The meaning of wisdom
BE Insight’s David Brennan shares his guide to creating wisdom out of intelligence
I really enjoyed writing my last opinion piece, exploring the role of insight in an AI-dominated world. I also enjoyed the debate it sparked. So, having explored some of the philosophical issues, I thought I would continue the theme with a look at the practicalities; the ‘how to’ guide to creating wisdom out of intelligence.
To do that, we need to think more about what defines wisdom over mere intelligence and how we can best shape it. So, in true clickbait style, here are five examples of what constitutes real wisdom.
Wisdom focuses on what is meaningful rather than what is available
“The art of being wise is knowing what to overlook” – William James
Too often, we give uncritical credence to the data that is available – and the metrics it produces – when much of it may be flawed, unrepresentative, fragmented and even downright misleading.
We are now so overwhelmed by data availability, we no longer know how to separate the wheat from the chaff. Well-designed insight can focus laser-like on what is meaningful and edit out what is not.
There is a phenomenon within behavioural science called quantification bias – we are more likely to value things we can measure regardless of how true that measurement is; it gives us a feeling of certainty and comfort.
True wisdom goes beyond numbers and looks for meaning. For an example, look at some of the great advertising campaigns that took as their start point a single piece of insight and then single-mindedly applied it to the brand’s strategy and execution.
Wisdom is for life, not just for Christmas
“Knowledge comes but wisdom lingers” – Lord Alfred Tennyson
True insight can stay pertinent for a very long time, because it is focused on universal truths rather than the temporary trends caused by clicks and views.
For proof, take a look at some of the older case studies in the IPA ‘Advertising Works’ series – the insights upon which the best performing campaigns are based upon are still relevant today.
[advert position=”left”]
One great example is the way De Beers associated diamonds with status and the size of the diamond the true barometer of a man’s love for his intended.
When we look backwards we are applying analysis. When we need to predict the future – which, let’s face it, we need to do constantly in these dynamic times – pure statistical analysis of historical data will only work if things stay pretty much the same.
One needs a well-designed insight project to live up to the maxim that if you want to ask people about the future, you need to take them there first. This is the key reason why the vast majority of industry predictions are just plain wrong.
I discovered this when I moved from ITV Network Centre to Liberty Global in the mid 1990s. At ITV, the future seemed settled and the past offered a good basis for prediction. Suddenly I was thrust into a world where all the old certainties felt rickety and unsafe.
I regularly attended meetings where I was asked “what would happen if…?”. The contemporary insight professional rarely gets the luxury of commissioning research to answer such questions these days; they must design insight that can apply itself to many such ‘what if?” questions.
After all, as Nobel-winning physicist Niels Bohr wrote “Prediction is very difficult. Especially about the future”.
Wisdom is sparked by curiosity, not commerciality
“Wonder is the beginning of wisdom” – Socrates
The problem for many of us working in insight is that when we are asked to commission a project, it is often for a specific purpose; usually to sell an idea or a commercial proposition.
One of the ironies of the current state of our industry is that this is often even more the case in the creative and content development fields than in pure commercial sales or marketing.
This is not an insurmountable obstacle, though. All the best insight people have an insatiable curiosity for what drives people to do the things they do, and we now have the understanding of human psychology (courtesy of Kahnemann, De Masio, Thayer, Gladwell et al) and the methodological tools to kill two birds with one stone.
Any insight project that tackles a commercial issue should also contain a deeper understanding of how decisions are made and perceptions formed.
Wisdom explains people not algorithms
“I can calculate the motion of heavenly bodies but not the madness of people” – Isaac Newton
The major gap that is still present in our data-drowned times is the human narrative; we have been too prepared to assume it is covered via the behavioural data, or possibly irrelevant to it. This would be a reasonable assumption if people were rational, or consistent or even vaguely predictable. They’re not.
We are only just beginning to see the backlash against the pitfalls of algorithms and AI; they are often opaque, easily fooled, limited in predictive ability and subject to human biases and assumptions.
To quote data scientist and mathematician Cathy O’ Neill, “Algorithms are opinions embedded in code”. They can often reinforce our own biases and become self-fulfilling prophecy.
True wisdom needs to understand people; in particular the complexities, nuances and emotional characteristics of human decision-making and perception-forming, in order to inform the algorithms and AI programs, but we are still a long way from when artificial intelligence is driven by real or human intelligence (HI).
Wisdom should be testable
“The unexamined life is not worth living” – Socrates
How much of the data we use is really tested and validated? It used to be, when data was scarce, but now we confuse correlation with causation; assume the published numbers are both accurate and reliable; appear oblivious to potential biases or conflicts of interest; and have a generally poor understanding of what goes into the black box that drives many of the applications and outcomes we follow slavishly.
When our assumptions are robustly tested the flaws become apparent. The rapid growth in the volume and quality of econometric testing has demonstrated conclusively that advertising in the online space is far less effective than for legacy media and advertising on social media.
In the era of research, testing the quality and provenance of the data was a key part of the role; in the age of insight, it often falls between two disciplines.
The case for insight
There are many other characteristics of wisdom – such as transparency, universality, integration, nuance and openness to change. It helps to create a tick-list of what a good insight project should offer.
Having judged hundreds of media research papers this year – including the 90+ papers submitted for the Mediatel Media Research Awards – I can confirm that the best of what we do consistently ticks many of those boxes; we need to continue to create, innovate and communicate so that the flood of intelligence becomes a feast of enlightenment.
None of the above points argues for insight instead of analytics, or wisdom instead of intelligence. Unlike digital technology, these things are not binary. It is about adding analogue to digital so that the whole is greater than the sum of the parts – another characteristic of true wisdom.
David Brennan is co-founder, BE Insight