The partnership with ASUS will see the Leap, a device about the size of a pack of gum, bundled with select ASUS computers shipping this year. The Leap functions much as a Nintendo Wii or Xbox Kinect but is much more precise and sensitive, tracking movements of both hands and all 10 fingers at 290 frames per second and detecting movements as small as 1/100 of a millimeter.

I talked to Leap Motion’s president and chief operating officer, Andy Miller, about the announcements.

“We’re starting with all-in-ones and then moving to high-end laptops,” Miller said. “An all-in-one is just a great demonstration of our technology.”

Bundling the Leap with ASUS is just the beginning, Miller told me. The Leap adds physical gestures to the now-standard computer interface vocabulary of visuals, mice, keyboards, and touch, and “lots of other OEMs” are interested in the technology.

“Companies are interested in using Leap in laptops, tablets, robotic surgery … we’ve been contacted by thousands of places from fast-food places to fighter jet manufacturers to integrate this technology,” Miller said.

40,000 developers have expressed interest in building software that takes advantage of Leap’s gesture technology, and Leap Motion has already sent out 12,000 units to help developers build and test their code. Apps that are being built for Leap include games, productivity apps, music and art apps, and more, Miller said.

Leap Motion is also building an app store so that developers can monetize their Leap-compatible apps. The app store will be available for both Windows 8 and Mac OS X.

I asked Miller if Asus will be building any Leap-specific apps, as the computer manufacturer has already built a significant amount of software for its netbooks, laptops, and desktops in an attempt to differentiate itself from competitors. Miller confirmed that “it’s on the table,” and that the Leap is now “getting into their roadmap,” which would enable ASUS to build software that integrates gestures into a native, built-in way to interact with the company’s PCs.

Leap’s gesture-based technology seems a natural for gaming, and Miller said Leap Motion is also talking to gaming console manufacturers about incorporating better-quality gesture support into their platforms, but that “it’s not our priority right now.”

The Leap is now available for preorder at $69.99; the retail version, when available, will cost slightly more. ASUS has not yet set pricing for its Leap-equipped PCs, however.

The new $30 million funding round will help Leap Motion bring the technology to other OEMs and to retail channels later this year.

“Leap Motion is poised to fundamentally change human/computer interaction, and this new funding will help us bring our technology to the mass global market,” Leap Motion CEO Michael Buckwald said in a statement. “With this influx of capital, coupled with the major OEM partnership we also announced today, we’re ready to make 2013 the year of the new interface.”

Here’s a Leap in action:

The only thing needed now? Software that understands gestures.

Which is precisely why over the next two weeks, Leap Motion will send 10,000 Leap units to new developers to help them build software applications and games which take advantage of the new gesture-based input capabilities … and why the company has attracted over 40,000 developers so far.

San Francisco-based Leap Motion has already put the Leap device into limited mass production.

It’s about the size of a pack of gum, or small iPod. Sitting right in front of your Mac or PC, the device senses your hand motions and allows you to control your computer with hand gestures in the air. Those motions will allow you to zoom in on pictures, rotate on-screen 3-D objects, draw, write, create 3-D computer-aided designs, and much more.

The device costs about $70 at pre-order prices, and will be delivered to consumers in early 2013. But before the hardware is delivered, Leap Motion wants a rich software ecosystem.

So the company is also releasing an updated software development kit (SDK) today, with new features that will help developers build gesture-aware apps much faster than before. The new SDK offers pre-fabricated building blocks: a library of defined interaction APIs. Which means that instead of trying to comprehend how a user’s hand moved, developers will now have access to a library of sensed motions: a twist, a push, a sweep. The Leap software will report a defined and pre-identified motion, and developers will now simply need to map that gesture to actions in their applications.

“Our top priority is making sure that when the Leap Motion controller ships to consumers, it is supported by a wide array of quality apps,” Leap Motion co-founder and CEO Michael Buckwald said in a statement.

Leap Motion released a demo app showcasing how an intern software developer used the new SDK to create a simple 3-D game:

Finally, the company announced that Leap will ship with an app store, so users can pick up more software that understands what they are doing with their hands, and so developers can monetize their creations.

