At Dasra, our commitment to advancing equity has fundamentally shaped how we approach the integration of data and AI within collaborative systems. Responsible innovation is not just about the technology—it begins with who’s at the design table. Recognizing the larger algorithmic biases, data sets that underrepresent the most vulnerable communities, and tools that are built without accounting for contextual inequities that sectorally persist, here’s how we can flip the narrative:
Start from a place of proximity: Meet communities where they are and build with them, not for them. Thought leadership pieces such as Byte By Byte: Following the Strides in Data-driven Innovation at India’s Grassroots are a helpful resource, or Buffering Now, to help identify key levers and lessons for harnessing technology for sustainable good.
Build in public: As ecosystem builders, we have the opportunity to engage communities impacted by the use of data and AI to define its guardrails. We did this by integrating an AI-powered language translation platform into our tools like Glific, extending the reach and access of information to regional communities. Our iterative approach to testing developed technology platforms with those it’s aimed at benefiting, such as youth leaders, gender experts, and non-profit practitioners, ensures those most impacted by these tools are defining its guardrails.
Stay agile: With the ever-changing data, technology, and AI landscape, we acknowledge that this work cannot be done in silos. Lean on the experts. In our case, we turned to our non-profit partners who specialise in online safety, digital equity, and AI ethics to ensure we’re building ecosystems that are safe, context-aware, and future-ready.
Bridge data gaps responsibly: To enable level playing fields, bridge the data maturity gap and data ethics gap through consent-first data sourcing, anonymization protocols, and full transparency. We’ve catalyzed ecosystem capacity through fractional CXO placements and our bespoke data-upskilling programs, such as D4GX for democratizing access to responsible AI practices.
Lastly, this journey is not a one‑time effort—it’s a practice of trust, accountability, and power‑shifting.