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?
Watch How Do Websites Personalize Recommendations for Me? – Exploring Ethics
We have all heard the dire warnings. Artificial intelligence is predicted to decimate job sectors already hit hard by outsourcing. Some studies suggest up to half of all work could be automated by 2030. That means factory workers, drivers, even some accountants may find themselves without a job.
Jennifer Granholm, the former governor of Michigan, knows the pain of job-loss all too well. She witnessed the closing of factories in towns like Greenville, where three thousand of the town’s eight thousand residents worked at the same plant. But, Granholm remains optimistic about the future of employment in the United States. She believes we can make artificial intelligence work for us, not against us.
Granholm uses the autonomous vehicle as one example. While the technology could put five million drivers out of work, it could also create millions of new jobs. We could see the rise of new industries such as mobile motels, or pop-up shops. Driverless cars could eliminate the need for massive parking lots, creating space for affordable housing. But, new industries require a workforce with new skills.
Granholm has five suggestions for creating that workforce. Three of those suggestions focus on investment in training, including apprenticeships and internships. She suggests diverting funds currently used to subsidize unemployment. She also says we need to come up with a way to create portable benefits for people with alternative jobs, such as Uber drivers and other app-based workers. The final suggestion: pay people for their data. Granholm says the tech sector is making billions off our personal information, and there may be a way to share that wealth.
Watch Shaping a 21st Century Workforce – Is AI Friend or Foe?
With the vast amount of data available in digital form, the field of Artificial Intelligence (AI) is evolving rapidly.
If you’ve even been caught on a phone tree with a computer that doesn’t understand what you are saying, you’ll appreciate that scientists are trying to figure out how to teach machines to understand, to communicate and even be empathetic.
William Wang, Director of the Natural Language Processing Group at UCSB, summarizes the stunning achievements of Artificial Intelligence for the past decade and talks about the intersection of AI and language. He’s trying to build an empathetic conversational agent that can understand and generate human sentences with rich emotions.
Wang also looks at the challenges facing AI in the future and the work ahead of these researchers as they strive to keep improving AI and making it better for everyone.
William Wang is the Director of UCSB’s Natural Language Processing Group, and an Assistant Professor in the Department of Computer Science at UCSB. He received his PhD from School of Computer Science, Carnegie Mellon University. He has broad interests in Artificial Intelligence, Machine Learning, and Natural Language Processing. He is the recipient of a DARPA Young Faculty Award, an IBM Faculty Award, a Facebook Research Award, and an Adobe Research Award. He is an alumnus of Columbia University, and he also worked at Yahoo! Labs, Microsoft Research Redmond, and University of Southern California. His work and opinions appear at major tech media outlets such as Wired, VICE, Fast Company, The Next Web, and Mental Floss.
Watch Artificial Intelligence: What’s Next?