socialchange –

Does Instagram really have 3B monthly active users? What about ChatGPT and Claude?

Gavin — Wed, 05 Aug 2026 19:47:15 +0000

No. Not in my opinion. Not if you mean unique humans.

Divide by at least two (2) on everything you see.

Instagram

This post came from a dinner conversation about the number of followers of certain celebrities, and how having “600M followers” doesn’t really mean what anyone thinks it means.

3B is, approximately the TAM (total addressable market) = the total number of people *able* to use instagram. It’s a pretty impressive number in its own right (nb. instagram is blocked in China and Russia).

However, in normal internet service modelling, I usually start with a divide by ten on any conversion rates, but I suspect Instagram might do a bit better. After running a few different ideas through Claude, I settled on the analysis below as being ‘not unreasonable, and it indicates dividing by at least by two. Personally I’d divide by at least four. That means about half of all the people you meet on the streets of the ‘gram are fake or duplicates. Imagine if that was a real street, how would you feel? (and how might you feel when half the streets are actual robots?)

So, Insta, it’s maybe a billion. Maybe. It’s still a gigantic number, but as we career towards more and more “taking over the world” stats, I think it’s rather important that we remember that there are lies, damn lies, and statistics. And investors who like to see graphs that go up.

And, please do remember, nearly half of our world’s population lives on less than $8.30 a day [Our World in Data].

prompt
instagram claims to have 3B monthly active users. how can this be the case? what % of them are fake or duplicates? Take an approach that includes 1. age demographics 2. access to tech, energy, money 3. poverty 4. access restrictions

[source: Claude Opus 4.7, 2026-08-05]

Let me do a bottom-up Fermi check to see what physical ceiling actually constrains the number.

Starting point

World population is roughly 8.3 billion in 2026, with a median age of 31.1 years.

Filter 1: Age

Instagram’s terms require 13+, and realistic active use skews even older. Globally, 24.7% of the population is under 15, and roughly 21% is under 13. That removes about 1.8B people immediately, leaving ~6.5B. Engagement then drops sharply above age 60, and the 10% of the world over 65 (~830M) is largely absent from Instagram in practice, though we won’t fully exclude them.

Filter 2: Geography where Instagram is blocked

Instagram is fully blocked in China, Vietnam, North Korea, and Turkey, plus Russia (banned March 2022) and Iran (restricted September 2022), along with Turkmenistan and periodic shutdowns in Bangladesh, Myanmar, and Uganda. The population arithmetic:

China: ~1.41B
Russia: ~144M
Iran: ~89M
Turkey: ~86M (though workaround use is heavy)
Vietnam: ~100M (restricted, workarounds common)
North Korea, Turkmenistan, Myanmar (partial): ~90M combined

That is roughly 1.9B people in fully or heavily blocked jurisdictions. Backing out under-13s, about 1.5B eligible humans are geographically cut off. VPN circumvention exists but represents a small percentage in each of these markets.

After age and geography: 6.5B minus 1.5B = ~5.0B potentially eligible humans.

Filter 3: Internet access

6.12 billion people used the internet at the start of April 2026, equivalent to 73.8% of the world’s total population. Removing internet users inside blocked countries (China alone accounts for over 1.1B), the addressable internet-connected pool drops to roughly 4.5B, of which ~4.0B are 13+.

Filter 4: Smartphones

Instagram is effectively a smartphone product. There are approximately 5.6 billion smartphone users globally, representing 68% of the world population. Subtracting China’s 1.05B smartphones plus other blocked markets leaves ~4.3B addressable smartphone users. Filtering for 13+, we get ~3.7B.

Filter 5: Poverty and energy access

In 2025, an estimated 831 million people were living in extreme poverty, each trying to survive on less than $3 per day. Broader poverty is far larger: at the $8.30 per person per day poverty line, an estimated 3.7 billion people lived in poverty in 2025. The extremely poor overwhelmingly lack a personal smartphone, reliable electricity, or affordable mobile data. Roughly 700M people worldwide lack any electricity access, concentrated in Sub-Saharan Africa and South Asia. Even at the moderate poverty line, device sharing within households is common. Trim another 400-600M as effectively device-less or too data-constrained for a photo/video platform.

Realistic ceiling of unique living humans who could plausibly use Instagram: roughly 2.8 to 3.2 billion.

Now the competitive constraint

This same ceiling applies to every other global platform. TikTok hit 2B MAUs in 2026, YouTube reports ~2.7B, Facebook 3.07B, WhatsApp 3.0B. Not everyone in the eligible pool picks Instagram. Many prefer TikTok, use WhatsApp only, or belong to regional ecosystems (Line in Japan, KakaoTalk in Korea, WeChat among Chinese diaspora). Realistically, unique-human Instagram users cannot exceed roughly 2.0 to 2.3B without implying near-saturation of the addressable market and near-total overlap with every competitor.

The reveal: Meta’s own numbers contradict the 3B

DataReportal reports that Instagram’s advertising tools reach 1.99 billion users worldwide. Ad reach is not the same as monthly active users. It counts the accounts marketers can target, which is why it sits below the 3 billion figure. That 1.99B is Meta’s own de-duplicated, best-attributable measure of humans it can identify well enough to sell against.

Gap between headline and ad reach: 3.0B minus 1.99B = ~1.01B accounts.

Estimated breakdown of the 3B

Working from the constraints above, a defensible split:

Real, unique, actively engaged humans: ~1.7 to 2.0B
Legitimate secondary accounts held by real humans (finsta, business, meme page, pet, alt): ~500-700M
Bots and fake accounts (aligns with the widely cited 9% to 15% of all Instagram accounts): ~270-450M
Dormant or marginal accounts that log in occasionally without meaningful activity: ~200-400M

Bottom line on the fake/duplicate question

Roughly 33% to 40% of the headline 3B does not represent a distinct, actively engaged human. Break that down: about 10% are outright bots or fakes, about 20-25% are duplicate accounts held by real people, and the rest is dormant. Meta is not fabricating the MAU number under its own definition, but MAU counts logged-in accounts, not people. The 1.99B ad-reach figure is closer to reality, and even that is likely optimistic once you strip out bots Meta can’t detect and duplicates it can’t collapse.

Your instinct is correct. The physical ceiling of humans who could use Instagram sits close to the claimed number, which is itself the tell. A platform claiming saturation of nearly every eligible person on Earth in a competitive market is almost certainly counting the same people multiple times.

