Lawrence Flynn, the CEO of Artificial Solutions, recently wrote a guest post for Forbes online. In the post, Flynn focuses on various types of personalization and how this topic relates to intelligent virtual assistants. Artificial Solutions is a prominent player in the enterprise virtual assistant / virtual agent marketplace. I wrote briefly about their Teneo Network last spring.
In his blog post, Flynn spends some time drawing a distinction between what he terms “implicit personalization” versus “explicit personalization.” Flynn defines implicit personalization as the type of understanding that a virtual assistant develops as it interacts with you. For example, if you instruct the assistant to send a text to your brother Joe, it can easily deduce that your brother’s name is Joe. If you frequently have your assistant make a calendar hit for you to meet Joe for Mexican food in the evening, the assistant knows that you interact with your brother a lot and you both enjoy Mexican food. There is obviously a whole range of implicit information that an observant intelligent assistant can catalog about you.
Explicit personalization is not information that’s inferred through conversation or other means. Instead, it’s the knowledge that an intelligent assistant collects when you feed it to the assistant deliberately. I recently interacted with a mobile personal assistant that seems to rely very heavily, if not exclusively, on explicit personalization. The assistant is called Curious Cat and it’s available on the Android platform. When you start up the app, the cuddly looking cat meows and then begins to bombard you with questions. It asks for your address, birth date, occupation, employer, whether you own an apartment or house, whether you have a car, a motorcycle, or a boat. The prying questions go on and on.
Curious Cat probably has lots of great features and capabilities and I don’t want to disparage it. The process of feeding it with information about yourself is tedious, though. Being asked so directly for private information such as your phone number and other data about yourself feels as though your privacy is being invaded. The end result of the explicit personalization (knowledge feeding) process is probably the same as the outcome of implicit personalization. In both cases, the virtual assistant knows a whole lot about you and could potentially use that knowledge to transgress against your privacy. But implicit personalization seems far less intrusive as a process.
As Flynn states, there’s a lot of discussion that still needs to occur about privacy concerns and how intelligent assistants access, store, and use personal information. In the meantime, intelligent assistant vendors and developers need to firm up their privacy policies and ensure that they have an effective strategy in place for protecting user data and being transparent about how they use it.