What Happens in Vagueness Stays in Vagueness

“An investment in knowledge pays the best interest.” Benjamin Franklin  

We don’t know what we are missing.

At this point, when some privacy expert or consumer do-gooder bemoans the fact that US consumers give away their private information for free to behemoth enterprises, we all just shrug and wonder what there is to do about it.  Some of our helplessness comes from general ignorance.

How much is our data worth?  If information about my web searches nets Google a fraction of a penny each month, then 1) I understand that billions of those penny fractions can be profitable to Google, and 2) I don’t care because I am receiving much more value for my ability to make free, effective, lightning-fast searches than I am paying with data value and/or privacy value.  But If my search value is worth forty bucks a month to Google, then 1) Google is making an obscene boatload of money from my search information, and 2) I want some of it back (or at least to shop it around to other search companies, some of whom might pay me for my data).

It is with this context that I read that US Senators Mark Warner and Josh Hawley have introduced legislation to require the big data platform companies to disclose to the government and the general public the “value of their users’ data.” The proposed Designing Accounting Safeguards to Help Broaden Oversight and Regulations on Data Act, shortened to the “DASHBOARD Act” (don’t get me started), would demand companies with more than 100 million users that generate revenue from data collection or processing to disclose to users and the government 1) the types of data collected, 2) how it is used, and 3) an assessment of the value of the data every 90 days.

This Act does not propose to pay users for their data.

I see dozens of issues with this fresh approach to regulating the big consumer information companies, but two that I want to discuss here.  First, how do you figure out the value of a person’s data?  Do you just take the total advertising payments and divide by the number of data subjects?  Or are some animals more equal than others? Would the companies be forced to differentiate between a heavy user who posts all day or runs dozens of searches and a light user who checks in occasionally? Does this mean we would each get a quarterly report from Amazon and Google explaining how our activities led to revenue? Will the value include the massive internal value that a grocer or bookseller gains from the transactional, search and review data collected about each of us.  In other words, a company does not need to develop a sales or advertising price for a datum point to gain immeasurable value from it. Will this value be calculated into the prices we see?

[Caution Cynical Take Ahead] And how will these companies game the system? I have a truism that I state frequently – “Mystery Equals Margin.” The harder it is to tell where profits come from in production and sale of a good, the easier it is to increase profits on that good. Adam Smith’s lovely supply/demand/price curves assume perfect knowledge.  Cloud the buyer’s knowledge and create space for higher profit margins. So the incentive for Amazon, Facebook, et al. will be to understate those value statements and make the process as oblique as possible. [End Cynical Take]

Which leads me to the second point: a moderately accurate reading of the value of data is clearly the first step in creating an open market for information.  If one search engine makes big money from my data and a competitor offers to pay me for the data, I will likely leave my previous favorite search company and move to the more generous one.  “ To paraphrase Charlie Sheen’s character in the movie Wall Street, “How much money do you need? How many yachts can you water ski behind?”  Once there are numbers, even misleading numbers, assigned to data value, these numbers become client differentiators, and companies making tons of money might want to tweak their formulae to keep customers.

This reminds me of recent efforts by both political parties to force health care institutions to publish costs, prices, and profits.  When we finally understand why one hospital in town charges $300,000 for a knee replacement and the cross-town rival charges only $25,000 for the same procedure, we are likely to see some rationalization of pricing methods.  When we know that our transactional data can earn a social media company ten dollars, we can decide whether we are spending our data wisely. Right now, mystery = margin – for both hospitals and internet companies.  We don’t know, so we don’t factor cost into our decisions.  Once we start to understand the value of our data, we may decide to act on the knowledge.  

I am not sure how this would work, but it could be a game changer.