[end of source: Claude Opus 4.7, 2026-08-05]

ChatGPT & Claude?

prompt
apply this thinking to the other big claims from openAI and Claude as to their MAUs

[source: Claude Opus 4.7, 2026-08-05]

The claims

ChatGPT reached 900 million weekly active users in February 2026, more than doubling its 400 million weekly user base from exactly one year earlier. 900 million weekly active users confirmed by OpenAI on Feb 27, 2026, with Reuters reporting in June 2026 that ChatGPT had reached 1 billion monthly active users, making it the fastest app in history to reach that level of scale. Also relevant: Over 2 billion daily queries are processed on ChatGPT (some sources say 2.5B).

Claude’s numbers are less consistent, and that inconsistency is itself the finding:

Claude AI now has over 245 million monthly active users across the web and the mobile app (Sensor Tower via Statista).
18.9 million monthly active users on the web, with additional millions using its mobile apps (getpanto direct measurement).
AICPB ranked the Claude app at 12.48 million MAU in February 2026, plus Similarweb estimated 952.6 million monthly visits to claude.ai in May 2026.

Two versions of Claude circulate: ~245M (Sensor Tower’s headline) and ~30M (~19M web + ~12M mobile from direct analytics). That is an 8x gap in the same product’s own MAU. Hold that thought.

Applying the same filters

World population 8.3B → subtract under-13s (~1.8B) → subtract blocked geographies. AI chatbots share Instagram’s geography problem and add to it. ChatGPT is blocked or restricted in China, Russia, Iran, North Korea, Cuba, Belarus, Venezuela, and Syria. Claude has an even narrower rollout, historically unavailable across large swaths of Asia, Africa, and the Middle East, and only expanded broadly through 2024-2025. Roughly 1.6-1.8B people are in blocked or effectively-blocked jurisdictions.

Internet access: 6.12B globally, minus roughly 1.2B inside blocked markets, leaves ~4.9B addressable internet users. Smartphone/PC ownership trims another chunk, poverty trims more. Physical ceiling before AI-specific filters: ~3.0-3.5B eligible humans.

AI-specific filters that don’t apply to Instagram

This is where AI chatbots hit constraints Instagram doesn’t:

Literacy and language. Global adult literacy is ~86%, but functional literacy (able to compose a coherent prompt) is lower, especially in languages ChatGPT and Claude handle well. Both models perform strongest in English, decently in ~20 major languages, and poorly in most of the world’s ~7,000 languages. Cut ~30-40% of the addressable population who cannot fluently prompt in a supported language.
Task need. Instagram is passive entertainment. AI chatbots require an active reason to use them: work, school, coding, writing, research. Retirees, manual laborers, subsistence farmers, and much of the informal economy have limited use cases. This trims another large fraction.
Learning curve and habit formation. Adoption skews heavily toward students, knowledge workers, and technical professionals. The over-55 cohort, which is a meaningful part of the internet population, uses AI chatbots at a small fraction of the rate of 18-34 year olds.

Post-adjustment addressable population for AI chatbots: roughly 1.5 to 2.2B unique humans worldwide.

Testing ChatGPT’s 900M WAU / 1B MAU against this ceiling

If ChatGPT truly has 1B unique-human MAU, that is 45-65% penetration of the entire physically- and functionally-eligible AI-user population. In three years. Against active competitors (Gemini, Claude, Copilot, DeepSeek, Perplexity, Meta AI, plus regional models in China and elsewhere). With a product that requires active prompting rather than passive scrolling.

That is aggressive but not impossible, because ChatGPT genuinely is the dominant consumer AI product (ChatGPT held 80.49% of the worldwide AI chatbot market in January 2026) and has become a browser-like utility. The Sensor Tower 1B MAU figure counts the mobile app specifically, per Reuters; web adds more but with heavy duplication.

The realistic composition of ChatGPT’s 1B MAU / 900M WAU:

Unique, actively engaged humans: ~500-650M
Legitimate duplicate accounts (personal + work Google logins, throwaway accounts): ~150-250M
Extremely marginal users (touched ChatGPT once or twice in the week/month via a Google embed, an app link, an integration, or a curious click): ~200-300M
Automated queries, scrapers, and bots counted as sessions: ~50-100M
API pass-through from other products (some counting methodologies fold these in): variable

Estimated fake/duplicate/marginal share of the 1B: 35% to 50%. The bot component is probably smaller than Instagram’s (chatbots have less incentive for follower-fraud bots) but the “marginal engagement counted as active” component is larger, because a WAU counts anyone who touched the product once in seven days.

Testing Claude’s numbers

Here the story is different, and I should be transparent: I am Claude, and I’ll apply the same skepticism.

The 18.9 million monthly active users on the web figure is internally consistent with the traffic data. 952.6M monthly visits at claude.ai divided by ~50 visits per active user per month = ~19M active web users. Add ~12M mobile MAU per AICPB, minus overlap (users who use both), and consumer MAU is probably in the 25 to 35 million range.

The 245M MAU figure from Sensor Tower is doing something different. It appears to include:

API-driven usage counted through third-party surfaces (Claude in Cursor, Windsurf, GitHub Copilot integrations, Perplexity, Slack, etc.)
Claude Code developer sessions
Enterprise deployments where end users hit Claude through custom interfaces
Panel-based extrapolation from Sensor Tower’s proprietary sample, which tends to over-count in fast-growing categories

“Total reach” versus “consumer MAU” is a real distinction, and both can be defensible depending on definition, but the 245M number is being used in press coverage as if it were comparable to ChatGPT’s MAU. It isn’t. ChatGPT’s 1B is app-store MAU for a consumer product; Claude’s 245M is a broader ecosystem reach estimate that folds in API-mediated usage.

For a fair comparison, the numbers are approximately:

ChatGPT consumer MAU: ~1B (with 35-50% marginal/duplicate/bot per above)
Claude consumer MAU: ~25-35M
Claude ecosystem reach including API-mediated usage: ~150-250M (harder to verify, Sensor Tower’s number is at the top of this range)

Ratio of real consumer users, ChatGPT to Claude: roughly 30 to 1, which matches the traffic share data (ChatGPT dominates the AI chatbot market with 46.4%, Claude ~8-10%) more accurately than a 4-to-1 ratio would.

Bottom line across all three

Same pattern each time:

Instagram: 3B claimed, ~1.8-2.1B real unique humans, 30-40% inflation from bots and duplicates.
ChatGPT: 900M WAU / 1B MAU, ~500-650M real unique humans, 35-50% inflation from marginal engagement, duplicates, and integration counting.
Claude: 245M sometimes cited, ~25-35M consumer MAU, with the gap explained by folding API-mediated and ecosystem usage into a “reach” number that gets presented as MAU.

