Our work investigating potential and plausible futures, involves extensively scanning for trends and signals from which we trace and extrapolate into the future. Both qualitative and quantitative data play an important role. In doing such work, we have observed how data is often used as evidence, and seen as definitive. Historical and contemporary datasets are often used as evidence for a mandate for future change, especially in some of the work we have undertaken with governments and policy makers. But lately we have been thinking if this drive for data as evidence has led to the unshakeable belief that data is evidence.  

“Evidence is just a special kind of data. Data becomes evidence when it stands in a particular testing relationship with a hypothesis.”

Brendan Clarke. Lecturer in History and the Philosophy of Medicine at University College London.

So, why is data being consistently conflated with evidence? As new business models have emerged which commodify data; from Google to Facebook, Uber and Amazon, the paradigm of data capital has firmly rooted itself in our collective consciousness. Big data can be a powerful tool for the good of society, but data is not evidence, and the rise of the use and misuse of big data in policy has risen in parallel with its more commercial deployment.

The drive to collect data and our increasing ability to not just draw connections and analysis from it, but to use the data to train systems, means we need to think through this carefully. With the best of intentions, we may programme our biases into these new systems. By conflating data with evidence, and forming important decisions based on that data, many challenges emerge. Some quick questions that come to mind: 

1. What about what we cannot measure? e.g. The failure of political polling to adequately account for “shy voters” and measure voter preference in the run up to the recent American presidential election and the Brexit referendum.
2. We have the information, so why are we still not doing anything about it?
3. Where is the data generated, who generates it, and what are the generator’s and the interpreter’s inherent biases?
4. Can we rely on using data as our main source of evidence while surrounded by so much uncertainty and change?

We know evidence comes in a variety of forms. Legal and forensic evidence, or perhaps scientific, anthropological or ethnographic evidence easily spring to mind. We are aware of the terms evidence based policy (EBP) or evidence based medicine (EBM), but outside of the disciplines and professions that utilise these practices, how can more organisations and companies utilise evidence to determine their policies, products and futures?

Practitioners from anthropology, ethnography, social sciences and many other disciplines often practice using qualitative data as a research tool. Here, lived experiences, artefacts, and the stories of people’s lives become evidence. These disciplines and their forms of evidence acknowledge the messiness of reality, they acknowledge the difficulty of having to rely on an analysis that is more challenging to quantify. We need to take the risk to listen to and embrace anecdotal evidence, and confront what is happening on the ground floor.

If the examples mentioned previously can be used as evidence to inform policy, and product development today, to what extent can this evidence also help inform decisions we make about the future? In our work we think a lot about evidence, and “make, create, and construct” evidence that is speculative in nature.

These speculative forms of evidence are created not only from deductions taken from data, but from weak signals, ethnographic observations, and the stories of people’s experience. Based on this rich tapestry we create “speculative evidence” from multiple futures, that people can see, touch, listen, and even breathe. For instance we have literally created speculative evidence for a fictional court case Dynamic Genetics vs Mann in which a body of evidence is used to build a case focused on the “theft” of genetic material. For the Future Energy Lab we worked with the Government of the UAE we created air, products, and services from the future in response to econometric data supplied by the Ministry of Energy.  And for our project Muto Labs we collected anecdotal evidence from professionals within the finance and investment industries to determine a potential future for data trading, roboadvisory and the blockchain.

In each of these cases, speculative, yet concrete forms of evidence have become powerful catalysts for directly informing energy policy, product innovation, and new business models. Invariably, these forms of evidence also lead to organisational reflection, and an opportunity to understand the implications of an increasingly accelerated world.

Based on our learnings from this kind of work, we are developing methods for generating frameworks that help extrapolate from such future-facing evidence back into the present, to help transform decision making today.

We want to develop mechanisms for constructively translating speculative and experiential evidence into adaptable policy and systems change.

If you are interested in exploring this with us, we would love to hear from you.