Building Bridges: The PC’s (Important) Forgotten Origin Story

By jeremy | September 3, 2024

Sir Clive Sinclair mosaic, made with original keys from Sinclair computers, Charis Tsevis, 2011 (Flickr)

Technology-wise, we’re presently in what might be called an interregnum.

There is no clear outcome for AI, especially generative AI. We can’t tell whether it’s a saviour, a destroyer, or a damp squib. More importantly, generative AI — and a lot of other stagnant technologies — doesn’t offer a bridge between where we currently are, and where we need to go.

But what might that bridge look like?

This is best explained by looking at an earlier paradigm shift: when personal computing began the journey from a DIY hobby for (mostly) 14-year old males to being a household tool or entertainment console. In blunt terms, the computer went from being a Meccano kit on a workbench to an item of furniture in the living room. When computers started to be useful and affordable.

Here’s a great visualisation which captures this sudden growth in the early 1980s (Source: Home computer sales, 1980–93 | Retro Deam/YouTube)

(The video doesn’t include IBM-compatible PCs, which of course eventually stole most of the market for a few decades. But you get the idea.)

For the masses

Exploring why and how this shift happened might help us understand what we should be looking for right now: what engine of change should we be keeping an eye out for, or, if we were of entrepreneurial bent, cooking up in a lab somewhere?

A Canadian Holocaust survivor, Jack Tramiel, was the first to recognise that computing was as much a consumer device as a business one. The trick was to make it visually appealing, fun, and cheap. His Commodore 64, unveiled in January 1982, was the first real mass market computer, with sound, graphics and software — all for less than $600. The computer “for the masses, not the classes” took North America by storm in 1981. At the time an Apple computer, though far better, would cost at least twice that. The Commodore 64 sold upwards of 12 million units.

Tramiel had understood computers were not confined to the workplace or science. But a British entrepreneur also understood that and may, on balance have contributed more to building the bridge that connected ‘computing’ with ‘appliance’. Sinclair (later Sir Clive) had sold circuit boards and kits profitably to a market of do-it-yourself enthusiasts since the early 1960s, but he was sure there was a much bigger market if he could make the products accessible and cheap enough.

Sinclair wanted to sell them below £100 — about $200 at the time. He knew the market well — enthusiasts wanted to get their hands on one to tinker with, to write code on, to learn how the machines worked, but they were often kids, and didn’t have a lot of cash.

Crucially for bridge building, he focused on marketing and distribution.

According to Bill Nichols, who ran his PR at the time, Sinclair understood that the market itself needed to be carefully nurtured in the crucial early days. Clive “always insisted that every product first went to market mail order under the total control of the company and the marketing team.” This direct connection, via a cohort of outsourced customer service staff allowed the company to hear and respond to feedback directly from early customers. “Then and only then when the awareness and initial demand was created — typically after six months or so — did it go retail,” he told me.

WH Smith ad for the ZX81, date unknown. (FunkYellowMonkey, imgur)

“Retail” here didn’t mean hobby and computer shops but high street heavy hitters like stationery and newpapers chain WH Smith and pharmacy and healthcare giant Boots. Now the demand had been nurtured enough to be self-supporting, and Sinclair’s marketing and pricing had taken hold, retailers could be confident there was enough demand across a broad customer base to make it worth their while to display them prominently.

Tomb Raider and GTA

For kids and parents they were now easy to find, impossible to resist, and fun to use. The ZX Spectrum, the third incarnation of the Sinclair computer launched in April 1982, sold over 5 million units. Sinclair was a suddenly a serious competitor to Commodore: the Commodore sales team felt them to be enough of a threat to post a photo of Sinclair’s marketing chief Nichols on their dart board.

In one year the computer had gone from an obscure piece of machinery to a consumer device. It also played an important role in creating what we’d now call the ecosystem to support the transition. It was still a little unclear what computers might do for us. Games was the most obvious thing, and the ZX series are credited with spawning a generation of ‘bedroom coders’, kids who would develop games and sell them via hobby magazines. The British video game industry now employs over 20,000 people, and major franchises like Grand Theft Auto and Tomb Raider can trace their roots to companies founded in this early wave. By 1984 the UK had more computers per household (13%) than the U.S. (8.2%) — with the U.S. only catching up in the 2000s.

Sinclair made mistakes. A crucial one was trying to build a market with professionals with the next ZX model, the QL. The device was as half-baked as the rationale — professionals who might need a spreadsheet would already have an IBM PC — and its failure led to him selling the ZX business to a consumer electronics company, Amstrad. Amstrad’s owner, Alan Sugar, had a better instinct for what people needed a computer for: his line of PCW computers were marketed as “word processors”. He sold 8 million of them. (I was no techie but I bought one, and it kickstarted my journalism career. My dad wrote a book with it.)