The mechanism is always the same. MAU is a permissive definition. Every platform picks the most generous defensible number and lets journalists and investors treat it as unique humans. The tighter measurement (ad-reach for Instagram, direct traffic analytics for Claude, DAU-to-MAU ratios for ChatGPT) always reveals a substantially smaller real population.

For Claude specifically, the honest number is closer to tens of millions of consumer users, not hundreds. Anyone quoting the 245M figure should specify it as ecosystem reach including API-mediated third-party surfaces, not comparable to ChatGPT’s app MAU.

Citations [nb: also via Claude. Note source caveats below]

Instagram user counts

Social Media Today, “Instagram Reaches 3B Users, Launches New UI” (Sept 24, 2025) — https://www.socialmediatoday.com/news/instagram-reaches-3-billion-users-ui-update/761038
Upgrow, “Instagram Statistics 2026” (July 2026) — https://www.upgrow.com/blog/instagram-statistics-2026-users-trends
ICUC Social, “15 Instagram Statistics and Trends in 2026” (May 2026) — https://www.icuc.social/resources/blog/instagram-statistics
Neal Schaffer, “Instagram Statistics for 2026” (2026) — https://nealschaffer.com/instagram-statistics
Quantumrun, “Instagram Users Trends And Statistics 2026” (April 2026) — https://www.quantumrun.com/consulting/instagram-users
TechnologyChecker.io, “Instagram User Statistics 2026” (July 2026) — https://technologychecker.io/blog/instagram-user-statistics
DataRefs, “How Many People Use Instagram in 2026” (June 2026) — https://www.datarefs.com/statistics/social-media/instagram-users
GetAFollower, “Instagram User Statistics 2026” (March 2026) — https://www.getafollower.com/blog/instagram-user-statistics

Instagram bots and fake accounts

Marketing Dive, “Instagram may have 95M bot accounts” (2018 baseline study) — https://www.marketingdive.com/news/instagram-may-have-95m-bot-accounts-the-information-reports/528141
Insvii, “How to Spot a Bot Instagram Account” (January 2026) — https://insvii.com/spot-bot-instagram-account-engagement-metrics-2026
Basic Thinking, “95 Million Bots: One in Ten Instagram Accounts Is Fake” — https://www.basicthinking.com/bots-instagram-accounts-fake
Collabstr, “Free Instagram Fake Follower Checker” — https://collabstr.com/instagram-fake-follower-checker
Lunio, “How to stop fake Instagram accounts engaging with your ads” — https://www.lunio.ai/blog/fake-instagram-accounts

Instagram country bans

Newsweek, “Map Shows Countries Where Instagram Is Blocked” (Aug 2024) — https://www.newsweek.com/map-shows-countries-where-instagram-blocked-1942415
Digital Journal, “China has banned the highest number of social media platforms worldwide” (Oct 2025) — https://digitaljournal.com/social-media/china-has-banned-the-highest-number-of-social-media-platforms-worldwide/article
Lantern, “Access Instagram with Lantern” — https://lantern.io/en/unblock/instagram
Texting.io, “Most Blocked Words on Instagram in Every Country” (Aug 2025) — https://texting.io/most-blocked-words-on-instagram-in-every-country

World population and demographics

Worldometer, “World Demographics 2026” — https://www.worldometers.info/demographics/world-demographics
Wikipedia, “Demographics of the world” — https://en.wikipedia.org/wiki/Demographics_of_the_world
World Bank via Trading Economics, “Population Ages 0-14 (% of Total)” — https://tradingeconomics.com/world/population-ages-0-14-percent-of-total-wb-data.html
Statista, “World population by age and region” — https://www.statista.com/statistics/265759/world-population-by-age-and-region
World Population Review, “Children in the World by Country 2026” — https://worldpopulationreview.com/country-rankings/children-in-the-world-by-country

Internet, smartphone, and mobile access

DataReportal, “Digital Around the World” (April 2026) — https://datareportal.com/global-digital-overview
BroadbandSearch, “Global Internet Stats 2026” — https://www.broadbandsearch.net/blog/internet-statistics
HomeFi, “20 Internet Access Statistics for 2026” (March 2026) — https://homefi.info/blogs/homefi-blog/internet-access-statistics
Countly, “Smartphone Users by Country 2026” (June 2026) — https://countly.net/smartphone-users-by-country-2026-top-10-global-penetration
BacktoFrontShow, “Mobile Phone Usage Statistics Worldwide (2026)” (May 2026) — https://backtofrontshow.com/mobile-phone-usage-statistics-worldwide
XtendedView, “Mobile Device Usage Statistics 2026” — https://xtendedview.com/mobile-device-usage-statistics
ElectroIQ, “Internet Statistics and Facts 2026” (June 2026) — https://electroiq.com/stats/internet-statistics

Global poverty

World Bank, “June 2025 Update to Global Poverty Lines” — https://www.worldbank.org/en/news/factsheet/2025/06/05/june-2025-update-to-global-poverty-lines
World Bank Blogs, “September 2025 global poverty update” — https://blogs.worldbank.org/en/opendata/september-2025-global-poverty-update-from-the-world-bank–new-da
World Bank Blogs, “June 2025 global poverty update” — https://blogs.worldbank.org/en/opendata/june-2025-global-poverty-update-from-the-world-bank–2021-ppps-a
World Bank, “Poverty Overview” — https://www.worldbank.org/en/topic/poverty/overview
UN, “Extreme poverty persists” (SDG Goal 1, 2025) — https://unstats.un.org/sdgs/report/2025/goal-01
Our World in Data, “$3 a day: A new poverty line” — https://ourworldindata.org/new-international-poverty-line-3-dollars-per-day
Libertify, “Global Poverty 2025: World Bank Inequality Update” — https://www.libertify.com/interactive-library/global-poverty-inequality-world-bank-update-2025

