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It’s been over three years and more than 150 stories on Decode, the vertical I built for BOOM. In that time, I’ve learned a lot about technology — enough to get on the nerves of more than a few tech bros I’ve met. I don’t hate technology; in fact, I find it exciting (I talk about it at parties and dates, sigh). The reason I still care so deeply about these stories, despite all the scrambling for angles and endless back-and-forth with reporters, is because, accountability sits at the heart of them. That’s what keeps me hooked.

Lately, when people ask me what Decode really is, I find myself pointing to my colleague Hera Rizwan’s story:  When A Face Scan Decides Who Eats And Who Keeps Their Job

The story is about the mandatory use of facial recognition technology (FRT) to verify identities before distributing Take Home Ration under the Integrated Child Development Services scheme. ICDS is supposed to support pregnant women, lactating mothers, and children under six with vital nutrition. Yet, with FRT, a simple mismatch in face data can mean a child goes hungry.

I keep returning to this story because it highlights a bigger tension: in a world already divided by economy, caste, politics, gender, and culture, technology isn’t neutral. It shapes who gets access, who gets excluded, and who holds power.

This week, I want to share the work of my colleague Karen Rebelo, deputy editor at BOOM. She spent time as a fellow at the Reuters Institute for the Study of Journalism, Oxford, where she wrote a research paper on how journalism can hold technology accountable — especially when it shapes welfare, employment, and rights. With her permission, here are some highlights, along with my own thoughts to place them in context.

Karen writes:

DPI — Aadhaar, UPI, and a whole network of APIs that let others build on state-backed systems — has been sold as efficiency, inclusion, even global leadership. But, as Karen shows, the cracks are real. And they’re deeply exclusionary.

Take welfare delivery.

So apt. That “choose the traffic lights to prove you are a human” moment is fine until it becomes a daily reality for people dependent on state support — forced to constantly prove they’re “worthy” of it. A complete reversal of what welfare is supposed to mean.

And sometimes, systems are rolled out without even being functional. Journalist Varsha Bansal came across an engineering student who was part of the team that built the MNREGA app.

A glitch in an app is one thing. But a glitch in an app that blocks wages for rural workers shows how casually technology is being pushed into livelihoods without care or concern.

Sometimes, what we really need is a little less technology, a little more empathy.

Karen also draws parallels with Europe, where investigative journalist Gabriel Geiger has been reporting on AI in welfare, in her research paper. 

Then there’s bias, which isn’t new. But digitisation amplifies it. As Geiger points out, if the data you build on is skewed, the algorithm will be too.

So, what’s the way forward? Apar Gupta of the Internet Freedom Foundation offers one:

It’s not enough to regulate after the fact. Unless technology becomes a political issue — one we debate, one that influences elections — the consensus in favour of digitisation will stay unquestioned.

Karen ends with a set of clear, practical baselines: consult before rollout, run real pilots, keep analogue backups, publish error and appeal rates, limit how data is used, allow independent audits (even of code), and provide time-bound redress. Simple ideas, but rarely implemented.

You can read her full paper here.

Reading Karen’s work alongside Decode’s own reporting, I keep circling back to the same question: when technology steps in to govern welfare, work, and rights, who is it really serving? And maybe the harder question for us is this: what will it take for technology policy to move out of closed rooms and into our public debates, our political conversations, and even our voting choices?

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