We use recommender system all the time. A website will recommend something to you based on what you’ve watched, listened to, bought or who you’ve friended on Facebook. These systems attempt to predict your preferences based on past interactions.
The systems range from simple statistical approaches like Amazon’s people who bought X also bought Y links, to complex Artificial Intelligence-based approaches that drive feed ranking on sites like Facebook.
Julian McAuley, UC San Diego Computer Science and Engineering, explores the modeling techniques behind personalized recommendation technology on the web and the different systems that we encounter.
He reminds us that we often find these recommendations a bit “creepy,” but that actually the recommender system has no human intelligence; it’s really a simple statistical process. They focus on short-term predictions but could they be adapted to make long-term predictions or estimate more subjective qualities? Would that be bad?
Advertisers are always looking to better understand consumers’ preferences and decision making. The application of neuroscience knowledge and techniques to answer market and media research questions is not new but in our digital age, the practice raises new questions about privacy, informed consent, and consumer autonomy in decision making. Dr. Carl Marci, Chief Neuroscientist at Nielsen explores the ethical concerns that arise and explains some of the tools used by advertisers in this growing field.
Timothy Taylor’s “Sounds of Capitalism” might not espouse the same sentiments as Simon and Garfunkel’s “Sounds of Silence,” but they’re interesting nonetheless.
In his new book, Taylor, a professor of ethnomusicology and musicology at UCLA, tracks the use of music in American advertising for nearly a century, from variety shows to the rise of the jingle, the postwar rise in consumerism and the more complete fusion of popular music and consumption in the 1980s and after. It’s fascinating stuff, especially as we find ourselves in such a turbulent and exciting time of media shape-shifting.