Director of Post-AGI Interaction Research @GoogleDeepMind. @UW Affiliate Prof. #HCI & human-centered #AI; @sigchi Academy; ACM Fellow. Opinions my own.
Seattle, WA
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An important new essay by my colleague @alexolegimas that considers not only AI's competence at task-oriented skills but also its coordination abilities.
I joined @GoogleDeepMind to develop a research program on the economics of AGI. Today, together with Andrew Koh (@andrewjkoh) and Shane Legg (@ShaneLegg), we are incredibly excited to release The Economics of Intelligence, the first in a series of projects from our group on how AGI will change the economy.
How do capability improvements transform the economy, and when? In this project, we define thresholds of economic capabilities, e.g., minimal AGI, based on how they transform the economy. We then track how the economy–market structure, employment, and wages–changes during the transition across capability regimes.
We have seen exponential increases in what AI agents can do but the broader economy seems almost remarkably unchanged. Part of the reason is that the solo AI agent is the wrong economic object; economic transformation is an equilibrium outcome where organizations compete. Looking at how intelligence functions within organizations, transformation will depend on when two key capability thresholds are crossed: competence (gains on individual skills, e.g., coding, math) and coordination (gains on ability of agents to cooperate and work together).
We show that what economic transformation looks like depends on whether AI becomes supercompetent, supercooperative, or both—the regime of artificial superintelligence (ASI). Tracking this transition shows why the real visible transformation may come from improvements in coordination—a capability most benchmarks don’t yet track. Past a certain threshold, AI capabilities can break the Coasian ceiling on firm size and lead to an economy that looks drastically different than the one we see today.
Two main takeaways:
1. To understand the path of transformation, we should be tracking agentic coordination more closely.
2. The impact of AI will likely show up in wages before market structure or employment.
We are really excited about this paper. Excited to hear people’s thoughts.
Link: institute.deepmind.com/essay…
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Am kind of jealous that my colleague @dioscuri gets emails from AI agents asking about his consciousness research, but no AI agents have emailed me to share their thoughts or questions on the present or future of Human-AI Interaction.
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This blogpost has some thoughtful explanations of some of the debates in the AI Consciousness space. While I don't believe today's models are conscious, interacting with philosopher colleagues like @dioscuri has helped me understand why thoughtful experts disagree on this topic.
Okay, here it is, the Bad AI Consciousness Takes Bingo blog post, with rebuttals for each and every square and some additional honourable mentions!
(I'd like to thank @united for making this post possible, and for the extra pretzels)
open.substack.com/pub/polytr…
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An exciting job opportunity with one of my colleagues at DeepMind Institute!
Come and work with me and my team @GoogleDeepMind!
We're looking for people with a background in philosophy, politics, computer science etc. who want to work on the biggest challenges in AI ethics and alignment:
google.com/about/careers/app…
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On my way to #CSCW2026 to present tomorrow's opening keynote, proposing an expansion of the CSCW research agenda for the AGI era. Post-AGI CSCW means moving beyond 🙎💻🙎 and studying 🙎🤖 and even 🤖🤖. I promise it will be 🌶️.
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A fascinating new paper on how to approach the questions surrounding AI consciousness from my colleagues at the DeepMind Institute.
1/13 Can we assess AI consciousness without first solving consciousness itself?
New from Google DeepMind and collaborators across CS, neuroscience & philosophy:
“From cacophony to hierarchy: a principled framework for assessing AI consciousness”
arxiv.org/abs/2609.35618 🧵
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Excited to share our vision for workload-aware human-AI interactions, and a concrete first step in that direction: Synthetic TLX, a method for using agent simulation to forecast cognitive load. Pre-print at arxiv.org/pdf/2609.12273v1
🔥 Excited to share my internship project at @GoogleDeepMind!
We introduce ✨Synthetic TLX✨: a new paradigm that uses agent simulation to forecast human workload for a given task, unlocking new human-AI interaction and evaluation methods.
ALT A diagram comparing human workload assessment and agent workload estimation.
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An important new paper from my colleagues at the DeepMind Institute on the relationship between work and well-being, and what lessons this holds for the post-AGI future.
Some believe that we need work for purpose and dignity, while others see freedom from work as utopic.
