 goal to suggest that all intelligent systems used in governmental non-military applications are required to be open-sourced to the public.
 This could help to protect against hidden biases in applications such as classification and prediction systems that make decisions directly
affecting individuals, based on information about the individuals. Applications where transparency is critical include 
conviction, sentencing, and financial aid allocation. A open decision making system is a vital part of the 
democratic process, and remains so even when such decisions are made by non-sentient intelligent systems.


Works Cited


1. Peter Stone, Rodney Brooks, Erik Brynjolfsson, Ryan Calo, Oren Etzioni, Greg Hager, Julia Hirschberg, 
Shivaram Kalyanakrishnan, Ece Kamar, Sarit Kraus, Kevin Leyton-Brown, David Parkes, William Press, AnnaLee 
Saxenian, Julie Shah, Milind Tambe, and Astro Teller.  "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.