There is no word yet, however, on whether major applications such as Microsoft Office, iPhoto, or even web browsers such as Chrome will incorporate support for Leap gestures. Or whether operating system vendors such as Microsoft, Apple, and Google (yes, Chrome OS) will built support for Leap right into the system.

Leap Motion has raised $14.55 million from various investors to take the Leap and its gesture language to the world.

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I recently talked to Nass about his work and his book, in which he uses our interactions with machines to investigate how human relationships could be improved.

Naas stumbled across sociology by accident, deciding it was the easiest possible course to take to get enough credits to finish his degree in Computer Science. Soon he realized he was in a unique position as a sociologist who knew how to program a computer. Software was a new tool for research. As he says, “Galileo was one of the first people in the world to have a telescope. He was bound to discover something.”

The perfect confederate

What Nass discovered is that we treat machines to some extent as if they are were also human, and highly tech-savvy people like software developers are no exception. He gives an example where people were asked to evaluate a piece of software they had been using. In one group of participants, the evaluation was done on the same computer on which the software being evaluated was used, in the other not. The first group gave consistently higher evaluations. Unconsciously, they didn’t want to “hurt the computer’s feelings”, said Nass.

Some issues in sociology and psychology are difficult to investigate because of what is called the confederate problem. Let’s say you want to design an experiment to test how people react to flattery. In such an experiment, the scientists need an assistant, whose complicity is unknown to the other participants, to do the flattering. The problem is that so many variables exist in the simplest social interaction that the experience of each participant is never exactly the same. Nass, through his work in human-computer interaction, realized that he had found the perfect, consistent confederate: a computer. Now he uses our relationships with computers to learn how we interact with each other.

How to build a team

One of the subjects Nass tackled, and discusses in the book, is team-building. He says only two things are required to make a team. The first is identification (knowing you are on the blue team or the development team of Startup A), and the second is the sense that success depends on everyone in the team. One of the traditional ways for tech companies to promote their products is to give out t-shirts at tech events. Nass sees this as a wasted opportunity. The point of the t-shirt is to build a team, which means that only employees should be able to get hold of them. Otherwise the identification is not effective.

He conducted experiments where participants had to perform some tasks on computers. Each computer was arbitrarily assigned to a red team or blue team simply by tying a cloth of the appropriate color around it. Participants quickly start to rate the computers on their “team” as better, faster and more helpful.

How to persuade

Another issue Nass examined was persuasion, in particular in the area of recommendations. When it comes to “experience goods” like perfume, whose qualities you can’t judge just by looking at them, social recommendations from “people like you” of the type used by Amazon are very effective.

With “search goods” like cameras, consumers are more swayed by recommendations based on perceived expertise, like a review score based on 30 aspects of the product rather than 5. In fact, the two general factors involved in persuasion seem to be perceived expertise and trustworthiness, where the latter means whether you think the recommender has your best interests at heart.

Asking for favors

Some of the most striking of Nass’s experiments involved testing the best way to get people to reveal information or do you a favor. Participants in one experiment interacted with a program that said something like “Most PCs these days have at 2MB of memory. Being an older model I only have 1MB. What do you feel inadequate about?” Participants were much more likely to reveal personal information in this case then when the program simply stated the specs of the machine.

The same was true when a search program was configured to be “helpful” or “unhelpful”  in some search tasks participants performed. When people were then asked to help optimize the screen resolution on a computer where the program had been “helpful”, they were much more likely to do so than with the less helpful version.

Social Prosthetics

Nass expects technology to get better and better at following the social rules and therefore seeming more human. He cites the example of a navigation company that instead of saying, “Turn left after 30 meters” is starting to use landmarks instead, such as  “Turn left after the supermarket”, since this is much more natural for people.

He even envisages software built into cell phones, which would change the speed and cadence of our voices to match that of our conversation partner, something humans do naturally but which some people do better than others. He calls such tools social prosthetics since they make us more likeable. It’s not hard to see an era when technology adapts itself to us so efficiently that we find it more pleasant company than other human beings. There’s something quite disturbing about that thought.