Making Data Serve Humans Through API Design
04 Oct 2016
APIs can help make technology better serve us humans when you execute them thoughtfully. This is one of the main reasons I kicked off API Evangelist in 2010. I know that many of my technologist friends like to dismiss me in this area, but this is more about their refusal to give up the power they possess than it is ever about APIs.
I have been working professionally with databases since the 1980s, and have seen the many ways in which data and power go together, and how technology is used as smoke and mirrors as opposed to serving human beings. One of the ways people keep data for themselves is to make it seem big, complicated, and only something a specific group of people (white men with beards (wizards)) can possibly make work.
The dominant industrial metaphors for data do not privilege the position of the individual. Instead, they take power away from the person to which the data refers and give it to those who have the tools to analyze and interpret data. Data then becomes obscured, specialized, and distanced.
We need a new framing of a personal, embodied relationship to data. Embodied metaphors have the potential to bring big data back down to a human scale and ground data in lived experience, which in turn, will help to advance the public’s investment, interpretation, and understanding of our relationship to our data.
DATA IS A MIRROR portrays data as something to reflect on and as a technology for seeing ourselves as others see us. But, like mirrors, data can be distorted, and can drive dysmorphic thought.
This is API for me. The desire to invest, interpret, and understand our relationship to our data is API design. This is why I believe in the potential of APIs, even if the reality of it all often leaves me underwhelmed. There is no reason that the databases have to be obscured, specialized, and distant. If we want to craft meaningful interfaces for our data we can. If we want to craft useful interfaces for our data, that anyone can understand and put to work without specialized skills--we can.
The problem in this process is often complicated through our legacy practices, the quest for profits, or there are vendor-driven objectives in the way of properly defining and opening up frictionless access to our data. Our relationships with our data are out of alignment because it is serving business and technological masters, and do not actually benefit the humans whom it should be serving.