bRight: Taking human-machine interaction to the next level

“Learning and improving and continuous adaptation to a user’s needs will be central to bRight.”

As I sit here tapping away at my keyboard, I’m flanked by a computer screen showing news feeds from the world of technology, another frantically tumbling away with Twitter updates, and another still that’s telling me that yet another email has landed in my inbox. While I sometimes feel like I’m drowning in data, my woes are as nothing to those experienced by air traffic controllers, network administrators, operators in emergency response control rooms, and even busy stock traders. bRight from SRI International – the Californian research institute which originally developed the Siri virtual assistant – has been designed to make life a little easier for folks who need to make snap decisions in time critical situations, but are faced with an overwhelming amount of information flowing in all at once. In addition to offering task automation and data filtering, the system can predict the actions, behavior and needs of a user or group based on previous activity.

In 2007, Silicon Valley’s SRI International formed Siri Inc. to commercialize a virtual personal assistant technology born out of the institute’s DARPA-funded CALO (Cognitive Assistant that Learns and Organizes) artificial intelligence project. A free app for the iOS platform was subsequently launched as a public beta in early February 2010, and just a couple of months later, Apple acquired the company. Spin forward to October 2011, and a conversational search assistant called Siri was launched as a new feature for the iPhone 4S.

A little while later, Google premiered its own digital PA in Android 4.1 (Jelly Bean). In addition to providing Siri-like search and assistance using natural language, Google Now delivered information and suggestions based on actions or decisions that the user had previously taken. SRI’s latest project, bRight, progresses beyond both systems as an answer to what’s been dubbed cognitive overload, where the tidal wave of information that can flood in during emergency situations can prove to be just too much to deal with effectively and, perhaps more importantly, rapidly.

The research prototype uses face recognition (though more secure biometrics, such as iris scans, will likely be implemented in the future) and gaze monitoring systems, along with proximity, gesture and touch sensors, to build detailed user profiles. In a similar way that modern computers might make valuable performance gains by effectively taking a shortcut when certain conditions are met, bRight’s powerful AI software uses this information to anticipate what might be needed so that only data that’s relevant to the job in hand is presented to the user, necessary tools can be literally placed at a user’s fingertips, and repetitive tasks can be fully or partly automated.

For example, at a fairly simple level, if a user highlights a word in a document, the system can guess which menu items might be needed next and present the user with likely choices. Or if someone’s writing a specific kind of email, such as a staff newsletter or performance bulletin, bRight may be able to determine its recipients based on previous activity, and pre-populate the Send To field. It might also detect potential errors or breaches of standard protocol.

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