After mapping why many remain excluded in Part 1, I turned to those who did navigate the process, people who reached the counter, found help, or sometimes hit another wall.

“I didn’t think it would work… but the community centre helped me apply for Ujjwala. Two months later, I got a gas connection. No more smoke in the kitchen, a quiet but profound change.”

Shilpa — Housekeeper, Dindoshi

“After my father passed, we got ₹20,000 through a scheme. It paid for rituals and debts I didn’t know existed until an NGO told me.”

Resident, Dahisar

Problems faced by applicants

24%Didn’t understand the process

20%Application rejected

17%Paid a bribe

Problems faced

Most faced confusion, rejection, or bribes; 22% had no issues.

Takeaway: Awareness helps, but navigation still depends on intermediaries, local officers, and informal payments.

When treatment breaks dignity

Three-quarters of rudeness cases came from men; women were often dismissed with “Come later with someone else.”

“Nothing moves without some money changing hands.”

Anil — Driver who paid a middleman for PDS access

“We’ll fill your form, but you’ll only get ₹400 out of ₹3,400.”

Cook, Mumbai

17% admitted paying bribes, the true number is likely higher.

Takeaway: Dignity violations often pave the way for poor outcomes, eroding trust before delivery is even attempted.

No problems vs. unsuccessful applications

Among men, outcomes were split evenly. Few women applied, but those who did often succeeded when guided or accompanied.

Outcome by gender

Men split between success and rejection; women rarely rejected.

Outcome by religion

Hindu applicants mixed outcomes; Muslims reported smoother experiences but were fewer in number.

Outcome by caste

Outcomes were similar across caste groups, but hidden frictions remained.

Takeaway: When dignity is protected, outcomes improve, but small frictions still persist across communities.

Justice — Injustice

Even successful applicants felt fairness was uneven: deserving people left out; undeserving benefitting.

Fairness perception

8 in 10 believed benefits were unfairly distributed.

“It’s not what you know, it’s who you know.”

Takeaway: Fairness is a fragile perception of bias that persists even when delivery succeeds.

Reimagining welfare with AI

When described as a fairness watchdog, not job replacement AI, it gained broad support. Over 80% believed it could improve justice in distribution.

Belief that AI could improve justice

Over eight in ten respondents believed AI could deliver better justice.

“We don’t want to remove our officials. We just want someone watching to make sure they’re fair.”

Resident, Mumbai

These conversations shaped how SARAL was designed not to replace humans, but to restore trust in them through transparency.

Takeaway: Technology is welcomed when it strengthens, not supplants, human roles and makes fairness visible.

Parth Mody
Engineer & Data Scientist — Building AI for Governance

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