9 05 2013
Reducing digital overload
What is the biggest problem most of us face today using our digital devices and services? Too much of a good thing.
Email and other messaging systems are wonderful inventions, but we spend too much time going through irrelevant or marginal messages. Web resources are indispensible, but search engines too often return an overwhelming number of options rather than an answer. Social media can be wonderful at times, but also can be overwhelming in their demands. And today’s software and devices have so many features that we often spend more time mastering them than using them.
Some recent “innovations” move us toward even more interruptions, supposedly in the name of efficiency. Google Now and Windows 8 tell us what the software thinks we want to know. (I can tell it is sunny in LA by looking out the window, thank you.) More demands on our attention.
There is a productivity crisis. Driven by an assumption that individuals want more information and more features, most companies are compounding the problem rather than addressing it.
The Software Society suggests that the “personal assistant model” will drive the next wave of technology innovation. How will it address this personal productivity crisis?
The ideal personal assistant would be a pervasive manager of your digital life, whatever device you are using. You tell it what your priorities are, and it avoids interrupting you unless you make a specific request. Most proactive notifications should be the result of specific requests: “Remind me when to leave for my 2:30 meeting.” It can use machine learning to prioritize messages for you, providing a “high priority” email folder, for example, by filtering your emails based on how you have filtered them in the past or because you have told it, “Email from this person is high priority.”
The personal assistant should be able to guide you through any feature of the device or software you are using. Done correctly, it will be a unifying user interface.
When you ask for information, you should get a direct answer, even if the assistant must ask clarifying questions. You shouldn’t find that the question requires exploring a long list of options to get an answer. Your personalized assistant can call on specialized assistants, such as travel assistants or a company customer service assistant, when specialized knowledge and data are required.
And the navigation among assistants must be intuitive. We must be able to ask a general personal assistant for a specialized assistant and have it understand how to find that assistant. We must be able to return to the general assistant from a specialized assistant by invoking its name.
Specialized personal assistants should still be “personal,” despite being specialized. For example, a customer service assistant should feel as if it is representing you to the company, rather than being an agent of the company. It shouldn’t, for example, force you to provide more information than necessary before even asking for your request.
Are we there yet? Not close. It’s not just an issue of the underlying language, machine learning, and knowledge representation technologies; those tools need improvement, but have passed the threshold of utility. These technologies are capable of supporting the goal of making us more efficient, protecting our time. The key to personal assistants being embraced passionately by the general public is making it a major objective of those assistants to address the productivity crisis. If they are designed with the primary goal being reducing complexity and information overload, they will dominate the next generation of digital devices.