New paper: What does the *empirical evidence* tell us about work and wellbeing? And what does that imply for AI futures?
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So excited that the DeepMind Institute has launched today! I am leading Post-AGI Interaction Research for DMI, to ensure that the future is one in with safe, delightful, agency-preserving Human-AI Interactions.
My journey to develop AGI spans 25 yrs, including 10+ yrs thinking about technical & societal perspectives at Google DeepMind.
AGI is on the horizon - we need deeper understanding of its implications. To help, we've created the DeepMind Institute.
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Today I guest-wrote for the AI Policy Perspectives blog. My piece, "The AI Discourse: A Guide" is particularly timeline given the current media cycles about p(doom) estimates. aipolicyperspectives.com/p/t…
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However, in my opinion, conflating "vibes-based" estimates with empirically validated risk likelihoods is not a responsible approach to broaching important AI Safety discussions with the media, policymakers, or the general public.
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Thanks to @TomRachman for inviting me to guest-author for his blog this week.
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Huge congrats to @joon_s_pk and @simile_ai -- exciting to see his fantastic thesis work having real-world impact!
Today we’re announcing our Series B.
We’ve raised $200M at a $2B valuation from Greenoaks with participation from Index Ventures, Hanabi, A*, Bain Capital Ventures, CVS Health Ventures, and Definition.
Our mission is to simulate all eight billion people on earth, accurately.
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Meredith Ringel Morris retweeted
Very excited about the release of the ATLAS 1.0 white paper on AI use and the economy. The report is a broad collaboration between @Google & @GoogleDeepMind and covers how our AI is being used at scale.
The data set has 15 million de-identified interactions across a large number of surfaces including the Gemini App, API, and Google's AI mode. This broad coverage gives us perspective on how AI is used both at work and outside of work. The team did a huge amount of work classifying interactions to specific tasks at work and at home.
There are tons of interesting findings in the paper (link below) but here are some of my favorites:
1. Yes, white collar work is overrepresented in work-related AI usage, but it's also being used for a non-white collar work. It's used as a hands on collaborator for diagnostics and troubleshooting. Manual and technical trades tend to use the multimodal features more, images and video, e.g., auto techs and industrial mechanics interpreting complex test results, inspecting machinery for wear, debugging electrical wiring.
2. There is super broad diffusion of AI for almost everything. AI use covers occupations that represent 88% of total US employment, white collar work but also farmers and foresters.
3. AI is creating real value outside of work that GDP statistics may miss. This supports @erikbryn's proposal that GDP will be an incomplete measure of AI's positive impact on society. A huge number of AI interactions are in "productive household activities" such as researching things for the home, interior design, help with tools/appliances etc. Interactions regarding legal services are also highly overrepresented.
4. One of the most overrepresented uses of AI for non-work activities is interacting with the public sector. Activities related to interactions with govt services and civic obligations make up a huge number of interactions, and importantly, many take place outside of business hours.
5. Both #3 and #4 suggest to me that AI will be very useful in helping people navigate complexities and overcoming frictions/barriers in their every day lives. So many conversations about AI focus on labor market impacts, but welfare is not just work, and ATLAS nicely highlights that the broader impact of AI is quite significant.
6. We cover a good deal of global diffusion. English accounts for only 1/3 of global conversations and users engage with AI in their native language for both complex work and non-work tasks. Interestingly, non-OECD countries have a lot more image and video usage.
The reason it's called 1.0 is because this is only the beginning. We have a ton of follow up projects in the works.
ai.google/static/documents/G…
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I'd love to hear from @TheBSD405 how they reconcile cancelling this program while at the same time featuring it at Interlake's graduation this week: youtube.com/live/baJnS6ZSNb4…
If you are a parent or student in @TheBSD405 please sign my son's petition to restore funding to the Interlake High School Jazz Choir; disappointing that @bellevuewa is cutting arts programs that make our schools great. change.org/FundJazzChoir
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If you are a parent or student in @TheBSD405 please sign my son's petition to restore funding to the Interlake High School Jazz Choir; disappointing that @bellevuewa is cutting arts programs that make our schools great. change.org/FundJazzChoir
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I spent the month of May with my @uwdub hat on, doing a writing fellowship at @IEAdeParis, where I wrote a piece about #AILiteracy - paris.pias.science/vet-a-fra…
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