Contextual search and the Internet of Things are two key factors in how search is evolving from users actively searching for information to users receiving information as they need it.
But there is another key component that must be added to the search equation: the rise of intelligent software agents that will not only anticipate the information you need, but also act on that information to help manage your life.
The Dawn Of The Bot Age
Call it artificial intelligence, software agents or even bots, the technology for search-related automated prediction and action has been in development for a long time. (In fact, I used to cover this topic when I was the managing editor for BotSpot.com at the turn of the century.)
(See also Futurist’s Cheat Sheet: Artificial Intelligence.)
In those days, bot development was focused on creating automated software to handle the routine tasks that were proliferating on the then-fledgling commercial Internet. Web crawlers, software that actively seeks out and indexes websites for search engines, were one very popular use of software bots. But there was always a goal beyond the mundane world of Web crawlers and software trying to reasonably fake a Turing test to appear human: developers wanted the software to take specific tasks completely off the hands of humans.
Over a decade later, we may finally be getting to the point where bots can actually do that.
It is not that the development of intelligent agents stalled during the first decade of the 21st Century. Instead, we may not have been quite ready to implement them. Automating routine tasks just didn’t seem like the top priority during the beginnings of the mobile revolution.
Now things have changed. First, and most obviously, mobile devices are everywhere. Second, there are now legions of interesting Web services to automate. The final ingredient is the most important: With the rise of Big Data, there is now enough information available for a software agent to actually use to perform anticipatory actions. In that context, the challenges of applying software agents and artificial intelligence to business solutions is nothing compared to the potential payoff to users.
Dr. Moshe BenBassat, CEO of ClickSoftware, it is fair to say, lives and breathes this stuff every day. BenBassat envisions a world where personal agents, which he calls “butlers,” manage the day-to-day planning and implementing of workflows.
The “Butler” Did It
BenBassat offers an example to illustrate: Imagine a service technician who logs into his smartphone’s service app and pulls up today’s schedule. His first appointment: the Acme Bank downtown. A few more swipes pulls the address from the calendar app and then brings up a map in the navigation app, and off the technician goes. When he arrives at Acme, he finds and calls the customer contact, who has to come down to the lobby and admit him into the building. Once arriving at the customer site on the 17th floor, the technician discovers he has left the replacement part in his vehicle, so he goes back down to get it.
In a scenario like this, BenBassat estimates the technician would spend 7-12 minutes just swiping and typing on the phone to find and use the data he needs. Over the course of the day, that adds up to a lot of lost productivity.
In a world staffed by BenBassat’s butlers, the scenario might unfold like this: The service technician logs into his phone’s service and is immediately informed about the first appointment: the Acme Bank downtown. The butler asks if the technician if he would like a map to the appointment, and after agreeing, off the technician goes, using the map to reach his destination. Just before he arrives at Acme, the butler autodials the customer contact and informs her the technician is about to arrive, so she can come down to the lobby and let him into the building. When the technician leaves his vehicle, the butler senses that the replacement part is not in toolkit the technician is carrying, and prompts the technician to grab it from the truck, saving the trip back down to the vehicle.
“Butlers” like the ones BenBassat describes promise to play a huge role in changing search – and by extension the way we work. Proactive software agents will reduce the need to waste time looking for information. Instead, information will be delivered right when we need it. As software agents get better at figuring out what we want, that information will become more useful and actionable.
We are almost there now: Contextual search tools like Google Now, which takes into account where you are and what you are doing to provide useful information, are the first big step towards anticipatory and responsive software agents.
The Interaction Issue
There is still a ways to go. Social interaction is seen as the biggest obstacle to effective software agents. Agents are only as good as what they are programmed to do, while humans have internalized a lot of common-sense tricks for interpreting reality. We know what we mean when we say, “find me some pizza,” but the software agent might give you a map of nearby pizza places – or just call up pictures of pizza.
In the consumer world right now, Apple’s Siri is the most well-known example thus far of how a software agent will interact with humans, though it has its limitations, both in speech recognition and plain common sense. As that interaction is smoothed out, though, it is not hard to imaging giving agents like Siri or Google Now’s voice search more permissions to act on the information at hand, instead of just reporting it. Once that hurdle is overcome, all of that predictive and contextual information that the Internet is starting to finding for us will have a smooth, human-like interface and better able to help us manage our days.
(See also Who Has The Advantage: Siri Or Google Now?)
Why Search Anymore?
Searching for anything – be it on the Internet, your inbox or on your personal devices and services – will be far less necessary, both in business and personal contexts. Search is not just firing up Google, after all – it also includes combing through your own data for relevant information. When your spouse has a last-minute meeting and can’t pick up the kids from after-school sports, for example, you won’t have to go though a complicated dance of multiple phone calls, texts and emails as you re-arrange both your schedules and stress out over making sure someone gets there on time. Instead, your search agents could analyze and coordinate both your schedules and create a single suggestion to line everything up. All you’d have to do is agree to the changes.
The combination of automated agents, contextual search and a sea of data from our devices, services and the Internet of Things, search is poised to become vastly more useful and efficient than it already is. The pieces are getting there with agents like Siri and contextual search like Google Now. If it all works as promised, information we need will be delivered to us just when we need it, without our having to invest time and effort looking for it.
Image courtesy of Shutterstock.