If one thought that only the people were divided in their opinion, to add to the confusion the experts are divided too. For every person that believes in the Indian Demonetisation, for example, there is another who doesn't believe in it. If one were to look at the experts for every economist who supports the hypothesis that Demonetisation will not curb black money, there is an economist who believes it will. In addition, there is a third group which professes that the upside of Demonetisation, in any case, is the digitisation of the Indian economy, more than anything else.
In the US, for every person that believes that immigrants should be left alone, there is a person that believe that they should be unceremoniously kicked out of their country. During Brexit, for every person that believed that they should leave the EU, there was one person that believed that they would be better off being part of the EU.
The Likert Scale
When there are strongly polarised opinions, there is bound to be unrest. Likert scaling is a bipolar scaling method, measuring either positive or negative response to a statement. Sometimes an even-point scale is used, where the middle option of "Neither agree nor disagree" is not available. This is sometimes called a forced choice method since the neutral option is removed.
The problem with the current discourse around the world is that most people don't seem to be in the middle of the scale. If you are in the middle or slightly off middle, there is a chance that you may see another person's point of view. But try putting one person who disagrees strongly and another who agrees strongly on the same subject in the same room, not hoping to see some real fireworks.
As a result, discussions on sensitive topics like Brexit, the US Presidential Elections and the Indian Demonetisation is disrupting friendships, getting work colleagues to hate each other, tiffs between lovers and partners, and unfollows between friends on Facebook. The funny thing is that while some of the events are quite old, and decisions have been taken on US Presidential Elections and Brexit, providing something of a fait accompli, the debate and the anger haven't stopped.
Post-truth, Lies and Statistics
Data is misinterpreted more often than you might expect. Even with the best intentions, some important variables may be omitted or a problem may be oversimplified or overcomplicated. And even when two people view the same analytical result, they may interpret it differently. Jonathan Freedland recently wrote a piece in the Guardian called "Don’t call it post-truth. There’s a simpler word: lies". Post-truth politics (also called post-factual politics) is a political culture in which debate is framed largely by appeals to emotion disconnected from the details of policy, and by the repeated assertion of talking points to which factual rebuttals are ignored.
Firstly, the public has got a lot more discerning and is unwilling to implicitly trust politicians anymore. There is too much information floating around - social media has become a myth-buster, for people to innocently consume anything that is being pushed over to them. So what is the underlying trend behind this polarisation? Is it simply that people are tired of the old ways of doing things and that it is just a great desire for change? Because any change would be good compared to the current status quo? Often the winning decision that people have voted for seems to be based not on any great rationale or logic but certainly based on strong emotions. Also increasingly people seem to be caught between two bad choices. Often it has been less about expressing a clear preference but choosing between two sub-optimal solutions. So As Ralph Keyes says in his book on the Post-Truth Era : Dishonesty and Deception in Contemporary Life, "At one time we had truth and lies. Now we have truth, lies, and statements that may not be true but we consider too benign to call false. Euphemisms abound. "
Because we are a data filled society, an increasing trend is the capability for people to selectively pull out data that supports their own truth. The guy who hates the Indian demonetization will pull out data of how the poor people are suffering. The believer, on the other hand, will talk about the digital upsides and give examples of how all the poor people are accepting cheques because actually most of them have bank accounts, that digital payments are on the rise, and whole villages are going digital in India.
Both are right. Obviously, the truth lies somewhere in between and not at the extremes. As Confucious is once known to have mystically said, 'If one person is right it doesn't mean the other person is necessarily wrong'.
-----------------
About the Author:
Prabhakar Mundkur is an ad veteran with over 35 years of experience in Advertising and Marketing. He works as an independent consultant and is also Chief Mentor with Percept H. All previous posts of Prabhakar can be found here.
Chat
Comments