Read the following passage carefully and answer the questions that follow.

For those of us who work in the Sciences, the last decade has been a boon to research and discoveries. This has been facilitated by the massive data collection and data analysis which would have been inconceivable just a few decades ago. As a side consequence of these changes, many of us thought that the time has finally arrived where data will be the absolute arbiter of truth. If the global events of 2016, in general, are any indication, then we were dead wrong thinking this. One may even ask, in an era of fake news and alternate facts, is data that relevant? One can do all the fact-checking in the world but it won’t matter if the person to whom the evidence is being presented gives the rejoinder, ‘What does the evidence have to do with it?’

As a data scientist, I imagined that an argument based on careful analysis of data coupled with sound statistical reasoning should be enough to convince any person of one’s argument. However, in many contexts, this may have the opposite effect. Thinking about why people act this way becomes easier if we rather drop the assumption that people are rational and start thinking that people’s rationality is mediated via emotions. However, there is a hidden assumption in this assertion that all people evaluate evidence in the same manner. The presence of confirmation bias and other cognitive biases in humans tell a different story altogether. People are more likely to be sceptical and thorough in an investigation if the evidence presented to them goes against what they already believe. Even things like what people perceive as the scientific consensus varies from person to person.

The current political climate of data nihilism did not arise in a vacuum. In the nineties, we had the culture wars including the assault on science in public schools. Post-modernism also played a role in relativizing truth. All this may sound gloomy as journalists even wrote about the death of facts as early as five years ago but now people are even questioning whether one can no longer even trust the data that the government is collecting. The history of the 20th century is a testament to data manipulation by different communist regimes and ideologically driven research agendas that led to nothing.

Then there is the Dunning-Kruger Effect where people with low competency tend to greatly overestimate their ability in a given area of expertise. Couple that with culturally induced ignorance and we have a recipe for disaster. Confucius had a maxim that real knowledge is to know the extent of one’s ignorance. The rise of populism and authoritarianism in the world as of late has been a grim reminder that people are far from rational. The phenomenon of data nihilism and culturally induced ignorance do have one thing in common, an appeal to values. Studies show that people are more likely to change their minds if there is an element of social desirability involved. If a person thinks that changing their position in a certain context is non-threatening or desirable then they are more likely to engage and even change their position. You don’t lead with the facts to convince. You lead with the values – to give the facts a fighting chance. So data scientists and journalists have a harder task at hand, not only do we have to use data to tell stories but also we have to use idioms and framing that makes the other side listen. That solves half of the problem, i.e. the presence of ignorance, but if the problem is just data nihilism then all bets are off.

In this passage, the author is primarily trying to: