These are notes for a short talk I gave as part of a panel discussion at NSLA's Linked Up, Loud and Literate: Libraries enabling digital citizenship event at the National Library of New Zealand on November 12.
I'm usually a pretty sunny and optimistic person, but this talk as I prepared it took a decidedly bleak turn. It was actually really interesting to write and present something that wasn't exploratory or uplifting, and the resulting questions were more probing than those I usually provoke.
The quality thinking in this piece should be attributed to the cited authors: Cory Doctorow, Maciej Ceglowski and James Bridle. I just stitched it together with some observations from my recent experiences.
I recently returned from a research trip around art museums in the States, looking at, amongst other things, trends in digital development and engagement in art museum.
One strong trend is towards the collection and analysis of visitor data. This isn't through surveys or visitor-trailing, but rather by inducing people to sign up for traditional memberships (where you pay an annual fee for free access to a paid-entry museum) or for a new breed of museum membership, where you trade your data for access and benefits.
The leading exponent of this latter new membership model is the Dallas Museum of Art. Under (soon to depart) director Maxwell Anderson, over the past three years the DMA has removed entry charges and introduced a new Friends programme.
When you sign up for the programme, you give your contact details and your postcode information. In return, you are admitted to a programme where, through various activities, you can gain 'points' that can be traded in for benefits. For example, if you collect sufficient points by entering enough codes from the signs by gallery entrances, you can having your parking charges redeemed. In a city where the car is king, the free parking is a compelling offer. More points get you better access, more special and desirable rewards.
From a body of 100,000 plus Friends, the DMA is able to collect information about which galleries are visited, which programmes are attended, and which rewards are most desirable. Using the postcode information allows them to see where visitors are coming from and, by comparing this information to census data, draw conclusions about which demographics their visitors may represent - at scale.
The DMA is currently using this information to understand which communities they are reaching and not reaching, under-serving and over-serving. The more time that is invested, the more of a data-driven organisation they can become: carrying out targeted programming, marketing and community outreach activities, and measuring whether this has discernible impacts on visitor behaviour.
Now, this can be great. It is all too easy to rely on anecdotal information and your own perceptions of your audience and the success of your initiatives. It can also, I think, get a bit creepy.
We trade our data for convenience, for discounts, and for free things. Who here has bought something on Amazon? Has a Facebook account? Has a loyalty card for which you handed over your email address? We hand over our data merrily and maybe without thought for how this data is being stored, analysed, and shared.
We sometimes provide personal information to other providers of goods and services so that they may assist us in connection with ticket sales, event promotion, fundraising, or otherwise in connection with providing services or merchandise to you. However, we require that those providers use personal information only for that purpose, and we require our providers to provide assurances that they will appropriately protect personal information entrusted to them.
A growing number of American museums are amping up their collection of data in order to increase engagement for the purposes of visitor acquisition, retention and conversion. One museum I met with was planning on implementing the DMA's software with a new free membership programme, with the same intent of understanding visitor demographics. They also had however a clear plan for using this information - this personalisation - for targeted marketing campaigns, and to convert visitors to shoppers, shoppers to donors: effectively, using the data to maximise revenue.
As well as giving us information to improve the relevance of our programmes, tackle inequality of access, and increase revenue generation, data can sometimes tell us things we'd rather not hear.
Colleen Dilenschneider is a consultant with a company in the States that specialises, among other things, in the application of data analysis in the non-profit sector. She writes and presents regularly on data as it relates to cultural and visitor organisations. One of her most recent blog posts crunched the data on free admission days - those monthly free days many paid-entry museums in the US run in the hopes of reducing the barriers to access for non-traditional visitors (read: those who are lower-earning, more geographically distanced, less educated and from a different racial or ethnic background to your average white middle-class middle-aged museum member).