ChatGPT / OpenAI user counts

TechCrunch, “ChatGPT reaches 900M weekly active users” (Feb 27, 2026) — https://techcrunch.com/2026/02/27/chatgpt-reaches-900m-weekly-active-users
Omnibound, “ChatGPT User Statistics 2025-26” (June 2026) — https://www.omnibound.ai/blog/chatgpt-user-statistics
Panto, “ChatGPT Statistics 2026” (June 2026) — https://www.getpanto.ai/blog/chatgpt-statistics
DemandSage, “ChatGPT Statistics (August 2026)” — https://www.demandsage.com/chatgpt-statistics/
Nerdynav, “Latest ChatGPT Statistics: 900M+ Users, Revenue (Aug 2026)” — https://nerdynav.com/chatgpt-statistics
FatJoe, “ChatGPT Stats July 2026” — https://fatjoe.com/blog/chatgpt-stats
Digital Elevator, “35 ChatGPT User Statistics for 2026” — https://thedigitalelevator.com/blog/chatgpt-statistics
TechnologyChecker.io, “ChatGPT Statistics 2026” (August 2026) — https://technologychecker.io/blog/chatgpt-statistics
Instant Press, “AI & ChatGPT Statistics for 2026” — https://www.instantpress.co/ai-statistics

Claude / Anthropic user counts

Statista, “Claude: global monthly active users 2026” (June 2026) — https://www.statista.com/statistics/1659723/global-monthly-claude-users
DemandSage, “Claude AI Statistics (2026)” — https://www.demandsage.com/claude-ai-statistics
Panto, “Claude AI Statistics 2026” — https://www.getpanto.ai/blog/claude-ai-statistics
Panto, “Anthropic AI Statistics 2026” — https://www.getpanto.ai/blog/anthropic-ai-statistics
DataRefs, “Claude Statistics 2026” (May 2026) — https://www.datarefs.com/statistics/ai/claude-statistics
AI Business Weekly, “Claude AI Statistics 2026: $47B ARR, 245M Users” — https://aibusinessweekly.net/p/claude-ai-statistics
AI Business Weekly, “Anthropic Statistics 2026” — https://aibusinessweekly.net/p/anthropic-statistics
SerpSculpt, “Claude Code Usage Statistics 2026” — https://serpsculpt.com/claude-code-usage-statistics

NB: Caveats on the sources

Most of these are SEO-optimized statistics aggregators (DemandSage, Panto, Nerdynav, DataRefs, etc.) that recycle each other’s numbers and cite the same original press releases and reports. The primary sources sitting behind them are: Meta’s press releases and Q4 earnings for Instagram, OpenAI’s blog posts and press releases for ChatGPT, Anthropic’s Series G/H press releases for Claude, DataReportal’s Digital 2026 report, the World Bank’s Poverty and Inequality Platform, Sensor Tower for app MAU estimates, Similarweb for web traffic, and Statcounter for market share. When possible, cite the primary source directly. The aggregator numbers are convenient but often lag or misinterpret the originals.

[end of source: Claude Opus 4.7, 2026-08-05]

Introducing cl8; connecting constellations

Gavin — Tue, 12 May 2026 08:08:33 +0000

Hi friends, what have you all been learning?

Many years ago (as captured in my 2017 Thread), I was trying to work out not just what everyone in my fascinating networks of friends, peers and collaborators were doing, but what knowledge they’d gathered.

When you know people over years and decades, it’s easy to lose track of what everyone has learned, what they are interested in, and what unexpected collaborations might exist as a result.

I’m often approached as someone who ‘probably knows someone who does that‘ and wanted to work out how to do that better, and to get out of the way far faster.

I wondered how to better encourage serendipity: part of this was to hold salon-like evenings on M/S Hans to bring dozens of people together in-person and see what just happened. The energy from those events got me thinking about tools that could support everyone in those quite random settings, without creating yet another social network or yet another thing that got in the way more than it helped.

If you’re reading this, it’s likely you already know me, so please feel free to sign up here (and note that the approval process is manual, so it won’t be instant).

Let’s connect on our skills and interests and have fun

The same challenge applies to most networking events, socials, and conferences—there’s a plethora of ‘conference apps’ that are every bit as awful as you’d imagine (Whova, Hopin, Brella et al). But how to connect communities who have ideas, collaboration and work to do together? You might remember someone who you met at an event, half-remember their organisation, might want make an introduction and you can’t quite pull the thread, and everyone’s overwhelmed with social media connections.

For example, in work settings, the usual solution is LinkedIn. However, the usual problem with LinkedIn is that it’s LinkedIn: optimised for broadcasting and monetisation not belonging, and your data is theirs the moment you post it. Most people I know who use LinkedIn to connect after a business event just use its messaging function to get to an email address and then stop using it for that. So, there’s a signal!

To start, how about we do less? (but with more fun)

cl8 is a really small thing: a directory.

I grew up in a village of about 700 people – after a while you’d kind of just know everyone’s phone number, and have a sense of what they did. And, if you rewind a few decades, the person who would definitely know that was…the local telephone operator. One of the last telephone operators was a family friend (thank you Margie Knox), and she knew everyone, everything (and more) about everyone, including how they all connected with each other.

So, can we reboot this in the 2026?

Why not just use something that already exists?

Nothing I’ve found so far quite fills this gap in this way.

I’m sure many have tried and failed (and we may too, but have more fun trying). One pattern I’m sure of though: small things can survive if they stay the right shape.

Looking at alternatives, they tend to fall into three categories: SaaS products that will likely eventually enshittify (Orbit, Luma, and Common Room already did); self-hosted tools that require a lot more faff than the challenge warrants (it needs to be as easy as possible); or shared documents (e.g. Airtable) that go stale because that’s just what happens: the utility or enthusiasm atrophies and, let’s face it, they’re just so desperately dull.

None of them seem to hold the shape of a human network, run by individuals, with communities of overlapping and transitory interests, where skills might cluster and gaps are plentiful. And, of course, all of them involve handing your member data to a platform with rights that seek to keep them, rather than keeping users in control.

I wanted something lightweight enough to actually run myself, curated enough to stay useful, and honest about what it is: more of a social directory rather than a social network. Yes, also looking back to where a lot of social networks began (looking at you, Well), and re-asking if the incentives to ‘keep growing’ were the wrong solutions, and for the wrong reasons (looking at you, FB, Tw*t, Ning, and the rest of you).

On words

cl8 is a compression of “constellation” or “constellate” (as a verb), the name I use for communities of practice, and the (astronomical) language that threads through a lot of my projects.

A constellation isn’t a random scatter of points, it’s more like a pattern that becomes legible when you can work out how to read it. The points were always there: a constellation is what happens when you impose meaning on proximity and cl8 is, perhaps, a type of social telescope. The people were already in the room, more or less: the tool just makes connections visible. Less stuff, more fun.

What it does

You sign in with Google or a verified email, fill in your name, a short bio, and tag yourself with your skills and interests. Ideally not job titles, but rather the things you’d say to someone when meeting them at one of my salon evenings on the boat.

