
Episode 46: Empowering Democracy with LLMs
About this episode
With all the reports about the spread of misinformation and disinformation on social media, sometimes it feels like one of the biggest threats to democracy is technology. But no technology is inherently good or bad. It’s how you use it that matters. And just as technology has the potential to harm democracy, it also has the potential to enhance it.
In this episode, Vikram Oberoi joins Dr Genevieve Hayes to discuss how he has been using generative AI and large language models (LLMs) to enhance people’s access to NYC council meetings through his work on citymeetings.nyc.
Guest Bio
Vikram Oberoi is a software engineer, fractional CTO and co-owner of Baxter HQ, a boutique early-stage tech product development firm. He also built and operates citymeetings.nyc, an LLM powered tool to make New York City council meetings accessible.
Highlights
- (00:00) Meet Vikram Oberoi
- (01:31) Overview of citymeetings.nyc
- (07:50) Vikram’s journey into local politics
- (12:05) Technical aspects of citymeetings.nyc
- (18:41) Dealing with AI hallucinations
- (25:00) Understanding the different types of AI errors
- (26:05) Case study: Honeycomb’s query feature
- (26:59) Reinforcement learning with human feedback
- (28:32) Choosing between Claude and GPT
- (31:42) The importance of context windows
- (40:31) Effective prompt engineering tips
- (46:11) Final advice for data scientists
Links
- citymeetings.nyc
- Vikram’s website
- Vikram’s talk at NYC School of Data about citymeetings.nyc
- Follow Vikram on X
- Connect with Genevieve on LinkedIn
- Be among the first to hear about the release of each new podcast episode by signing up HERE
Get every episode summarized
Each time Value Driven Data Science: Boost your impact. Earn what you’re worth. Rewrite your career algorithm. publishes, we email you a written briefing from the transcript — the topics, who appeared, and any specific claims, with the ad reads skipped.
Email me new episodesFree for 3 shows. No card needed.
Hosts & guests
No transcript yet
This episode has not been transcribed. Request it and it moves to the front of the queue.
More episodes
More from Value Driven Data Science: Boost your impact. Earn what you’re worth. Rewrite your career algorithm.

Episode 100: What Data Science Value Really Means
Value Driven Data Science: Boost your impact. Earn what you’re worth. Rewrite your career algorithm.

Episode 99: [Value Boost] Preventing ML Bias Before it Becomes a Problem
Value Driven Data Science: Boost your impact. Earn what you’re worth. Rewrite your career algorithm.

Episode 98: Building Trust in AI Through Model Interpretability
Value Driven Data Science: Boost your impact. Earn what you’re worth. Rewrite your career algorithm.

Episode 97: [Value Boost] Mathematical Modelling as a Gateway to ML Success
Value Driven Data Science: Boost your impact. Earn what you’re worth. Rewrite your career algorithm.