In my last post, I listed the five key components of a mobile virtual assistant, as outlined in the VisionMobile report Beyond Siri: The Next Frontier in User Interfaces . I wrote about Speech Recognition and Natural Language Processing. The next component of intelligent virtual assistants that I’d like to explore is User Profiling. User Profiling entails learning as much information about a user’s preferences, environment, and general context of usage as possible. The virtual agent then leverages this information to shape how it responds to the user and to his or her requests. Another term that is often used to describe similar behavior is personalization.
One example of user profiling, or personalization, that readily comes to mind are the product recommendations that online retailers offer frequent shoppers. The retailers track your previous purchases and gradually learn about your preferences. If you’re a regular purchaser of mystery novels, the recommendation engine is likely to alert you to the hottest mystery titles the next time you visit the site. This is certainly a more valuable service to you than if the site were to repeatedly annoy you with offers for romance novels, ignoring the fact that you’ve never bought a romance title.
Virtual assistants of the future will most likely use similar information gathering strategies in order to improve the services they offer. Your personal mobile assistant might take note of the route you take to work everyday to alert you of a traffic problem. A truely helpful virtual assistant may be able to order food or medicine automatically based on your preferences and usage. Customer facing virtual agents will most likely try to determine a user’s location, past buying habits, and other demographic information in order to appropriately tailor their responses and recommendations.
In a recent white paper called Digital Personal Assistant for the Enterprise, IT@Intel describes a current in-house Intel project to develop an intelligent virtual agent that can assist Intel workers in more effectively accomplishing work-related tasks. Over time, the digital assistant will be designed to support various usage models, including acting as an executive admin and a collaborative assistant. The first release of the Intel enterprise virtual assistant takes into consideration the user’s location to offer a visual map with walking directions when the user is searching for a meeting room in an unfamiliar building. Future iterations of the digital agent will integrate more user profile information to provide a higher level of service. For example, the virtual agent is supposed to become so knowledgeable of its user’s behavior and moods that it will be able to automatically detect when the employee has entered “deep problem-solving mode” and then restrict all non-critical disturbances.
User profiling on the part of future virtual digital agents may give us concerns about loss of privacy, but the potential benefits appear to be huge.