Google Apps are being deployed in thousands of organizations around the world, including schools and universities. We are examining the adoption and use of these cloud-based services on four campuses of the University of California system. We are interested to learn how Google Apps may go beyond simply replacing existing IT services to being integrated into the classroom curricula and the research activities of these learning environments.

We are interested in analyzing how people write together.  Google Docs allows us to look at the Revision History, at who did what and at what time.  By visualizing this history, we can detect patterns of writing.  We have a tool, called DocuViz, that shows the authorship (in color) and placement and size of the contribution in each stored revision “slice.”  The second tool is called NoVox, which analyzes collaboratively written documents for abrupt changes in style.  Together the tools are not only helpful for researchers, but can help authors reflect on their own writing strategies and styles.

We have been studying a variety of collaboratories, first in science and then in other fields of academia. Our book, Science on the Internet (2008) compiled 20 years of work studying both the kinds of collaboratories there are, the factors that must be in place for them to be successful, and the special challenges each type of collaboratory faces.   We have identified over 400 Collaboratories (distributed teams) in the Sciences and Humanities and complied descriptions and basic facts about each, a public resources called the Science of Collaboratories (SOC) database.

While people have talked about collective intelligence for decades, new communication technologies—especially the Internet—now allow huge numbers of people all over the planet to work together in new ways. The successes of systems like Google and Wikipedia suggest that the time is now ripe for many more such systems, and the goal of the MIT Center for Collective Intelligence is to understand how to take advantage of these possibilities. The basic research question is: How can people and computers be connected so that—collectively—they act more intelligently than any person, group, or computer has ever done before?  It is now possible to harness the collective intelligence of thousands of people all over the world at a scale and with a degree of collaboration that was never possible before,” Malone said. “We decided to basically crowd-source the problem of what to do about global climate change.”

Google Glass gives us an opportunity to present information to people personally in the moment without having to get out cell phones.  They also can record people’s behavior in a variety of ways, including what they are looking at and what they are saying.  We are experimenting with Google Glass in two ways:  We are following UCI Medical students who are using Glass in their training of how to interact with patients, and we are doing a microanalysis of whether someone can do their primary task and pay attention to feedback from Glass.

Given the success of startups in Silicon Valley, many people have developed “Seed Accelerators” to help startups succeed.  The Seed Accelerators bring together promising startups, give them training (e.g. developing “the pitch,” critiquing each others designs, advising on marketing and sustaining the product or service).  More recently, we’ve seen these Seed Accelerators emerge in other countries like China, Korea, Argentina, and Europe.  The leaders of the Accelerators are modeling the activities after the ones they thought most successful in Silicon Valley.  But, we are finding that there are wide cultural differences, both in who participates in the startups and what they need to be trained in and how to do the training.

In the United States and abroad, ordinary internet users are increasingly aware that their personal communications are monitored in the interest of U.S. national security.  A secondary effect of having so much surveillance is that reporters, who need to serve as watchdogs for government misconduct, have a hard time protecting their sources.  This research investigates how reporters are taking extra measures to protect the people who reveal the ways in which government is abusing its power.

At points in some collaboratively written documents like policy statements or regulations it is important to know who wrote what.  Knowing who wrote a section will tell you who to talk to if you want to make a particular change.  We have developed an Chrome extension called AuthorViz that shows the entire document, color coded by who wrote what.  It is constructed from the stream of data that makes up the revision history.  It is available in the Chrome Store. 

Some early drafts of collaboratively written documents have points where the style changes abruptly.  Editors can catch these and suggest ways to make the document have a single voice.  We are building an expert system that detects these abrupt changes automatically.  We call this system “Novox” meaning new voice.  We will seek to both detect these and suggest ways in which to change parts to have a single voice or style.

Children with various medical conditions cannot go to school, but now can “go to school” on a telepresence robot.   These robots project the child’s face on a remote system whose position and movement the child can control.  These robots have been used in work settings for remote workers, and in medical settings for bringing specialists into a medical consultation.  But school is a very different environment, where children are not only attending class, but then walking the halls, participating in lunch and even going to the gym.  It provides them not only the schooling but also the connectivity with their friends.