Technology appropriation happens when a party finds a technology suitable for a particular purpose that conforms to or accelerates existing social conditions or preferences (cultural, economic, and environmental). There are great examples of technology appropriation where the existing culture uses it to elevate their status. For example, Lowriders modify their cars by appropriating hydraulics to lower and raise their cars. These cars are seen as form of pride and identity by Chicanos.
However, technology appropriation can be unpredictable and dangerous. Between 2006–2009, drug cartels in Mexico relied heavily on video streaming websites to intimidate enemies and snitches, and to recruit new members by recording torture and streaming them on these platforms. That seems a grisly new use of a technology, and while it is impossible to predict all the ways in which a technology will be used, it is within our reach (and I’d argue scope) to ask what deeper questions about the cultural context in which tools will coexist.
With Lean and Agile practices, we take a user-centric approach. We make small iterations, and try and our best to do the leanest thing we can that delivers the largest amount of value. We make sure to list our assumptions and create lean scientific tests that will help us de-risk these assumptions. We learn; we build; we measure.
But, when it comes to deeply engraved culture, those characteristic that are so hidden that have us on autopilot, does a Lean and Agile approach surface enough information? While we share with ethnography a focus on the subject (or user, in our case), ethnography moves slow, while Lean moves fast — and I’d argue that information on the cultural, environmental, and economic phenomena can be missed when we move fast. Why not leverage our tools and practices to ask deeper cultural questions that will help us understand more about otherwise hidden contexts (cultural, economic, and environmental).
Food for thought: What if we consider generating “Appropriation Experiments?” In these experiments we can combine social science approaches with the speed of agile. We take our tools and introduce them to unintended audiences. Just like ethnography, we focus on exploring the social phenomena rather than testing specific hypothesis; and just like contextual inquiry, we are inductive. We collect data in a way that accumulates descriptive detail and then let the data speak from the ground up.
We would need to afford more flexibility as to what and how data is collected. We would need to be creative about how we collect data (e.g. journals, videos, audios recordings). It might even challenge us to get better at leveraging other tools like NLP. The type of artifacts we analyze will be more challenging, but holistic. The results of our tests may or may not change what feature we build next, nor can they predict every possible way our tools will be appropriated. But they might help understand challenges our products will face.
My ideas are untested, but as technologist, we have the moral responsibility to make an effort to broaden our understanding of the unexpected ways in which we might be disturbing the waters of a culture, and unexpected behaviors we might be enabling. Again, not because we can predict all unintended use and nor because all technology appropriation is bad. But because we are lucky enough to catch one negative use of our technology, it might change how we approach our products. Let me know if you’re interested in this too, and in how we might apply and test this.