Jaime Teevan, Ph.D.
Blog, Twitter: @jteevan
One Microsoft Way
Redmond, WA 98052
(425) 421-9299
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Jaime conducts research at the intersection of human computer interaction, information retrieval, and artificial intelligence to help people to work less and do more. Recent threads include:

AI and Work Large language models and related AI systems are transforming how work gets done, creating new possibilities and challenges for workers, employers, and society. AI can augment human capabilities, automate tedious tasks, and enable new forms of collaboration and creativity. But AI also raises questions about the skills, values, and ethics of the future workforce, the impact of AI on productivity and inequality, and the design of human-AI interactions and systems. (For more, see http://aka.ms/nfw and publications: human-AI interaction)
Hybrid Work The pandemic forced a rapid shift to remote work that upended existing work practices. As people return to the office, hybrid work presents a new set of questions and challenges, such as how to choose the best location for different tasks, how to coordinate and use in-office time effectively, and how to have inclusive and productive hybrid meetings. The current moment presents an opportunity to create a new and better future of work that empowers people working across different locations. (For more, see http://aka.ms/nfw and publications: hybrid work)
Microproductivity Many of the chunks of time we have in a day are too short to use productively. We try to avoid fragmentation by changing how we work, but can also embrace it by changing our tasks to fit our existing work patterns. Large productivity tasks can now algorithmically be broken down into a series of smaller microtasks that can then be selfsourced, crowdsourced, or even completed by AI. This transforms information work into microwork, changing when and how we work, and enabling us to complete challenging tasks efficiently and easily. (For more, see publications: microproductivity, crowdsourcing, personal information management)
Slow Search People expect search engines to return results instantaneously, and judge faster results as better and more engaging. To meet the expectation for speed, search engines make many compromises to shave milliseconds off their response time. This is ironic given most of our search interactions involve multiple queries and take minutes or even hours. There is an opportunity to slow the search experience down and help searchers as they learn, gather, and explore, while using the extra time to algorithmically generate high quality, personally relevant content. (For more, see publications: slow search, personalized search, re-finding, serendipity, social search)

For more about Jaime's research, please see her complete list of publications.