Paper Reading #27- Sensing cognitive multitasking for a brain-based adaptive user interface

Title: Sensing cognitive multitasking for a brain-based adaptive user interface
Reference Information:
Erin Solovey, Francine Lalooses, Krysta Chauncey, Douglas Weaver, Margarita Parasi, Matthias Scheutz, Angelo Sassaroli, Sergio Fantini, Paul Schermerhorn, Audrey Girouard, and Robert Jacob, " Sensing cognitive multitasking for a brain-based adaptive user interface". CHI '11 Proceedings of the 2011 annual conference on Human factors in computing systems. ACM New York, NY, USA. ©2011. ISBN: 978-1-4503-0228-9.
Author Bios:
Erin, Francine, Krysta, Douglas, Margarita, Matthias, Angelo, Sergio, and Robert are all associated with Tufts University in Massachusetts, USA.
Paul is associated with Indiana University.
Audrey is associated with Queen's University in Ontario, Canada.
Summary:

• Hypothesis: If the authors can create a system to detect a user's "to-do list" and allow them to multitask on different things at once, then those tasks will be completed faster, the user will become "understood" by the system, and a new kind of technology will be effectively used.
• Methods: While constructing their functional near-infrared spectroscopy (fNIRS), the authors took into account the three multitasking scenarios of the brain: branching, dual task, and delay. Branching is when you hold in mind goals while exploring and processing secondary goals. For example, you are working on your homework when a friend e-mails you and you begin to read the e-mail (while still remembering to return to your homework after you finish). Dual Task is when you have two tasks that require additional resources to complete. For example, a network technicial is fixing issues with his company's network while responding to important e-mails (possibly answering questions about the network). Finally, Delay is when a primary task is being worked on and a secondary task gets ignored. For example, you are watching a movie on your laptop when you see a notice come up that you have an e-mail. You ignore this notice. This is called delay because the secondary task gets delayed by the primary task. The authors were curious to see if they could tell the difference, cognitively, between the three kinds of multitasking. So they strapped some volunteers with gear and tested to see if they could while users performed given tasks (obviously multitasking was involved). After the preliminary study, the authors conducted a second study with the same methodologies in different spaces more relevant to HCI (for example, users were required to sort rocks by their type from Mars while keeping track of the position of a robot). The authors also launched a third study involving random vs predictive branching (the robot would move randomly in terms of the number of rock types were displayed vs the robot would move after every three presentations of rock types).
• Results: The preliminary study returned a recognition accuracy of 68%. To the authors, this was promising. In the second study with the robot and the rocks, any result where the participant achieved less than a score of 70% were discarded because it was seen as the task being done incorrectly. In the last study, there was no significant statistical difference found between the random and predictive branching. The authors were able to construct a proof-of-concept model because they were able to differentiate between the three types of tasking and incorporate machine learning into it.
• Content: The authors wanted to be able to create a system to measure and handle multitasking mechanisms. They were able to differentiate between three types of multitasking, create studies to measure efficiency for each kind of multitasking technique, test their system, and prove that it works as well.

Discussion:
I think these guys are geniuses. The technology is super advanced and the methodologies were complex when dealing with the proof-of-concept system. I don't know how much effect this will have in the HCI field (at least that I can see) because it didn't seem to me from reading this that there was much of a "new invention" or "new technology" here. They were able to recognize and "quantify" multitasking, but aside from that, I'm not sure how this could be applied. Maybe I missed it. I think the authors definitely achieved their goals, though. They said that all they wanted to do was be able to handle cognitive multitasking, which they were able to do. I'm indifferent about this article, honestly.