This abbreviated history of human-computer interaction follows a clear trajectory of improvement, where each mode of communication with technology is demonstrably easier to use than the last. We are now entering an era of natural computing, where our interaction with technology becomes more like a conversation, effortless and ordinary, and less like a chore, clunky and difficult. Those of us working in the field are focused on teaching computers to understand and adapt to the most natural human actions, instead of forcing people to learn to understand and adapt to technology.

Three years ago, the industry’s only point of reference to explain this technology was science fiction, like the movie “Minority Report.” Then in November 2010, Microsoft’s Kinect for Xbox 360 sensor was released, and broad adoption of voice and gesture technology found its way into millions of living rooms. A year later, Microsoft launched Kinect for Windows, which gives researchers and businesses the ability to take the Kinect natural computing technology to market in a variety of industries.

Since then, major investments in the field have been made by established companies like Intel and Samsung, maturing natural user interface (NUI) players like Primesense and SoftKinetic, and new entrants like Leap Motion and Tobii. Natural computing is moving from the realms of researchers to the minds of marketers, and a true commercial category is starting to emerge.

But even just a year ago, there was no definition, no language and no data for the commercial category. Clearly a richer, more informed language was needed. To this end, my colleagues and I have developed a category framework: Kinect and other voice and gesture technologies are part of the Natural Computing category, defined as input devices that enable users to trigger computing events in the easiest, most efficient way possible. Understanding that the term Natural Computing has a variety of different meanings in academia, we found it was a helpful term to describe the business side of human-computer interaction technologies.

In some respects, there is evidence of natural computing all around us, and there has been for many years. Think of automatic doorways, which open up for you with no effort required on your part beyond walking toward them. Think of automatic faucets, soap dispensers and hand driers — all you have to do is offer them your hand.

These systems are the most rudimentary forms of natural computing. They each recognize a single set of data (your hand placement), automatically interpret your intent (to wash or dry your hands) and immediately respond to it (by dispensing water or soap or air). Now imagine if more complicated forms of technology could understand your intent in all its complexity, and respond to it simply, immediately and perfectly. No learning required. This is how those of us working in this field see the future.

There are currently a limited set of ways that users can interact with computing devices, although there will certainly be more in the future. Today, these include everything from manipulating a mouse and keyboard, to touching, speaking and gesturing. The illustration below breaks down these methods according to how close the user is to the screen (“far” vs. “near”), and how hard or easy it is to learn the technology (“learned” vs. “natural”).

First, each input method is designed to solve for different distances. For example, you need to be right next to a screen to be able to touch it, yet you can be several feet or more away from it when using gesture technologies. Similarly, take into consideration how much time it takes someone to learn how to use the technology. Older technologies tend to take longer to learn (think typing lessons or early command line interfaces) while newer ones tend to take less time (think touchscreens). The combination of these two ideas — proximity and ease of use — make up the Natural Computing Category Map, which enables us to better envision where certain natural computing technologies play a role now and where they could grow in the future.

Figure 1. Natural Computing Category Map (Illustrative)

Within this new, rising category, the technology receives new information with every single gesture, move or sound, and can adapt to what it learns. After one year in market, my colleagues and I continue to see Kinect for Windows as a fundamentally human technology — one that sees and recognizes users as a whole person, with thousands of examples of human-centered applications beyond gaming in industries like healthcare, retail, training and automotive. Additionally, competitive activity has also accelerated, with new sensor and SDK releases, updates to more established open source offerings and significant partnership and investment activity by major players and new entrants alike.

These other gesture-based technology companies have evolved to form partnerships with major computer hardware manufacturers or are exploring the possibilities of integrating the technology in smartphones. The category is growing and evolving rapidly. All this activity accretes to businesses and consumers, who benefit from the quickly evolving natural computing experiences.

The future of the natural computing category is to reach end-users directly, fundamentally changing everyday interactions with technology. Imagine walking by a storefront window and having an avatar mirror your every move, talking to your next-gen TV with the same tone and sentence structure you would use with a friend, or improving your tennis swing with an immersive simulation tool. If you are reading this and wonder what the future of natural computing holds in store for you, the future of natural computer interaction is here already, albeit unevenly distributed. And natural computing is quickly beginning to demonstrate what a computer can do if you give it eyes, ears and the capacity to use them.

Leslie Feinzaig is the Senior Product Manager for Kinect for Windows. Leslie plays an important role in Microsoft’s Kinect for Windows business and has researched and developed great insights into the industry and competitive landscapes around natural computing.

We probably didn’t need a formal study to tell us that.

But that’s exactly what Tobii, maker of eye-tracking technology, set out to do.

The Sweden-based company, in collaboration with AnswerLab, recently pounced on a bunch of people at a San Francisco coffee shop and asked them to participate in a study in which they’d be examining the dating profiles of members of the opposite sex — and during the session, their eye movements would be tracked by Tobii’s sensors.

