Jonathan Bright 🇺🇦

At the end of January I started a "living document" tracking the impact of AI on productivity. I highlighted a disconnect: while micro studies showed a clear boost, the macro evidence was muted. I wrote that I expected this to change in the near term. Apparently "near term" is a bit over a month. The post has been updated with almost a dozen new studies, on benchmarks, new tasks, etc. Importantly, updates to the aggregate data are also showing what looks like AI productivity gains. It is still early days, but worth noting. See post here: aleximas.substack.com/p/what-is-the-…

bbc.co.uk/news/articles/… kind of depressing that people who work in the public sector and hustle to do a second job as well are treated as "fraudsters".

i follow AI adoption pretty closely, and i have never seen such a yawning inside/outside gap. people in SF are putting multi-agent claudeswarms in charge of their lives, consulting chatbots before every decision, wireheading to a degree only sci-fi writers dared to imagine. people elsewhere are still trying to get approval to use Copilot in Teams, if they're using AI at all. it's possible the early adopter bubble i'm in has always been this intense, but there seems to be a cultural takeoff happening in addition to the technical one. not ideal!

I made a list of forecasts of the impact of AI on economic growth over the next decade. A few observations... (🧵): tecunningham.github.io/posts/2025-10-…

I didn’t start doing physics until I was 33 and now I work on a cutting edge research project at one of the top labs in the world. You can just do things

CEO's question: What will be the hourly cost of work of a humanoid robot? Several projections have been published, e.g. by @CernBasher, @adam_dorr and @GoingBallistic5. Here's my take. I've produced a long-form video on this question (see link in comments). Here is the essence - based on very conservative assumptions (see attached image). - Production cost: $30,000. A humanoid is ~5% the mass of a passenger car. The costly parts are actuators and gearboxes; the rest is electronics, sensors, a few kWh of batteries, and plastics—components that are highly scalable in volume manufacturing. - Operating cost: $30,000 per year, of which $18,000 is human oversight and coordination. This is likely way too high. - Operating time: 6,600 hours per year (330 days × 20 hours/day). That equals the yearly working time of more than three people. - Work speed vs. humans: 100% initially. As with industrial robots, later generations will likely reach 200%+. - Business model: Most manufacturers will offer Robot-as-a-Service (RaaS) rather than selling units, because it drives far higher revenue and margin. Expect an initial one-time fee roughly equal to manufacturing cost plus a usage fee per year, month, day, or hour. - Service life (incl. repairs): 8 years. - Market dynamics: Because humanoids will be highly profitable to use (see below), demand will ramp quickly. But many suppliers will enter, so sustained overly high monopoly pricing is unlikely. Result: Based on these assumptions, a humanoid work hour will cost at most $14. That’s the highest realistic value. With learning effects and scale, the hourly cost will drop below $10 and likely below $5. @rethink_x even projects that by 2035 a humanoid hour could cost less than $1. By comparison, a skilled worker’s fully loaded hour is $42.53. Strategic consequence: In competitive markets, companies will have no real choice: first to replace labor shortages, and soon to replace existing roles. Even at $14/hour, the financial advantage vs. human labor is close to $200,000 per robot per year. I’ve published a three-part video series on the societal implications of this inevitable shift (see comments). Urgent advice: If you make or move anything physical, start rethinking your business around humanoids—as a supplier, service provider, or user. It is quiet now, but the ramp-up will be fast. How about you? Which tasks would you deploy humanoids for first?

London is a better city than it was a decade ago - or, perhaps, at any time. The billionaire exodus drains wealth and tax revenue. But if the below filters down and property becomes more affordable, living in London will be better still.

Hello friends! Wanted to share my reflections on exciting new insights during #ICLR2025. A summary (and links) 🧵 TL,DR: 1. We are on the cusp of long-horizon capabilities paving the way for open-ended automated research, AI personalization, etc. 2. Many necessary pieces are in place (see 👇) 3. But new challenges in evaluation and long-term knowledge management have arisen. 1/N

📈Out today in @PNASNews!📈 In a large pre-registered experiment (n=25,982), we find evidence that scaling the size of LLMs yields sharply diminishing persuasive returns for static political messages.  🧵:

Issue 95 4 out now! With @GavinJKelly1 @jonbloomfield2 @michaelujacobs @DanRCorry @aveek18 @SMFthinktank @aled_r_davies @kiragk2 @innes_abby @g_m_hodgson @stefanie_reher @ProfLizJEvans @HelenMargetts @CosDorobantu @jonmbright @PhMarliere And more... onlinelibrary.wiley.com/toc/1467923x/2…

📰 New Turing survey finds over half of UK doctors using AI are optimistic about its benefits. And that, while a quarter have used some form of AI over the last 12 months, around a third felt they didn't fully AI risk in healthcare: bit.ly/3BSrByX #AiNews #MedTech

I hate doing personal posts but: When my mum was dying last year, NHS data sharing failures and prioritising GDPR over pain relief repeatedly left her in agony. In desperation I began to build a Google Doc of her records linked to a QR code for doctors to scan. System's broken.

Our Systemic AI Safety Fast Grants scheme is open for applications. In partnership with @UKRI_News, we’re working to advance this new area of research, building the resilience of our society and infrastructure to AI-related hazards. Find out more: aisi.gov.uk/work/advancing…

Looking forward to speaking at #Digitech24 today on AI and public services digitech24.co.uk

'How to Build Progressive Public Services with Data Science and Artificial Intelligence' - by @HelenMargetts @CosDorobantu and @jonmbright 10-minute digested of the longer journal article >> #ai #publicpolicy politicalquarterly.org.uk/blog/how-to-bu…

✨ Thu 26 Sep: The first of a three-part lecture series, @turinginst’s Head of Online Safety and AI for Public Services @jonmbright asks ‘Can Democracy Handle AI?’, exploring how political campaigns are using AI and the challenges posed by deepfakes. 🎟️ kingsplace.co.uk/whats-on/words…

📰 No AI impact on UK, French & EU election results New research from the Turing’s CETaS finds a lack of evidence showing AI-enabled #disinformation had a measurable impact on recent UK & EU elections. Concerns about trust in digital content persist. ➡️ bit.ly/4gnObiu

Can #democracy handle #AI? On 26th September Head of Online Safety & AI for Public Services @jonmbright delivers a Turing Lecture exploring AI’s impact on our political world and what it might mean for the future of democracy. Register for your ticket ⬇️turing.ac.uk/events/turing-…

🚀 Want to query LLMs at scale? 🤔 Wish there was a package that could optimise rate/token limits for popular API providers? And could even hook into self-hosted open source models? We’re releasing prompto: a library designed to support reproducible LLM eval experiments.🧪

Great opportunity to work with the @WorldBank on AI in public sector work: docs.google.com/document/d/19W…. Closes 27/09