Ram 🔸

My goal is to do work that counterfactually reduces AI risk from loss-of-control scenarios. My perspective is shaped by my experience as the founder of a VC-backed AI startup, which gave me a firsthand understanding of the urgent need for safety.

I have a B.S. in Artificial Intelligence from Carnegie Mellon and am currently a CBAI Fellow at MIT/​Harvard. My primary project is ForecastLabs, where I’m building predictive maps of the AI landscape to improve strategic foresight.

I subscribe to Crocker’s Rules and am especially interested to hear unsolicited constructive criticism. http://​​sl4.org/​​crocker.html—inspired by Daniel Kokotajlo.

(xkcd meme)

Case Study: An AI-Pow­ered Ou­trage Mon­i­tor for An­i­mal Ad­vo­cacy Built in 6 Hours

• Ram 🔸 30 May 2025 0:31 UTC

  11 points

  4 ∶ 0

  on: The myth of AI “warn­ing shots” as cavalry

  This is a very well thought out post and thank you for posting it. We cannot depend on warning shots and a mindset where we believe people will “wake up” due to warning shots is unproductive and misguided.

  I believe to spread awareness, we need more work that does the following:

  1. Continue to package existing demos of warning shots into a story that people can understand, re-shaping their world view on the risks of AI

  2. Communicate these packages to stakeholders

  3. Find more convincing demos of warning shots

  Our base are people who have their own understanding of the issue that motivates them to act or hold their position in the Overton window. They are the people who we bring to our side through hard, grind-y conversations, by clipboarding and petitioning, by engaging volunteers, by forging institutional relationships, by enduring the trolls who reply to your op-ed, by being willing to look weird to your family and friends…

  This cannot be overstated, lets put in the work to make this happen, ensuring that our understanding of AI risk is built from first principles so we are resilient to negative feedback!