Dr Keshav Malhotra's great-grandfather started practising medicine in India. Four generations later, Keshav is sitting at the intersection of embryology and artificial intelligence, chairing the embryology wing of the Indian Society of Assisted Reproduction and working with the Alpha Scientists board to push reproductive science forward globally.

In this episode, we trace that lineage, not just as a family story but as a lens on how medicine evolves. Each generation inherited the questions the last one couldn't answer. Now, the question on the table is this: what happens when AI enters the fertility clinic?

We get into the real stuff. Time-lapse systems grading embryos while clinicians sleep. Digital chatbots triaging patients before they ever see a specialist. The genuine promise of making IVF faster, smarter, and more accessible, particularly in regions where reproductive healthcare is stretched thin.

But we also get honest about the gaps. Most patients going through IVF have no idea an algorithm played a role in their treatment. The datasets powering these tools skew heavily towards European and American populations. And the conversation around informed consent in AI-assisted fertility is still catching up with the technology itself.

If you work in health, tech, policy, or you've ever navigated the fertility system yourself, this one matters.

Turning the Tables: Normalcy Bias and the Case for Context traces the arc from Youth Parliament at 11, to teaching herself to code on Tumblr, through finance jobs and several countries, to the moment that set Dawn Intelligence in motion. It's an origin episode, but it's also an argument. Normalcy bias is quietly shaping how institutions respond to gender-based violence, and Leah makes the case that the data to see patterns earlier is already sitting in public, it just isn't being read in context.

Expect honest talk about founder life, mental health, and the ethics line Dawn refuses to cross. No individual risk scores. No surveillance. No reducing people to rows.

New episodes of AI for Equity weekly, hosted by Leah Garrett and Jenny Garrett OBE.

What does education look like when there are no schools and no teachers?

In this episode, we speak to Chandrima, a physicist who earned their PhD at Cambridge and held positions at Dartmouth and Harvard before making a radical career shift. During the pandemic, they stepped back from academia and into community organising, eventually founding DARS, an AI assisted tutoring platform designed for marginalised learners in West Bengal, India.

DARS operates at just 10 cents per student per month, runs on basic smartphones with limited connectivity, and is built around a peer mentoring model where every learner is also a teacher. It's not just an EdTech product. It's a community driven approach to closing an education gap that policy alone hasn't solved.

In this conversation we explore Chandrima's journey from research to real world impact, the disconnect between scientists and the communities they aim to serve, why gender justice and education are inseparable, and what it takes to build responsible AI for people who are usually excluded from the conversation entirely.

If you care about AI, education, equity or community led change, this one's for you.

Follow AI for Equity on LinkedIn, Instagram and Spotify.