After participants viewed mock-up pages of eHarmony.com and Match.com profiles, the verdict was in: Men spent 65 percent more time than women did reviewing photos in profiles; women spent 50 percent more time reading the text about a potential mate’s background and interests.

Women also spent an average of 84 seconds gazing at a profile to determine if it was a match, compared to 58 seconds for men.

The study also revealed that people tend to like dating profiles that they feel are more reflective of the kind they would build for themselves. For example, people that prefer to share lots of personal info gravitated more toward very personal dating profiles, while those that stick to “just the facts, ma’am,” liked profiles that had simpler demographic info and data.

Tobii uses tracking technology that zeroes in on a user’s pupil and calculates the point of gaze using algorithms. For heavy blinkers or those with shifty eyes, the recovery time of Tobii’s sensor is between 100 and 300 milliseconds; it draws an “imaginary box” around the user’s head to account for lots of head movement, as well.

For more info on how it works, check out this video from D9, where Tobii general manager Barbara Barclay demoed how Tobii could help users control their laptops with just their eyeballs. Late last month, the company introduced its X1 Light Eye Tracker, marketed mainly to usability and market researchers.

To demonstrate the usefulness of its eye-tracking tech at the consumer level, Tobii is planning to conduct more studies and present more interesting use cases, Barclay said. The next study, for example, might be even more precise: Instead of examining who is looking at pictures versus text, the next study might shed light on which area of the pictures people’s eyes tend to linger on. (We know what you’re thinking right now.)

Ultimately, these types of studies could be most useful for advertisers, as well as Web companies.

The study showed that when there was a great deal of ad content on the right-hand side of a profile page, participants would be distracted by the ads and avert their eyes from the profile information. Great news for advertisers, but bad news for those who want to remain focused on the task at hand.

It’s important to note that the sample for this study was very small: The company managed to convince more than 40 people to try it out, but had to throw away a handful of samples due to inconclusive data, which can be caused by certain types of glasses, lazy or droopy eyes, or an extreme amount of gaze-shifting.

But Tobii’s Barclay says continued testing could help companies determine monetization strategies and how they might conflict with the ultimate goal of a Web site’s content, or to help advertisers make ads more relevant and boost click-through rates.

(Feature photo courtesy of Flickr)

At next week’s Consumer Electronics Show in Las Vegas, Tobii plans to show off how its interactive eye-tracking software, called Gaze, works with Microsoft’s Windows 8 Metro interface.

Gaze would go in a compact rectangular device — smaller than the current 8-inch Tobii IS-1 tracker — that sits below the laptop screen and tracks a user’s eye movement using sensors built into the bar. You activate Gaze by tapping the trackpad once, and Gaze takes a few seconds to find your pupil and calculate the point of gaze using mathematical algorithms. An imaginary “head movement box” is created to delineate a range of motion in which you can still move your head and have the device track you.

In terms of precision, Tobii says the sensors measure within a quarter-inch of the tile or icon you’re looking at. For smaller icons or small text, Gaze still allows a user to navigate the cursor using the laptop’s trackpad, by pressing their fingers down on the pad instead of tapping it once.

Here’s a video showing how it works on Windows 8:

Gaze could, theoretically, work on tablets, too. But Tobii business development manager Anders Olsson says that tablet interaction is so smooth to begin with — with capacitive touch within an arm’s length of the user — that tablets don’t need much improvement. It’s boring old laptops that could use a boost.

“Gaze takes away the whole intermediate step of having a mouse or even using touch technology,” Olsson said in an interview. “We see this as an important innovation because, compared to tablets, laptops feel very ancient right now, in terms of user experience.”

While eye-tracking tech like Gaze could make sense for TV viewing as well, given the growing interest in gesture technology, Olsson said Tobii’s technology isn’t quite up to speed for TV. In fact, it could be a couple more years before Gaze hits the mass market.

Tobii doesn’t plan to sell Gaze directly to consumers, but will work with electronics manufacturers to ship on laptops. While the company says it is in talks with computer makers and electronics manufacturers, it hasn’t officially partnered with anyone, including Microsoft, for the development of Tobii Gaze (although Microsoft is expected to show Tobii eye-tracking demos at its CES booth, as well).

Eye-tracking technology isn’t new, but until now it has been used primarily in niche markets, as a tool for people with severe physical disabilities, or for psychological researchers who monitor eye movement to determine cognitive abilities.

Tobii has been around since 2001, and currently holds 13 patents in the area of eye-tracking tech.

(Image credit: Flickr/Mike Garza)

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OK, some hands: Tobii’s astonishing eye-tracking technology doesn’t allow you to operate all of your computer using your eyeballs alone. But it allows users to manipulate part of the machine, hands free.

This stuff is already in some specialized machines but widespread adoption could be a few years out, Tobii general manager Barbara Barclay said at the D9 conference this month.