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With the explosive growth of the internet over the past fifteen years, few can imagine their daily lives without it. Powered by AI, the internet has established user-generated content as a viable source of information and entertainment. Social networks such as Facebook are now pervasive, and they function as personalized channels of social interaction and entertainment—sometimes to the detriment of interpersonal interaction. Apps such as WhatsApp and Snapchat enable smart-phone users to remain constantly "in touch" with peers and share sources of entertainment and information. In on-line communities such as Second Life and role-playing games such as World of Warcraft, people imagine an alternative existence in a virtual world. Specialized devices, such as Amazon's Kindle have also redefined the essentials of long-cherished pastimes. Books can now be browsed and procured with a few swipes of the finger, stored by the thousands in a pocket-sized device, and read in much the same way as a handheld paperback.
Trusted platforms now exist for sharing and browsing blogs, videos, photos, and topical discussions, in addition to a variety of other user-generated information. To operate at the scale of the internet, these platforms must rely on techniques that are being actively developed in natural language processing, information retrieval, image processing, crowdsourcing, and machine learning. Algorithms such as collaborative filtering have been developed, for example, to recommend relevant movies, songs, or articles based on the user’s demographic details and browsing history.
Traditional sources of entertainment have also embraced AI to keep pace with the times. As exemplified in the book and movie Moneyball, professional sport is now subjected to intensive quantitative analysis. Beyond aggregate performance statistics, on-field signals can be monitored using sophisticated sensors and cameras. Software has been created for composing music and recognizing soundtracks. Techniques from computer vision and NLP have been used in creating stage performances. Even the lay user can exercise his or her creativity on platforms such as WordsEye, which automatically generates 3D scenes from natural language text. AI has also come to the aid of historical research in the arts, and is used extensively in stylometry and, more recently, in the analysis of paintings.
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. Few predicted that people would spend hours on end interacting with a display. Children often appear to be genuinely happier playing at home on their devices rather than outside with their friends. AI will increasingly enable entertainment that is more interactive, personalized, and engaging. Research should be directed toward understanding how to leverage these attributes for individuals’ and society’s benefit.
 Second Life, accessed August 1, 2016, http://secondlife.com; “World of Warcraft,” Blizzard Entertainment, Inc, accessed August 1, 2016, http://us.battle.net/wow/en/.
 John S. Breese, David Heckerman, and Carl Kadie, “Empirical Analysis of Predictive Algorithms for Collaborative Filtering,” Proceedings of the 14th Conference on Uncertainty in Artificial Intelligence (July 1998), accessed August 1, 2016, http://arxiv.org/pdf/1301.7363.pdf, 43-52.
 Michael Lewis, Moneyball: The Art of Winning an Unfair Game (New York: W. W. Norton & Company, Inc., 2003): http://www.imdb.com/title/tt1210166/).
 MuseScore, accessed August 1, 2016, https://musescore.org/.
 Shazam, accessed August 1, 2016, http://www.shazam.com/.
 Annie Dorsen, accessed August 1, 2016, http://www.anniedorsen.com/.
 WordsEye, accessed August 1, 2016, https://www.wordseye.com/.
 “Stylometry,” Wikipedia, last modified August 4, 2016, accessed August 1, 2016, https://en.wikipedia.org/wiki/Stylometry; http://arxiv.org/pdf/1408.3218v1.pdf.
Cite This Report
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.
AI100 Standing Committee and Study Panel
© 2016 by Stanford University. Artificial Intelligence and Life in 2030 is made available under a Creative Commons Attribution-NoDerivatives 4.0 License (International): https://creativecommons.org/licenses/by-nd/4.0/.