---
title: "Slides: Shipping Production AI Inside Government — William Tarr, Ministry of Justice"
category: "slides"
video_id: "qlHaO6laBlM"
sourceLabels: ["Public YouTube video frames", "Public YouTube metadata"]
---

# Slides: Shipping Production AI Inside Government — William Tarr, Ministry of Justice

## Source Video
[Shipping Production AI Inside Government — William Tarr, Ministry of Justice](https://www.youtube.com/watch?v=qlHaO6laBlM)

## Relationship To World's Fair 2026
These slides are extracted from a public AI Engineer YouTube video connected to World's Fair 2026. Speaker-matched clips are supporting context unless later confirmed as exact session recordings; official livestream recordings are day-level/event-level source material.

## Related Scheduled Sessions
- No individual scheduled session mapping has been assigned yet; treat this as an event livestream deck.

## Extracted Slides
![[assets/slides/qlHaO6laBlM/slide-002.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/qlHaO6laBlM/slide-002.html)
- AI slide classifier: `content_slide` confidence `0.97`
- Text source: agent_vision.

Slide text:

> About Me
> Now
> • Forward Deployed Engineer in the Justice AI Unit
> • No10 Innovation Fellow – selected from top 0.8% of applicants
> • Joined in November, working mainly across prisons
> Previously
> • Co-Founder @ Tergle (YC W25) – AI for audit automation
> • CS + Math @ Harvard


### Hidden Non-Slide Evidence
- [`slide-001.jpg`](/assets/slides/qlHaO6laBlM/slide-001.jpg) — `speaker_stage` confidence `0.99`; Stage shot with presenters at podium; projected slide is only partially visible and not readable as a standalone slide.
- [`slide-003.jpg`](/assets/slides/qlHaO6laBlM/slide-003.jpg) — `speaker_stage` confidence `0.98`; Stage shot with people walking in front of the screen; projected slide is cropped and not readable as a standalone presentation slide.

Classification audit: `raw/sources/slide-ai-classification/slides/qlHaO6laBlM/audit.json`

## Slide-Derived Subjects To Review
Subject extraction uses video title, related session titles/descriptions, transcript context, and OCR text when available. OCR is best-effort and should be reviewed against the embedded slide images.