In 1989, the essay ‘The End of History’ by the American political scientist Francis Fukuyama created quite a stir. He wrote that liberal democracy would be free of any serious opposition after the coming collapse of communism. The essay appeared just months before communist regimes in Eastern Europe began to crumble. Therefore, Fukuyama’s words sounded prophetic.

In 1992, he confidently expanded his thesis by predicting an era in which liberal democracy would sweep aside all manner of authoritarianism and become the globally preferred system, guided by established democracies in the West. 

But not long after this prediction, the vacuum created by the 1991 collapse of the Soviet Union was filled by new forms of authoritarian politics. These included militant Islamism and a wayward populism. The latter emerged in established democracies as well, which were supposed to guide the rest of the world towards building democratic societies.

When Fukuyama’s thesis crashed, he did not hesitate to concede that he was wrong and even a bit naive. The reason why he still gets flack for what he predicted over 30 years ago is maybe the manner in which he cold-shouldered the critiques that his thesis drew from various quarters.

While hypotheses created by political scientists can pass a test or fail it, many analysts are now lazily relying on social media chatter in order to determine their views

Yet, years later in 2014, he admitted that his predictions were ‘exaggerated’. Fukuyama’s thesis was not based on mere perceptions. Like a sound political scientist, he drew conclusions after flexing the ever-evolving theoretical tools and models available to political scientists.

But even then, the conclusions can be a hit-or-miss outcome, especially when the tools are used to establish the supremacy of a certain philosophy or ideology on the part of those using them. Fukuyama still applies them. All professional political scientists should, despite getting some of their major analysis completely wrong. Like ‘hard science’, political science too creates certain hypotheses that can pass a test or fail it. Fukuyama’s failed.

The real problem is with analysts who allow themselves to be swayed and swept away by mere perceptions conjured from social media chatter. Some actual political scientists also get influenced by the same. This is intellectual laziness.

When political analysts use robust survey models and analytical tools but still land on predictions that fail to materialise, one can critique their claims, but they can’t be accused of using unsound means. Political science is a way to aid analysts and researchers to ‘stay ahead of the curve’, but this is not always the outcome.

This has especially been the case since the late 2000s, when political scientists and political economists failed rather miserably to predict the 2008 global economic crisis, the consequential rollback of neoliberal economics and, in the 2010s, the eruptive electoral rise of populist sentiments and groups in multiple countries.

In June 2016, when the controversial American populist Donald Trump unexpectedly succeeded in winning the candidature of the Republican Party for that year’s presidential elections in the US, the political scientist Lloyd Gruber wrote that one of the casualties of this was the political scientist. Gruber complained that political analysts just couldn’t see Trump’s rise because it ‘collided’ with a reality that was ignored in their projections.

Such criticisms became more frequent and numerous when Trump actually defeated his Democratic Party opponent, Hilary Clinton, who was overwhelmingly predicted to win. Gruber may not have seen the possibility of Trump’s victory in the primaries, but at least he was able to peek into a reality that most of his contemporaries weren’t able to comprehend till Trump’s presidential victory. The same happened just before the Brexit referendum in the United Kingdom.

One country after another began to witness a plethora of populist groups gaining unprecedented electoral traction, leaving analysts disoriented. But whereas a lot of political scientists admitted that they had failed to even notice this particular curve, they plunged into exploring and studying a reality that they hadn’t bothered to take into account: a reality in which large segments of societies had begun to desire forces that could disrupt and punish mainstream politics for becoming complacent.

Populists capitalised on this sentiment, despite not being taken seriously by political scientists. Instead of testing a newer hypothesis, some political analysts began to simply jump on a bandwagon driven by the sentiments they had initially ignored. This produced a tendency in analysts to start formulating their analysis and projections by following perceptions of political popularity (or unpopularity) populated on social media by political groups. 

Badly bruised by the criticism of them failing to predict the emergence of populist politics in the 2010s, many analysts began to abandon ‘scientific’ or more analytical tools and directly plugged themselves into hyperbolic discourses found on social media platforms. The truth is, the bandwagon that such analysts decided to jump on may not be as robust anymore because the populism of the 2010s might now be struggling to remain relevant, mutating into becoming something even more enigmatic. 

In Pakistan, Imran Khan’s populist Pakistan Tehreek-i-Insaf (PTI) succeeded in proliferating (through social media) the perception that their now ousted and jailed leader was ‘the most popular politician in the country.’ Even his detractors in the mainstream media began to toe this line. Survey results by Gallup Pakistan did not quite substantiate this perception, yet scientific surveys were ignored and sheer perceptions were adopted.

But had the perceptions in this case been entirely true, PTI should have swept the 2024 elections. It didn’t. The proliferators of the perception were conscious of the discrepancy between the perceived and the actual, and thus emerged a new perception that posited that the party had actually won an overwhelming majority but this majority was ‘stolen’ from it through ‘rigging’.

Then, just a month after the elections, the by-elections on 21 national and provincial assembly seats completely undermined the popularity narrative. It was the anti-PTI coalition parties that were victorious on most of the seats.

Instead of admitting that they might have overestimated PTI’s popularity, many analysts went completely quiet, and some even began to echo rigging conspiracies. They had invested so much ego and emotion in their analysis, which is a bad idea to begin with, that the failure of their analysis triggered in them an awkward form of denial.

However, there were also those who did admit that their analysis was flawed. These are the ones who are mostly likely to go back to established analytical tools instead of determining political reality from social media, or worse, through WhatsApp chatter.

Published in Dawn, EOS, April 28th, 2024