Your Typing Style as a Password

Paul-Jean Letourneau, Lead Developer for Wolfram Alpha, recently read a New York Times article which detailed how in the future we may be able to bypass the password simply by typing a user name (or some string). The takeaway is that the way you type the characters will be a unique identifier for you and only you.

Using Mathematica, Letourneau then decided to analyze his own typing signature by seeing the difference in keystrokes as he typed “wolfram.”  He details everything in this blog post.

Using this fun little typing interface, I feel like I actually learned something about the way my colleagues and I type. The time to type two letters with the same finger on the same hand takes twice as long as with different fingers. The faster you type, the more your typing speed will fluctuate. The more your typing speed fluctuates, the harder it will be to distinguish you from another person based on your typing style. Of course we’ve really just scratched the surface of what’s possible and what would actually be necessary in order to build a keystroke-based authentication system. But we’ve uncovered some trends in typing behavior that would help in building such a system.

Quite fascinating to put the research and practical together. You can even test your own typing profile by installing a CDF (computable data format) in your browser. Very cool!

Stephen Wolfram on Personal Data Analytics

Stephen Wolfram, the designer of Mathematica, believes that someday everyone will routinely collect all sorts of data about themselves.

In a fascinating blog post, Wolfram admits that he’s been collecting data for many years (since 1990!), and until now, hadn’t had the chance to truly analyze the data. Using the data analytics tools in the latest release of Wolfram Alpha, Stephen Wolfram provides a summary of his outgoing and incoming email (on a daily and monthly basis), the keystrokes he’s used on his computers, how much time he’s spent on the telephone, and the number of steps he’s taken on a daily basis (since 2010). He makes the following observation about his data collection:

The overall pattern is fairly clear. It’s meetings and collaborative work during the day, a dinner-time break, more meetings and collaborative work, and then in the later evening more work on my own. I have to say that looking at all this data I am struck by how shockingly regular many aspects of it are. But in general I am happy to see it. For my consistent experience has been that the more routine I can make the basic practical aspects of my life, the more I am able to be energetic—and spontaneous—about intellectual and other things.

Wolfram mentions that the data he presents in the blog post only touches the surface of the kinds of data he’s collected over the years. He’s also got years of curated medical test data, his complete genome, GPS location tracks, room-by-room motion sensor data, and “endless corporate records.” I am guessing a secondary post from him will be forthcoming some day.

As for Wolfram’s conclusions about the future of personal analytics?

There is so much that can be done. Some of it will focus on large-scale trends, some of it on identifying specific events or anomalies, and some of it on extracting “stories” from personal data.

And in time I’m looking forward to being able to ask Wolfram|Alpha all sorts of things about my life and times—and have it immediately generate reports about them. Not only being able to act as an adjunct to my personal memory, but also to be able to do automatic computational history—explaining how and why things happened—and then making projections and predictions.

As personal analytics develops, it’s going to give us a whole new dimension to experiencing our lives. At first it all may seem quite nerdy (and certainly as I glance back at this blog post there’s a risk of that). But it won’t be long before it’s clear how incredibly useful it all is—and everyone will be doing it, and wondering how they could have ever gotten by before. And wishing they had started sooner, and hadn’t “lost” their earlier years.

Definitely check out Stephen Wolfram’s detailed and insightful post. And if you’re interested in data analytics, this site is a great resource. I also recommend watching the brief TED talk “The Quantified Self” by Gary Wolf.