|We should change our mindset about data transparency / Photo Credit: Gorodenkoff (via Shutterstock)|
“Striking it rich,” quoted Alex McDougall of Coindesk, a news platform on blockchain. This comes from natural resource exploitation. Prospectors would extract oil from an easy patch of ground, sell it, and watch themselves get rich. But this is the old oil. The “new oil” of today’s world is worth billions of dollars, but we haven’t figured out how to refine, sell, extract, and establish its value. We’re bad at compensating the owner of the personalized data they exclusively created. We don’t tell data creators that we’re “mining” them, manipulating their subconscious biases through engagement algorithms to encourage them to take action that allows their data to be more vulnerable.
Hence, it’s no surprise that the most valuable firms of today are driven by data and AI. It’s also not surprising to know for large companies to realize the value of the resource by harnessing and monetizing it. However, we tend to exclude data creators to the point where we don’t have a model to fully understand “how we could do it better.” Who owns the text you type on Gmail or what you search on Chrome? There are no rigs or trucks, just a business model that confuses users and user experience that creepily shows targeted ads to you on random websites. 2019 saw the increase in data spills due to how various parties value data and the antiquated means to protect it.
With data breaches occurring left and right, we are now starting to demand the best from our platforms. Altruism is one way to address the problem of extraction and regulation, so as establishing penalties for egregious data policies. Hopefully, the norm will be changed this year. Big data transparency will not happen overnight. However, we can change the mindsets of transparency and value sharing by creating models that utilize our existing hardware, software, and consumer behavior.
This approach enables us to start bringing data creators into the value chain, proving that shared data is better than extracted data. After all, shared data is timelier, more relevant, more accurate, and more ethical.