Digital innovation becomes meaningful only when we know the stories behind it
Algorithms, Big Data, machine learning, neural networks and artificial intelligence, they all have the capacity to lift the quality of our lives. Attempts to capture this potential are hampered by secrecy and mystification. It’s time to acknowledge that ‘Digitalization as a black box’ has become outdated. Openness, responsiveness and having a compelling narrative should be the new standard.
Stories help us to give meaning. A good narrative inspires and helps people in the process of decision-making. It holds value when we purchase products or services, in politics, but also when we engage in friendships. In summary, stories are trust providing. That’s why it is so disappointing we still not know the stories behind the many examples of Digitalization that quickly become an ever-larger part of our lives.
Let’s be honest, how should we look at a self-driving vehicle when we don’t know, in case of a collision, how the vehicle’s algorithm will decide between the lives of its (elderly) passengers versus the mother and her children that cross the street? Or if a 50% increase in operational efficiency for job-application evaluations is made possible only by an algorithm’s mathematical rule that says chances for social upward mobility are almost non-existent. Without the underlying stories Digitalization has no meaning.
Every data-driven solution holds its own story. The storyline emerges by the choices we make in bringing together the defined objective and the (quality and ownership of the) data we use. But also algorithm’s if-then-else rationality, which automatically results in trade-offs, strongly influences the story to be told. Openness about objectives, data and both practical as well as ethical parameters for algorithms, make data and analytics meaningful.
Some excellent examples can be found in a recent HBR article by Sanjeev Agrawal entitled ‘Why Hospitals Need Better Data Science’. It shows how objectives such as lowering health care costs and improving patient experience are linked with data on key care-delivery processes like resource utilization, staff schedules and patience admittance and discharge. And how, combined with predictive algorithms, this will streamline operating room scheduling, slash infusion center wait times and accelerate discharge planning. In other words, 100 points!
Those who oppose the new standard often claim that ‘black-box’ is a synonym for confidential business secrets and corresponding business models. This point of view is naïve and shows great resemblance to the mysterious and complex financial products from the early days of this century. Nobody understood these products at that time, but later on they appeared highly toxic and eventually became the main contributors to the largest financial crisis since the Great Depression.
Examples like those in the HBR article prove that honest, inspiring and future proof Digital narratives go well with organizations that are self confident and willing to learn more about their role in today’s data-society. These organizations not only contribute to the social acceptance of Big Data and artificial intelligence, they also engage in more trustworthy relations with all their stakeholders. As a bonus they position themselves in a perfect way to benefit from all future Digitalization opportunities that still lie in front of us.
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