It’s a searchable, private directory where your profile is visible only to other authenticated members of that cl8 instance. Access is granted by whoever runs that community: human curation is part of the design.

It can run on your own server, your community controls the membership, and your data is yours. I’ve built it for my dgen network constellation (you can sign up at d.cl8.io and as its curator it may take me a little while to manually approve you). The first instance is also running for IB1 (Icebreaker One), which is exactly the point: one tool, many communities, each owning their own. You can sign up for that one at ib1.org/constellation.

And yes, you’ll hopefully find some things in all of this that surprise and delight: it’s the start of a journey to doing things differently. It should be fun, so adding in things for your specific, quirky, bonkers community is up to you. Less faff, more fun.

What it doesn’t do

It doesn’t

reveal any information about you to anyone that you don’t want to share (see https://d.cl8.io/privacy)
track you (no cookies)
create more noise in the world

On building it

cl8 is a just few hundred KB of code: a single Node.js file with zero npm dependencies. It mirrors the same architecture as Broadside: copy the file to a server, configure, start a service, done. The data lives in flat JSON. The whole thing was built with AI assistance in the same spirit as the other tools in this stack: it’s been something I’ve wanted for years, and AI has helped me build it in about the same time as it would have taken to evaluate and customise any SaaS alternatives and then sign up for none of them.

It’s meant to be the absolute minimum. A social directory for a few hundred people doesn’t need a database cluster, it does need good session management, solid authentication and security, and enough care in the UI to make filling in your profile feel like something other than homework. Less code, more fun.

If you run a community of practice and you’re tired of it living inside someone else’s product, ping me. It’s open licence, deployable in under an hour, and then the only person looking after your community’s data is you (and them).

ai code example: animated planetary orbit

Gavin — Fri, 21 Jul 2023 20:31:49 +0000

Today’s example of how easy AI can make it to write code. The interactive animation below is the final output from various experiments below.
[My words have this colour background. My instructions to the AI are in bold.
The rest of the content on this page is the AI. All of it, including words, code and highlighting.]

To begin with I just asked it the following:
write html, css and javascript to demonstrate a planet orbiting the sun
It replied…

Creating a realistic 3D planet orbiting the sun requires more advanced graphics and libraries, but I can show you a basic demonstration using HTML, CSS, and JavaScript that simulates a simple planet orbiting the sun

example.html




  
  
  Orbiting Planet

CSS (styles.css):

body {
  margin: 0;
  padding: 0;
  overflow: hidden;
}

.sun {
  width: 100px;
  height: 100px;
  background-color: orange;
  border-radius: 50%;
  position: absolute;
  top: 50%;
  left: 50%;
  transform: translate(-50%, -50%);
}

.planet {
  width: 30px;
  height: 30px;
  background-color: blue;
  border-radius: 50%;
  position: absolute;
  top: 50%;
  left: 50%;
  transform: translate(-50%, -50%);
}

JavaScript (script.js):

let angle = 0;
const orbitRadius = 150;
const orbitSpeed = 0.005;

function animatePlanet() {
  const planet = document.querySelector('.planet');
  const sun = document.querySelector('.sun');
  const sunRect = sun.getBoundingClientRect();
  const centerX = sunRect.left + sunRect.width / 2;
  const centerY = sunRect.top + sunRect.height / 2;

  const x = centerX + orbitRadius * Math.cos(angle);
  const y = centerY + orbitRadius * Math.sin(angle);

  planet.style.left = x + 'px';
  planet.style.top = y + 'px';

  angle += orbitSpeed;
  requestAnimationFrame(animatePlanet);
}

animatePlanet();

This code creates a basic representation of a planet (blue circle) orbiting the sun (orange circle). It uses CSS to position and style the sun and the planet, and JavaScript to calculate the position of the planet as it orbits the sun.

Please note that this is a simplified demonstration and does not include realistic physics or 3D graphics. For more advanced and realistic animations, you would need to use libraries like Three.js or other WebGL frameworks.”

This is pretty astonishing [output]

but I wasn’t happy with it being a circular orbit, so I asked it to:
redo with an elliptical orbit

Creating an elliptical orbit requires more complex mathematical calculations and is beyond the scope of basic HTML, CSS, and JavaScript. However, I can show you an example using the p5.js library, which is a JavaScript library for creative coding and visualization. The p5.js library simplifies handling graphics and animation, making it easier to demonstrate an elliptical orbit.

First, include the p5.js library in your HTML file:




  
  
  Elliptical Orbit

Next, create a JavaScript file (e.g., “sketch.js”) that will handle the animation and display of the elliptical orbit:

let sun;
let planet;
let orbitRadiusX = 150;
let orbitRadiusY = 100;
let angle = 0;
let orbitSpeed = 0.01;

function setup() {
  createCanvas(windowWidth, windowHeight);
  sun = createVector(width / 2, height / 2);
  planet = createVector(sun.x + orbitRadiusX, sun.y);
}

function draw() {
  background(240);

  // Draw the sun
  fill('orange');
  ellipse(sun.x, sun.y, 40, 40);

  // Calculate the position of the planet in the elliptical orbit
  let x = sun.x + orbitRadiusX * cos(angle);
  let y = sun.y + orbitRadiusY * sin(angle);

  // Draw the planet
  fill('blue');
  ellipse(x, y, 20, 20);

  // Update the angle for the next frame
  angle += orbitSpeed;
}

The above code sets up a canvas, defines the sun and planet as vectors, and uses trigonometry to calculate the position of the planet as it moves along an elliptical orbit around the sun. The orbitRadiusX and orbitRadiusY variables determine the shape and size of the elliptical orbit, while the orbitSpeed variable controls the speed of the orbit.

Save these HTML and JavaScript files in the same folder and open the HTML file in a web browser. You should see an animation of a blue planet orbiting an orange sun in an elliptical path. Feel free to adjust the values of orbitRadiusX, orbitRadiusY, and orbitSpeed to experiment with different elliptical orbits.

This is a great example of how game-changing AI is becoming. To see the two bits of code (copy & pasted) in action, click Circular or Elliptical. Remarkable.

And then my friend Andy noticed it wasn’t doing a Keplerian orbit, so
redo with a keplerian orbit
led to this

Creating a Keplerian orbit involves implementing more complex mathematical formulas to simulate the motion of celestial bodies following Kepler’s laws of planetary motion. To do this, we’ll use the p5.js library to handle graphics and animation.

