Over the last few years, I’ve been monitoring “information” that is being presented on the internet and across multiple channels covering 3 main topics (science, politics, and economics / finance). Truth has always been somewhat elusive (just ask any lawyer about eye witness testimony), but it seems that subjective nature of interpreting truth has overtaken the substantive essence of what we rely upon for our “true north”. Case in point: Just look at the experts that are brought forward to debate the impacts and causality associated with global warming. Both sides are able to bring compelling arguments (facts, data trends, and reflection by certified professionals). On one hand, you could say that certified professionals should interpret data consistently otherwise what’s the point of certification. On the other hand, they may not be reviewing the same data or may be interpreting different summarizations of the same data. So, how can you trust one side over another. For economic and political topics, the consequences can impact the balance of power and/or distribution of wealth and capability amongst one or more populations. For science topics, the impact could be much greater and (in some cases) irreversible.
Here’s the dilemma around trusting what we read and hear: Once we can no longer rely on our compass for guiding decisions, we increase the likelihood of confusion, mis-trust, and lost productivity (lateral versus vertical movement / progress).
So, what can we do ? Well, the good news is that we may be able to leverage technology to improve our ability to validate what we hear and read. By applying the same approaches used to assure Data Quality and Data Integrity to information sources of any kind, we could establish a cross-reference capability to validate and/or challenge published opinions, reports, and conclusions by experts. Perhaps we can start in a few key areas within the Topics of science and economics and compare the conclusions (derived using the technical solution) against a selected set of conclusions (derived by experts). The goal would be to identify bias, non-validated data sources, and confirm or challenge summarized findings which were built using flawed processes (aggregates and/or pattern matches). This would be a non-trivial pursuit, but would be helpful in establishing a reliable source of truth for these established areas and over (over time) be extended to adjacent areas within existing topics and perhaps additional areas in new topics.
Let’s face it, at some point we’re going to have to rely on the technology to guide us along since the amount of information and the pace of change are both accelerating. We don’t have time for bad decisions that are caused by errant data and information (accidental or purposeful …whatever the reason). Too much is at stake and the stakes only get higher. The timing is right…just not sure about the willingness to invest in the technology on this level.
Perhaps it really comes down to one question: Is there a tipping point for investing in the pursuit of TRUTH ?