The data shows that free admission days do not attract underserved audiences. Dilenschneider's research shows that:
- Admission price is not identified as the chief barrier to access
- Free access days attract higher earning and higher educated attendees than paid access days
- Free access days do not tempt non-visitors, but rather accelerate the speed at which an existing visitor revisits
- Cultural organisations generally don't know how to, or don't effectively, market free access days to underserved audiences but instead use their email databases, social media platforms and regular marketing outlets to tap the people they are already reaching.
Dilenschneider's company generates these insights by buying data from many sources - the data of people just like us. They then analyse this data and sell that analysis and consultancy services back to cultural organisations - just like ours. I should note that Dilenschneider is not at all covert about this, and in fact that her company has been very generous in allowing her to share this data and information as freely as she does.
There's no escaping the fact though that companies are being built and money being made on the back of the landscape of data we are all drip feeding into.
Concern about the collection, security and use of data - from the outing of philanders on dating sites to a former CIA director's statement "we kill people based on metadata" - are hardly new. As I was preparing for this talk though a number of presentations and articles floated across my radar that shared a common theme - the comparison of data technology to nuclear technology.
In the Guardian in 2008, Cory Doctorow wrote:
We should treat personal electronic data with the same care and respect as weapons-grade plutonium - it is dangerous, long-lasting and once it has leaked there's no getting it back.
Doctorow at that time proposed that data should be embargoed for 200 years, that anyone who touches or cares for that data over that period must be properly trained, and that businesses and government must be made to bear the costs associated with this.
At the start of October Pinboard founder Maciej Ceglowski spoke at O'Reilly Media's Big Data conference. Aiming to puncture the bubble of data enthusiasts, he painted a purposefully grim picture of data as, in his words,
not as a pristine resource, but as a waste product, a bunch of radioactive, toxic sludge that we don’t know how to handle.
Ceglowski drew an explicit link between data technology and nuclear technology, as two powerful innovations whose, in his words, "beneficial uses we could never quite untangle from the harmful ones."
Like Doctorow, Ceglowski describes the similarity between data and nuclear waste - a material that has the potential to last far longer than the institutions we build to manage it. He stated
information about people retains its power as long as those people are alive, and sometimes as long as their children are alive. No one knows what will become of sites like Twitter in five years or ten. But the data those sites own will retain the power to hurt for decades.
He also noted that data technology is creating a situation where people are reacting to the manipulations of big data, purposefully gaming systems, forcing an ever-evolving arms race between data collectors and data creators that creates more distance between us as humans, not more understanding.
Finally, British artist and technologist James Bridle recently wrote an essay, based on a talk at the recent Through Post-Atomic Eyes event in Toronto, that name-checked the two above pieces. Bridle has written and made work extensively about mass surveillance, and in this piece he draws a parallel between the cold war that nuclear technology locked the world into for 45 years and the potential of big data today. Even though the information we collect about human behaviour grows and grows and grows, our sympathy and empathy and connection across politics, races, religions and nations do not leap forward at the same pace.
So, what is my point? We in cultural organisations think of ourselves as the white hats and the good guys. Libraries in particular have a strong ethos of free and protected access to information. The siren call of data is strong however, and we will all soon, if we're not already, have to ask ourselves who benefits from the data we collect, and how we keep each other safe.
At the end of the presentation, someone from the audience asked how exactly we can keep people and data safe. Being no expert myself, I cited the points Ceglowski made himself:
Don't collect it!
If you can get away with it, just don't collect it! Just like you don't worry about getting mugged if you don't have any money, your problems with data disappear if you stop collecting it....
If you have to collect it, don't store it!
... You can get a lot of mileage out of ephemeral data. There's an added benefit that people will be willing to share things with you they wouldn't otherwise share, as long as they can believe you won't store it. ...
If you have to store it, don't keep it!
Certainly don't keep it forever. Don't sell it to Acxiom! Don't put it in Amazon glacier and forget it.
I believe there should be a law that limits behavioral data collection to 90 days, not because I want to ruin Christmas for your children, but because I think it will give us all better data while clawing back some semblance of privacy.