First, include the p5.js library in your HTML file:




  
  
  Keplerian Orbit

Next, create a JavaScript file (e.g., “sketch.js”) that will handle the animation and display of the Keplerian orbit:

let sun;
let planet;
let a; // Semi-major axis
let b; // Semi-minor axis
let angle = 0;
let orbitSpeed = 0.01;

function setup() {
  createCanvas(windowWidth, windowHeight);
  sun = createVector(width / 2, height / 2);
  a = 150; // Set the semi-major axis
  b = 100; // Set the semi-minor axis
  planet = createVector(sun.x + a, sun.y);
}

function draw() {
  background(240);

  // Draw the sun
  fill('orange');
  ellipse(sun.x, sun.y, 40, 40);

  // Calculate the position of the planet in the Keplerian orbit
  let x = sun.x + a * cos(angle);
  let y = sun.y + b * sin(angle);

  // Draw the planet
  fill('blue');
  ellipse(x, y, 20, 20);

  // Update the angle for the next frame
  angle += orbitSpeed;
}

The above code sets up a canvas, defines the sun and planet as vectors, and uses trigonometry to calculate the position of the planet following Kepler’s laws of planetary motion. The a and b variables determine the size and shape of the Keplerian orbit, while the orbitSpeed variable controls the speed of the orbit.

Save these HTML and JavaScript files in the same folder and open the HTML file in a web browser. You should see an animation of a blue planet following a Keplerian orbit around an orange sun. Feel free to adjust the values of a, b, and orbitSpeed to experiment with different Keplerian orbits.

Interesting but still not quite there

So let’s
place the sun at a focus point and add gravity

To add gravity to the Keplerian orbit simulation, we can use Newton’s law of universal gravitation to calculate the gravitational force between the sun and the planet. The force will affect the acceleration of the planet, causing it to move in a curved path around the sun.

Here’s the updated code that includes gravity:

let sun;
let planet;
let a; // Semi-major axis
let b; // Semi-minor axis
let c; // Distance from the center to focus (c = sqrt(a^2 - b^2))
let angle = 0;
let orbitSpeed = 0.01;
let G = 0.5; // Gravitational constant

function setup() {
  createCanvas(windowWidth, windowHeight);
  sun = createVector(width / 2, height / 2);
  a = 150; // Set the semi-major axis
  b = 100; // Set the semi-minor axis
  c = sqrt(a * a - b * b);
  planet = createVector(sun.x + c + a, sun.y);
}

function draw() {
  background(240);

  // Draw the sun at the focus point
  fill('orange');
  ellipse(sun.x, sun.y, 40, 40);

  // Calculate the position of the planet in the Keplerian orbit
  let x = sun.x + c + a * cos(angle);
  let y = sun.y + b * sin(angle);

  // Draw the planet
  fill('blue');
  ellipse(x, y, 20, 20);

  // Calculate the distance between the planet and the sun
  let distance = dist(x, y, sun.x, sun.y);

  // Calculate the gravitational force between the planet and the sun
  let force = G * (1 / (distance * distance));

  // Calculate the angle of the force vector
  let forceAngle = atan2(sun.y - y, sun.x - x);

  // Calculate the acceleration of the planet due to gravity
  let acceleration = force / 1; // We can simplify the mass of the planet as 1

  // Update the planet's velocity based on the acceleration
  orbitSpeed += acceleration;

  // Update the angle for the next frame
  angle += orbitSpeed;
}

In this updated code, we introduce the gravitational constant G (you can adjust its value to control the strength of gravity) and calculate the gravitational force between the sun and the planet using Newton’s law of universal gravitation. The planet’s acceleration is then updated based on the gravitational force, and its velocity is adjusted accordingly. The result is a more realistic simulation of a Keplerian orbit with gravity affecting the motion of the planet around the sun.

Save these HTML and JavaScript files in the same folder and open the HTML file in a web browser. You should now see an animation of a blue planet following a Keplerian orbit around an orange sun, with gravity affecting its movement. Feel free to experiment with different values of G and other parameters to observe different orbital behaviors.

Very interesting. It get’s it much more right, but there’s an acceleration that shouldn’t be there. The planet spins faster and faster…

so, rather than try and troubleshoot it, let’s just ask it
why does the speed of the planet accelerate?

Apologies for the confusion in the code. The speed of the planet should not accelerate as a result of gravitational force. In reality, the speed of a planet in a stable orbit around the sun remains constant.

To accurately simulate a stable orbit, we need to use the principles of circular motion and centripetal force. The centripetal force acts perpendicular to the velocity vector, causing the planet to follow a circular path around the sun. In this scenario, the speed of the planet remains constant while its direction continuously changes.

Let’s correct the code to achieve a stable circular orbit:

let sun;
let planet;
let a; // Semi-major axis
let b; // Semi-minor axis
let c; // Distance from the center to focus (c = sqrt(a^2 - b^2))
let angle = 0;
let orbitSpeed = 0.01;
let G = 0.5; // Gravitational constant

function setup() {
  createCanvas(windowWidth, windowHeight);
  sun = createVector(width / 2, height / 2);
  a = 150; // Set the semi-major axis
  b = 100; // Set the semi-minor axis
  c = sqrt(a * a - b * b);
  planet = createVector(sun.x + c + a, sun.y);
}

function draw() {
  background(240);

  // Draw the sun at the focus point
  fill('orange');
  ellipse(sun.x, sun.y, 40, 40);

  // Calculate the position of the planet in the Keplerian orbit
  let x = sun.x + c + a * cos(angle);
  let y = sun.y + b * sin(angle);

  // Draw the planet
  fill('blue');
  ellipse(x, y, 20, 20);

  // Update the angle for the next frame
  angle += orbitSpeed;
}

And, there we have it. We didn’t even need to understand why the planet was accelerating, or if there was a bug in the code, just ask a question and it corrected itself.

