AI – is Mark Carney right?

There has been a lot of noise about Artificial Intelligence (AI) recently, in particular about its potential to cause huge redundancies in the current work force – with Bank of England governor Mark Carney’s recent cataclysmic forecast the latest doom-laden prognosis.  

But even before the governor jumped on the AI bandwagon, everybody was talking about AI, particularly the mainstream media. Print and broadcast coverage ranges from optimistic utopias to gloomy predictions exploiting ‘Frankenstein anxiety’ and the possible consequence for our lives.

Let’s have a look at Carney’s doomsday warnings about the consequences of a widening application of smart technology on the demand for human labour. It is a fact that AI can lead to massive improvements in productivity. In 2014 a study by Deloitte and Oxford University estimated that 35% of UK jobs are at high risk from automation over the next two decades. Obviously, low-paid, low-qualified workers are more vulnerable to being replaced than high qualified professionals. But there is also an argument that by replacing high-pay, higher qualified functions within a business, AI could have an even bigger impact on the bottom-line.

So from a market research perspective, what is our place in a world that is increasingly shaped by the application of AI?

Firstly, I have a problem with the thoughtless and often incorrect use of the term ‘AI’ in all this. There is a tendency now to call any kind of algorithmic automation ‘intelligent', as if the automation of human tasks was a completely new development.

But it is the notion of ‘artificial’ intelligence that seems to frighten us, and that leaves us with the prospect of being substituted by machines. In reality, we are still far away from creating a system that could be truly classified as intelligent. Rather, what we currently see is the increasing use of machine learning designed to help humans in very specific tasks – and these are often tasks that humans do not, and cannot, actually perform.

For instance, a recent article in the Stanford Medicine News suggested that a computer program beats human pathologists in predicting the severity of lung cancer.  It might be true that a machine learning algorithm, trained on thousands of historical cases, can more accurately predict the survival rate after a given time span than human doctors can. But predicting survival rates is something that doctors do not do! They decide on the treatment, surgery or no surgery, chemotherapy or radiation. They are not trained to predict how much time a patient has left. And this is just one of many examples where machines and algorithms might outperform humans without making them redundant.

So rather than being scared of AI, we have to identify areas within market research where AI can help us to do something better, more productively, at a larger scale.

An obvious opportunity surely lies in the way we gather data. Let’s be honest: we, as an industry, have not been very creative so far in exploiting the true opportunities that online research offers us. We have simply taken our pen and paper surveys and put them onto websites, using the same rigid process of walking a respondent through dozens of questions.

Meanwhile, the world around us is increasingly populated by virtual chatbots which numerous organisations now use to answer customer queries.  RBS and Natwest, for example, have recently announced that they will use these virtual customer service agents to help them sorting out issues with their credit cards and accounts.

So why not turn it around and use chatbots to ask questions?  Bots could become the new survey tool, in particular in customer satisfaction research. Instead of asking a customer to fill in a boring survey, chatbots offer the ability to gather customer feedback in an engaging, conversational way.

The algorithms can be trained and optimised to specific domains and can control the interview flow, asking for more detail when responses are too generic, and digging into pain points detected via sentiment analysis.  Let’s defy the governor’s fears and use opportunities like this to take online research to a truly new level.

Frank Hedler, director advanced analytics, Simpson Carpenter