India’s public discourse today is marked by a degree of political and social polarisation unprecedented in recent decades. In such a charged environment, every announcement made by an interested party—particularly when supported by selective data or anecdotal references—demands careful scrutiny. Yet increasingly, information is received not with curiosity or scepticism, but through rigid filters of ideological alignment.
What is most troubling in
this moment is not disagreement itself, which is intrinsic to democracy, but
the manner in which data and statistics are deployed. Instruments once meant to
illuminate complex realities are now routinely used to reinforce pre-existing
beliefs. Data, which should function like streetlights—casting light to dispel
darkness—has instead become a convenient pole on which narratives are propped
up.
This tendency is
evidenced in recent developments: the Indo-US Trade deal and the social media post
by US President, Donald Trump, referring to the trade deal; the release of the
Economic Survey, Union Budget; and the sharply polarised responses to these
events. Each episode has generated competing interpretations, often based on
selective reading rather than comprehensive understanding.
Trump’s post on his Truth
Social platform offers a clear illustration. Within hours of his limited public
statement on the Indo – US trade deal and also the Tweet by PM Modi,
acknowledging the Indo-US trade deal, opposing camps in India quickly constructed
definitive conclusions. Critics of Prime Minister Modi portrayed the Indo-US
Trade deal development as a diplomatic capitulation, while supporters claimed
it reflected quiet strategic success, arguing that India’s steadfast position
had compelled concessions from the United States. The same fragment of
information produced contradictory narratives, each presented with absolute
certainty.
A similar fate awaited
the Union Budget and the Economic Survey, which preceded it. Intended as a
diagnostic document outlining the economy’s performance, structural challenges,
and medium-term prospects, the Economic Survey was swiftly mined for convenient
excerpts. Optimistic growth projections were highlighted by some as conclusive
evidence of economic strength; cautionary observations on employment,
consumption, and inequality were emphasised by others as proof of systemic
failure. In the process, the Survey’s own caveats, assumptions, and analytical
limitations were largely ignored.
The Union Budget too was
subjected to the same treatment. Within hours of its presentation, it was
declared either visionary or disappointing, inclusive or exclusionary. Selective
data and numbers—tax provisions, capital expenditure outlays, welfare
allocations, fiscal deficit targets—were lifted from their broader context and
pressed into the service of rival political narratives. Once again, the same data
points were used to arrive at entirely opposite conclusions.
What stands out is that each side claims fidelity to
“facts” and “data”. Yet the outcomes could not be more divergent.
This is hardly a new
phenomenon. Indian civilisation itself offers a cautionary tale in the
Mahabharata. Yudhisthira, known for his unwavering commitment to truth,
announces the death of Ashvatthama, adding quietly the word “kunjarah” (the
elephant). Dronacharya, hearing only what aligns with his fear, lays down his
arms and is killed. The statement was technically true, yet truth itself was
distorted through selective emphasis and omission. The episode reminds us that
truth can be undermined not only by falsehood, but by partial disclosure.
One illustrative example
- during the cold war times - is frequently used to demonstrate how narratives were
constructed by the two warring sides, United States and the Soviet Union. In an
imaginary international sporting contest, the US announces that it won Gold,
pushing the USSR to last place, while the Soviet Union declares that it won
silver, relegating US to second-last position. Both claims are technically
correct, yet profoundly misleading. What is left unstated was that there were
only two teams in the contest.
Such narrative
constructions remain deeply embedded in current times in public discourse.
Whether it is a Trump post, Economic Survey, or the Union Budget, selective
emphasis is used to manufacture certainty and moral clarity where none truly
exists. Social media platforms, designed to reward immediacy and emotional
engagement, amplify this tendency, encouraging citizens to retreat into
ideological echo chambers.
As someone long engaged
in science communication, I find this trend deeply concerning. Science instils
a fundamental discipline: anecdotal data does not constitute evidence; isolated
observations do not establish causation; and interpretation without context is
inherently incomplete. Science and rationality warrant that data must be
interrogated, its assumptions examined, and its limitations acknowledged before
conclusions are drawn.
Public discourse today
increasingly departs from these principles. Data is often treated as a verdict
rather than a signal, as proof rather than a prompt for further inquiry.
Economic indicators are presented as definitive judgments instead of partial snapshots.
Nuance is dismissed as equivocation, and uncertainty is portrayed as weakness.
Economic Surveys are
diagnostic tools, not report cards. Budgets represent complex trade-offs shaped
by fiscal constraints, global conditions, and competing social priorities.
Trade negotiations unfold over time and rarely conform to the dramatic
narratives of instant victory or defeat that dominate social media. Yet these
realities are flattened in the rush to claim validation or assign blame.
The deeper danger lies
not in disagreement but in the erosion of public reason. When citizens consume
news primarily to confirm their beliefs rather than to challenge them,
democratic debate is impoverished. When data is used selectively to legitimise
predetermined conclusions, trust in institutions and expertise gradually
weakens.
Scientific temper,
enshrined in the Constitution of India, must extend well beyond laboratories
and classrooms. It must equally apply to how we read economic surveys,
interpret budgets, and respond to political claims. Scientific temper requires skepticism
without cynicism, openness without gullibility, and a willingness to hold
competing possibilities in mind.
Data must serve as a
streetlight, illuminating complexity rather than obscuring it. When it is
reduced to a pole supporting narratives we already believe, it ceases to serve
the public interest.
Democracies rarely erode
through sudden collapse. More often, they weaken gradually, as truth becomes
fragmented and citizens retreat into separate interpretive worlds, each
convinced of its own completeness.
In such times, the most responsible civic act may be
the simplest: to pause, read carefully, ask what is missing, and think
rationally—before choosing what, and whom, to believe.