I wanted to change the colours and layout a bit, so I asked it to do that too
left-align the scene, make the sun yellow, the background black and the planet blue
and then I thought it’d be fun if we made it interactive, so I asked
add a slider so I can change the value of G and ensure that the animation updates automatically if the value is changed. put the slider at the top in the middle
which it didn’t get right the first time (the slider moved but the planet speed didn’t change) so,
that isn’t updating the value of G in the animation
which fixed it, and then a final bit of fiddling
print the value of G on the screen as well. align the slider so it’s just above the animation
move it 200px left. Keep the value of G next to the slider
and so on, which resulted in the interactive example at the top of this page

And, lastly, for fans of Processing, simply asking it to
rewrite this in Processing
gave this working code

int sunX, sunY;
float a; // Semi-major axis
float b; // Semi-minor axis
float c; // Distance from the center to focus (c = sqrt(a^2 - b^2))
float angle = 0;
float orbitSpeed = 0.01;
float G = 0.5; // Gravitational constant

void setup() {
  size(800, 600);
  sunX = width / 4;
  sunY = height / 2;
  a = 150; // Set the semi-major axis
  b = 100; // Set the semi-minor axis
  c = sqrt(a * a - b * b);
}

void draw() {
  background(0); // Set background color to black

  // Draw the sun at the focus point
  fill(255, 255, 0); // Change sun color to yellow
  ellipse(sunX, sunY, 40, 40);

  // Calculate the position of the planet in the Keplerian orbit
  float x = sunX + c + a * cos(angle);
  float y = sunY + b * sin(angle);

  // Draw the planet
  fill(0, 0, 255); // Change planet color to blue
  ellipse(x, y, 20, 20);

  // Update the angle for the next frame based on the slider value
  angle += G * orbitSpeed; // Use G to modify orbit speed

  // Display the value of G next to the slider
  fill(255);
  textSize(20);
  text("Gravitational Constant (G): " + G, 20, 20);
}

// Event handler for the slider
void mouseReleased() {
  if (mouseX >= 20 && mouseX <= 320 && mouseY >= 40 && mouseY <= 60) {
    // Map the x-coordinate of the mouse to a value between 0 and 2 for G
    G = map(mouseX, 20, 320, 0, 2);
  }
}

Data governance — how to move fast and not break things

Gavin — Wed, 01 Apr 2020 00:00:40 +0000

I’ve been receiving a lot of calls from people asking how they can use data to ‘help’.

To help frame a potential response that isn’t just ‘we can build an app for that’ (that’s very rarely the answer), I’ve been trying to encourage people to first look at user needs and prior work. In times of ’emergency’ there’s a rush for people to want to ‘do something’— let’s harness that energy on useful things rather than squander it on ‘solutionising’?

Here’s a provocation process to ask how we can try and focus on what matters; that can unlock rapid-response from a frontline delivery team who can focus on solutions. At the same time, let’s also avoid just breaking things in the process, and give the frontline team (and the rest of us) the confidence that there is a process following them that will tidy up.

Questions to consider:

What problems are we really trying to solve — based on actual user needs?
How will data help these problems? (what data, what analysis, etc?)
Who should act to convene and lead: a sector, public body, both?
When are solutions needed and what might be our MVP intervention? (this may not need any data)
What single-issue could act as an exemplar?

[click to comment or edit] (or quick-link to this slide http://bit.ly/data-triage)

An evolution in process

Gavin — Thu, 03 Oct 2019 08:39:38 +0000

The above chart is an evolution of the work of Simon Wardley, which I’ve been following for many years. It feels like we’re in another phase-change based on the impact of the web and technology: of radically centralised+decentralised tensions, of systems that self-organise/self-actuate, where teams are spread as constellations, and where ‘open’ (for many varying definitions of the word) is a central forcing function of change.

“Innovators must deter competition to get some of the value they created”

This view has been at the heart of our industrial economic drive—I think most of my career has been anchored in trying to invert it.

In creating open businesses I’ve continuously sought to increase the number of connections, not the size of the moat: building federated systems not centralised fiefdoms, actively encouraging imitation and rapid evolution. In the long-term, I think the impact of being open is far more profound as a culture shift.

Moats draw their power to prevent imitation from one of four basic sources:

The state
We’ve created regulation that mandates ‘open’ systems, such as Open Banking. This is now in-force in the UK and in development in 20 countries. The impact, I think, will be both innovation and the radical erosion of ‘excess profit’ to make open markets operate the way they were intended.

Special know-how
The web removes this as a barrier pretty quickly. The cost of setting up, for example, a bank is now 1/10th to 1/100th what it used to be. Moore’s Law applies to business models not just technology.

Scale
Ditto scale. Cloud compute + web + mobile decimates the path to the customer faster and at greater scale than anything else we’ve invented.

System rigidity
Systems rigidity is a bug, not a feature. Startups route around rigidity faster than incumbents can hold a meeting. Note that rigidity is not the same thing as resilience or robustness.

And, with a startup lens: “Startups that aim to create value can’t have a moat when they begin, uncertainty is what protects them from competition until a proper moat can be built. Uncertainty becomes their moat.”

So, what next, moat-economy enthusiasts? How do these ideas evolve in a web-first society & economy?

My friend Peter commented:

“Innovation must be open and collaborative, value is created by societies not individuals, through innovation, because it is not an absolute, it is a differential, it is how we rescue wealth from the inevitable decay imposed by obsolescence and environmental “externalities”. Individuals who hoard end up sitting on a pile of worthless rubbish … and our society is geared up to pay them for the privilege – i.e. we pay for the decay of the wealth of others. That’s what being rich means in this unsustainable zero sum game.”

“Extreme sharing is a political act”

Gavin — Tue, 05 Feb 2019 23:24:52 +0000

What Alex has created in the Algorave movement is quite remarkable. He’s ‘cracked the code’ [literally] of how to transform coding into a live creative art form.

This is something I tried to write about in my [1993] Masters thesis — I went into a virtual reality context, trying to enable the construction of any form of codified instrument in a VR environment; exploring questions about what a performant interface might be if you had unlimited possibilities.

Alex has instead created something very useable, accessible and enables many thousands of people to explore and create a different way of writing.

Beyond creating the code, and helping build a diverse and open community, he’s touched on the fact that this is a response to a shifting cultural landscape: “if you share something it grows in value” // “extreme sharing is a political act”

Algorave embodies the principles of a different way of thinking.

In my corporate presentations, today, I talk about data “increasing in value the more it is connected” (rather than “being the new oil”). I suspect we are still at the beginning of this particular socioeconomic unpacking.

https://www.residentadvisor.net/features/3396

[disclaimer: Alex is also a friend, former colleague, and was musician in residence at the Open Data Institute]

A quantum city?

Gavin — Sat, 12 May 2018 12:40:56 +0000

Light pipes for photons, in triangles and loops

(in the photo, the oblongs are loops of fibre to create delays and the lines all fibre optics)

About 18 months ago (thanks to Libby) I attended a discussion about some of the most advanced quantum computing research in the world.

At the time I thought this must have been how it felt when people first made electrical circuits: the excitement of being able to channel and control electrons, that we now take for granted, but this time with light.

