(Data) Trust is the New Oil

"Data is the new oil” became a common adage in 2019, and indeed 2.5 quintillion bytes of data are recorded, stored, processed and analyzed, every day. Runaway growth seems inexorable, for organizations that make more data accessible to artificial intelligence will have the best machine learning models, and will ultimately make the best decisions. Companies— and countries-- with access to the most data will win, whether at the games of streaming video, targeted advertising, or even military intelligence. It’s no surprise, therefore, that we’re all designing to optimize for hoovering up as much data as possible.

Over the past decade, a global Open Data movement helped to lay policy, software, and standards groundwork for the collection and sharing of massive public data sets that today drive machine learning models, improving everything from city planning to disaster response.

But when it comes to personal data, this data revolution is often happening at our expense—you can buy 400+ data points from any of dozens of data brokers about me (and 250+ million other Americans), but I have negligible true agency over that data. Pernicious potential results range from discriminatory financial lending based on biased models, to targeted advertising memes that destroy democracies. We have an existential trust problem when it comes to the collection and use of our personal data.

This talk will examine how we can redesign the data economy to optimize for trust, so that we as a society can benefit from the benevolent power of big data unleashed by machine learning, while protecting ourselves from its greatest ills. We will propose the creation of new “Data Trust” organizations that can be trusted to handle the complexity of negotiating at scale between data producers (you and I) and data users (corporations and governments), describe a potential technology “Trust Stack” to enable programing software for trust, and posit how designers of all stripes can contribute to making trust “the new oil.”