With the rise of crowdsourcing and social computing in the last decade, today, "computing" is not only about developing reliable systems or efficient algorithms. It is also about designing computational technologies that enable people to effectively interact with machines and/or other humans to solve complex problems. For example, many successful machine learning systems (e.g., the vision systems of self-driving cars) nowadays tap into the wisdom of crowd by incorporating human inputs and feedback in the loop. On the other hand, an increasing number of online platforms, like Wikipedia and StackOverflow, allow people all around the world to communicate and collaborate with each other for a wide range of purposes. This course surveys the state of the art in the research area of crowdsourcing and social computing. Topics of interests include incentives, workflow design, quality control and intelligent management in crowdsourcing, computer supported collaborative work, and applications in various domains like artificial intelligence and citizen science.

Course Logistics

Should I be interested?

This course should be of interests to you if you...

  • want to use the "crowd" to help with your computational tasks (e.g., label data) but don't know where to start.
  • want to improve the outcome of your crowdsourcing effort through better task design or intelligent crowd management.
  • want to better understand the phenomenon of collective intelligence and explore innovative crowdsourcing applications.
  • are actively/interested in doing research on human-computer interaction, artificial intelligence, machine learning, and computational social science.