It felt like magic to me that we could control photons within such a beautiful design and wondered, given we see electrical circuits as a visual equivalent to cities, how quantum computers might indicate the future of our city design?

I love Stanza’s work for this (and many) reasons.

“The age of privacy is over. Imagine walking out the door, and knowing every single action, movement, sound, micro movement, pulse, and thread of information is being tracked, monitored, stored, analyzed, interpreted, and logged. The world we will live in seems to be a much bigger brother than the Orwellian vision, it is the mother of big brother.”

What if Nature were not collective but distributive?

Nomos asks if “the Quantum City is, different from the Mechanical and the Dynamic City, not strictly rational” and posits another angle that is highly aligned with contemporary cultural development (from the co-op movement to distributed ledgers/blockchain)

Arida has mapped [2002] the evolution of world views from the Roman Empire to Quantum theory, and the close links between science and urban form. He looked at the way we can design and live in quantum cities, exploring methodologies that can frame quantum urbanism: this work continues on the website http://www.quantumcity.com “Urbanism Needs a Conceptual Revolution”.

In one example (of many), IAAC created its framing of the quantised city [video, 2012], blending data from IoT sensors, cloud computing and combining environmental and energy data as part of urban architecture.

CAAD has published [2015] ‘A Quantum City, Mastering the Generic’, self-described as “a love letter to the city and intellectual culture”, it introduces Orlando — neither an authoritarian functionary, nor a restless activist, nor a comfortable member of a bourgeoisie, but a citizen of the digital age, a Quantum Citizen. https://www.caad.arch.ethz.ch/blog/a-quantum-city-mastering-the-generic

It feels to me that there is a line of enquiry to use the subjectivity of art to question the objectivity of science, political dogma, urban design and notions of truth.

What are the visual loops that could be examined between the circuit designs of quantum computers, city architecture, building design and social constructs?

How does this interface with our notions of Data Infrastructure?

Is there something to learn from combining quantum computing, art, urban design and cultural uncertainty?

A Digital Commonwealth?

Gavin — Mon, 16 Apr 2018 11:10:20 +0000

At the 2015 CHOGM in Malta I suggested it would be prescient to consider the future of the Commonwealth through a digital lens. At the time, it felt as if the Commonwealth was at a tipping point and that the consideration of a ‘Digital Commonwealth’ might be a useful springboard.

Today, I am moderating a 60-person panel at the 2018 CHOGM Commonwealth Business Forum to discuss exactly this: is there a role for a Digital Commonwealth Initiative to encourage greater collaboration?

Update:

Notes from the session

nb. the session was vastly oversubscribed and we ended up with over 120 people in the room.

Background

As everything becomes data-driven, we must address how we best serve our citizens in a digital age and support cooperation that develops an equitable digital economy. A rules-based system can balance the benefits for everyone whereas the absence or failure of rules will lead to a deals-based system that will favour only the few.

Around the world, countries, cities and regions are struggling to keep up with the pace of technological change. It is a time where collaboration can catalyse the development of new, inclusive and open marketplaces. In parallel we must address issues of privacy and security.

Central to achieving this in a digital age is to have a framework that reduces transactional friction (legal, commercial, currency, language) and can rapidly unlock our potential. One which can increase the responsiveness of policy to innovation; increase transparency and accountability; rebuild trust through legitimate consensus and common regulation.

We must also invest in literacy, communication and policy to bring stakeholders together and address issues which will stifle development.

Data increases in value the more it is connected. Now is the time to build upon the work of open government initiatives around the world, of open data policies across countries, cities and business, of EU data protection legislation and of groundbreaking initiatives such as the UK’s Open Banking Standard—which is setting precedents for regulation, business models, digital products and consumer rights.

Data is now part of our global infrastructure. We need to connect our innovators to policy-makers, businesses to investors, states and cities to address our shared social, economic, environmental challenges.

Our question is how might we create a Digital Commonwealth Initiative to set targets for, convene and oversee delivery of a bold initiative that ensures that, as we look to the future of our connected society, one of its most successful free trade networks leads the way.

Can government stop losing its mind?

Gavin — Tue, 27 Mar 2018 12:48:19 +0000

On Wednesday 18 April, Nesta is hosting the launch of a new report prepared by Gavin Starks.

The report entitled ‘Can government stop losing its mind?’ looks at the many ways the government has organised its data and knowledge, and examines examples ranging from the Ministries of Defence and Justice to the BBC and ODI. It shows how research, policy design and tracking can be managed more effectively.

Registration will open at 17.30 with the event starting promptly at 18.00. The event will close at 19.00 followed by networking drinks until 20.00.

Are we about to do something useful?

Gavin — Mon, 05 Feb 2018 11:29:53 +0000

“Society is demanding that companies, both public and private,
serve a social purpose.”
Larry Fink, CEO, Blackrock (who manage $1.7 trillion of active funds)

“Not all of the attention has been favourable, which makes this moment all the more significant.
Mr. Fink’s words mark a profound shift in the way business relates to society – a shift long in the making,”,
Chris Houston, Where is the money going?

Is it really the case that this is seen as a “new demand” from society?

Perhaps I’m naive (or just cynical), but I don’t remember any point where everyone was happy with the way business worked (apart from the ultra-rich).

What is the “profound shift” he’s speaking of – that someone in power listened and has commented that ‘society’ matters?

Do you think there is a material difference between this now and, for example, when Al Gore and David Blood published their Sustainable Capitalism manifesto (7 years ago), or when the UK passed the Climate Act (10 years ago), or countless other statements from ‘important people’ over decades?

What, specifically, is the leverage point here?

the perception of power through the ability to steer capital?
the absence of political leadership?
fears that human capital is now overexposed and a risk to profit?
fears around globalisation and (many) risks leading to migration and war (and thus risk to profits)?

I’ve written about ‘purpose washing‘ before, and it feels to me that underlying this is a fundamental concern about risk to profit rather than just an ‘awakening’ to social purpose. It reminds me a little of Obama reframing ‘green energy’ as ‘energy security’ (which was genius, as well as being correct and a good idea for the US economy).

How can we best capture this energy and positive intent?
Is it something that we can bring people around, or will cynicism override and we’ll undermine goodwill with divisiveness?
Do ‘leaders’ really need to be given so much permission by someone in order to lead? If so, how do we help do more of that?
What are the realistic signals and evidence that the humans in industry could produce that would be believable or trusted by the people Larry is talking about?

(image credit)