Smart Grid Data: Unexpected and Amazing Reuses?

March 16th, 2010 by Grace Meng

As noted in “In the Mix,” the Center for Democracy and Technology and the Electronic Freedom Foundation recently issued joint comments to the California Public Utilities Commission regarding proposed policies around the use of smart grids and smart meters.

(via Flowing Data.)

And then a few days later, I saw this: EPCOR, a Canadian water utility company, issued a graph plotting water usage during the Olympic men’s hockey final.  Notice the spikes in water consumption (and toilet flushing) immediately after the first period, second period, third period, and finally when Canada wins the gold medal.

Is this our worst nightmare?  That someone will find out when we’re peeing?

That’s a bad joke. Plotting a large area’s water consumption in aggregate is not the same as what some of these smart meters are able to measure in terms of energy consumption.

But I do have a more serious point to make.  One of the points CDT and EFF make repeatedly in their comments is that we should avoid “unnecessary” data collection and destroy any “unnecessary” data.

What exactly does “unnecessary” mean?

Does it mean any purpose that is not related to the work of a utility company?  Who decides what’s unnecessary and should they decide what’s unnecessary and necessary now?

The beauty of data is that its potential value is unknown.  A single dataset, collected for one purpose, can be used for other purposes that are socially beneficial but rather unexpected.  For example, Google Trends was created for advertisers so that they can track what search terms are popular.  The CDC, however, has been using Google Trends to track flu outbreaks, by watching where people are Googling flu symptoms, data which is more quickly collected than reports from doctors.  The reason governments all over the world are pushing for open data is because we don’t know yet all that can be done.  By giving access to everyone, we expect interesting, useful, imaginative things to come out of the data we never might have imagined.

Data from the smart grids, in particular, will also require smart visualizations that are easy for individual consumers to understand and access.  Data alone isn’t going to change behavior.  You can imagine open data inviting developers to create easy to use apps that allow consumers to identify easily and painlessly ways to reduce energy consumption.  Some may even choose to share that information and compete with others, the way several universities have set up competitions between dorms.  As much as Al Gore was embarrassed by news revealing how much energy his mansion used, others may be eager to brag about how little energy they use.

Can we protect privacy while also creating room for imaginative and innovative reuse of data?

There are definitely privacy issues we have to consider.  I agree with a lot of the points made in CDT and EFF’s comments.  That “customer information” shouldn’t be limited to “personally identifying information.”  The misuse and misapplication of phrases like “personal information” is something we’ve been harping on for a while.  That customers should have access to the data collected from them and the power to correct mistakes.  That law enforcement shouldn’t be allowed to troll this information without a warrant, that civil litigants shouldn’t be allowed to access this information without a court order based on a showing of compelling interest and after notifying the customer to provide her with a chance to object.

But rather than talking about barring “unnecessary” data collection and data use, we should be thinking of ways to make the data safely available, regardless of whether someone has decided it’s necessary or not.  The data from smart grids is going to be both dangerous and valuable because it is so fine-grained; we clearly can’t just plop it online.  Anonymizing data is really hard.  So at CDP, we’re working hard at thinking about ways to come up with measurable privacy guarantees and testing technologies like PINQ that promise to provide access to raw data without indicating the existence of any particular individual in a dataset.  Other organizations may have different ideas.  I’m grateful for the existence of organizations that imagine the worst-case scenarios around data collection to protect our civil rights.  I also hope to see the growth of more organizations that try to imagine the best-case scenarios.

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