Resistance is futile

The Borg are a fictional alien race that are a terrifying antagonist in the Star Trek franchise. The phrase “Resistance is futile” is best delivered by Patrick Stewart in the episode The Best of Both Worlds.

When IBM demonstrated the power of Watson in 2011 by defeating two of the best humans to ever play Jeopardy, Ken Jennings who won 74 games in a row admitted in defeat, “I, for one, welcome our new computer overlords.”

As the Edward Snowden revelations about the collection of metadata for phone calls became known, the first thinking was that it would be technically impossible to store data for every single phone call – the cost would be prohibitive. Then Brewster Kahle, one of the engineers behind the Internet Archive made this spreadsheet to calculate the storage cost to record and store one year’s-worth of all U.S. calls. He works the cost to about $30M which is non-trivial but not out of reach by any means for a large US Gov’t agency.

The next thought was – ok so maybe it’s technically feasible to record every phone call, but how could anyone possibly listen to every call? Well obviously this is not possible, but can search terms be applied to locate “interesting” calls? Again, we didn’t think so, until another N.S.A. document, cited by The Guardian, showed a “global heat map” that appeared to represent how much data the N.S.A. sweeps up around the world. If it were possible to efficiently mine metadata, data about who is calling or e-mailing, then the pressure for wiretapping and eavesdropping on communications becomes secondary.

This study in Nature shows that just four data points about the location and time of a mobile phone call, make it possible to identify the caller 95 percent of the time.

IBM estimates that thanks to smartphones, tablets, social media sites, e-mail and other forms of digital communications, the world creates 2.5 quintillion bytes of new data daily. Searching through this archive of information is humanly impossible, but precisely what a Watson-like artificial intelligence is designed to do. Isn’t that exactly what was demonstrated in 2011 to win Jeopardy?

Savvy IT Is The Way To Go

There is a lot of discussion in the context of cloud as well as traditional computing regarding Smart IT, Smarter Planets, Smart and Smarter Computing. Which makes a lot of sense in light of the explosion in the amount of collected data and the massive efforts aimed at using analytics to yield insight, information and intelligence about — well, just about everything. We have no problem with smart activities.

We also hear a lot of speculation about the impact, good and bad, that advances in technology, emerging business models, and changing revenue, cost and delivery processes will exert on IT, and specifically enterprise IT. Add to these the predictions of the end of ‘IT as we know it’, with prognosticators describing a looming radical alteration in enterprise computing as in-house IT culminates in applications, data and computing moving into vast, amorphous clouds of distributed, but still centralized infrastructure and data centers. Who is kidding whom?

Smart computing isn’t going to go away, and it makes a point. However, our contention is that it takes more than just Smart IT to succeed; it takes Savvy IT.

Savvy IT complements and extends smarts – with the ability to leverage all of what you know and what you can do to be successful. Savvy can be used as a noun, an adjective and a verb. The definition of the adjective describes Savvy as “having or showing a clever awareness in practical matters: astute, cagey, canny, knowing, shrewd, slick, smart, wise”. More colloquially, it means acting and being ‘street smart’. Watching and listening across the industry, we see a market evolving to favor moving with Smart IT to Savvy IT.

Savvy IT is concerned with optimizing the use of IT infrastructure, assets and resources to achieve enterprise goals. Savvy IT acts proactively to drive line of business staff to use emerging technologies by helping them to understand how technology can help develop and implement new business models and revenue streams.  It is interactive, coordinated and cooperative efforts targeting external, as well as internal customers.

It’s about a ‘street smart’ application of technology to solve problems and drive organizational success. It is based on the insight of personal experiences that includes an awareness and knowledge about the business, their industry and personal efforts to exploit data, capabilities and technology. Finally, it’s about a CIO who pursues the goal of making sure IT’s services are at least the same, if not better than the best services available from SaaS or service providers.

An explicit example of Savvy IT appears in the evolution toward real solutions to comprehensive business and operational problems that are driven and developed from the perspective of the customer or client end-users. Savvy IT works with the business to proactively identify, develop and implement technology-dependent innovation that act as game changers for the company.

One example is the radical alteration in the sped up cycle of development, testing and distribution of business applications as they become app-based services. Or, when IT staff leverage transaction merchandising services across multiple technologies – linking transaction services in mobile technologies with traditional systems of record  to provide a seamless purchase experience whether ordering a purchase on-line, from a phone or flyer with the option for at home delivery or pick-up at a ‘brick and mortar’ store. An innovation that gives global merchandiser, Target, a significant competitive advantage.

Savvy IT requires both innovation and invention in the application of technology combined with experience that knows where and how to focus efforts that will either solve problems or reduce their impact in favor of continuing services. Smart operations provide a foundation on which to build; savvy tempers fashion with experience that ‘delivers’ despite the obstacles and challenges that inevitably arise.

In implementation and practice, Savvy IT involves and applies whether the model for IT services is built exclusively around an internal data center, an external cloud or service provider or a combination of both. Implementing Savvy IT is an organizational challenge that starts with IT, but extends to include the whole enterprise. Savvy IT is street smart. It’s about protecting the business from risks, existing and emerging that persistently evolve. We’ll explore more of the implications, impacts, processes and issues over the coming months.

Feel free to send any comments, questions or discussion about Savvy IT, pro or con, as well as other topics of interest to Rich Ptak: rlptak @ptaknoel [dot] com.

The Dark Side of Big Data

study published in Nature looked at the phone records of some 1.5 million mobile phone users in an undisclosed small European country, and found it took only four different data points on the time and location of a call to identify 95% of the people. In the dataset, the location of an individual was specified hourly with a spatial resolution given by the carrier’s antennas.

Mobility data is among the most sensitive data currently being collected. It contains the approximate whereabouts of individuals and can be used to reconstruct individuals’ movements across space and time. A simply anonymized dataset does not contain name, home address, phone number or other obvious identifier. For example, the Netflix Challenge provided a training dataset of 100,480,507 movie ratings each of the form <user, movie, date-of-grade, grade> where the user was an integer ID.

Yet, if individual’s patterns are unique enough, outside information can be used to link the data back to an individual. For instance, in one study, a medical database was successfully combined with a voters list to extract the health record of the governor of Massachusetts. In the case of the Netflix data set, despite the attempt to protect customer privacy, it was shown possible to identify individual users by matching the data set with film ratings on the Internet Movie Database. Even coarse data sets provide little anonymity.

The issue is making sure the debate over big data and privacy keeps up with the science. Yves-Alexandre de Montjoye, one of the authors of the Nature article, says that the ability to cross-link data, such as matching the identity of someone reading a news article to posts that person makes on Twitter, fundamentally changes the idea of privacy and anonymity.

Where do you, and by extension your political representative, stand on this 21st Century issue?