Sir Clive and Jack Tramiel are mostly forgotten figures now but it’s no exaggeration to say this: he probably contributed as much as the likes of Bill Gates, Steve Wozniak and Steve Jobs to the silicon landscape we inhabit today. Both built bridges from the narrow enclaves of ‘enterprise’ and ‘hobby’computing to something called ‘personal computing’, without which we wouldn’t be writing, distributing and reading this on computing devices. In 1980 some 750,000 devices that could be called personal computers were sold. In 1990 there were 20 million. (Source)

That this period is largely forgotten is to our cost. Sure, Gates was instrumental but he was late to the game — Windows 95 was arguably its first consumer-facing product. Jobs understood the market better, but Apple’s first Macintosh, launched in 1984, cost $2,500, ten times a ZX computer. Both Microsoft and Apple scaled the divide between office and home device, but it was the Commodore, ZX, and a handful of other much cheaper devices that built the bridge between them.

Sliding the rules

So what do we learn here? What lessons can we apply to the place we’re in today?

Well, first off, we have lousy memories. That the Sinclairs of this world, and what they did, are rarely mentioned shows just how little we understand about how computing got to be the ubiquitous, ambient thing it is today.

Secondly, there’s only so much we can learn through the lens of Silicon Valley’s favourite business consultant. Superficially at least, Sinclair was an early entrepreneur in the Clayton Christensen mould: catering to underserved segments, building products that were affordable, simplified and user-friendly, and making incremental improvements to gain market share. But he was so much more.

Sinclair was obsessed by several things, one of them fatal. He understood two key concepts: price and size. While semiconductor manufacturers would discard chips that didn’t meet their specifications, many of those rejects might work fine if he designed a product to more lenient specs. “Good enough,” in Clayton Christensen’s words. For the rest of his life he would follow a similar pattern: dream up a product, scout out the technology to see whether it could be built, and then pare back the product (and the size and quality of components) to fit a specific price point and size.

Sinclair’s obsession with the miniature emerged less from notions of disruptive innovation and more, his sister Fiona believes, from the “very confused childhood” they shared, which led her to therapy and him to seeking to impose order on the world. “Everything he makes, everything he designs is to do with order — making things smaller, finer, neater,” she said of him.

The resulting products all leveraged technology to build bridges from niche market to mass. His calculators were small and stylish enough to be desirable in a way calculators hadn’t been before, but cheap enough for everyone. It’s hard to overstate the impact this had. Schoolkids like me were still being taught how to use a sliderule to make calculations in the 1970s, but when the first kid brought a Sinclair Oxford 100 into class (£13) we knew those log table books were doomed.

Vintage Aristo Darmstadt Slide Rule, Joe Haupt (Flickr)

But he had another infatuation: the new. The Sinclair QL, which effectively killed his computer business, arose out of his reluctance to build on a good thing, throwing the earlier ZX model out and trying something completely new, for a market that was already being catered to and which didn’t care overly about price. Launched in 1984, the QL was discontinued within two years after selling around 150,000 units, and Sinclair was forced to sell.

Sinclair understood about the bridge, but in this case misread it. The bridge here was a bridge backwards, returning to a market that already existed, and where users weren’t overly sensitive to price, but were sensitive about usability.

A calculator in your stocking

To me the key lesson to be drawn is this: Sometimes there needs to be an intermediary technology, or technologies, that can be pulled together in a new (and cheaper) way to create a new device, possibly even one that doesn’t have a name. There may be no demand for such a device, but that demand can, with good marketing and distribution, be created. By doing so you create a new market beyond the old one.

This might sound easy and obvious, but it’s not. Sinclair was already well-versed in this approach before he applied it to computers. He had built tiny transistor radios, taking the radio out of the living room and into the pocket or bedroom; home-made amplifiers to take hifi away from the deep-pocketed connoisseur; calculators out of science labs and accounting departments; digital display watches light years ahead of your smart watch; and (spectacularly, in terms of grand failures) electrical vehicles out of the auto industry and milk float sector.

Not all of these, ok not many of these, were successful, but it helped Sinclair develop a good understanding, not so much of invading existing markets a la Christensen, but of creating new ones. No one realistically thought that everyone wanted a calculator until Sinclair suggested it would make a great Christmas present. No one thought a computer would be much fun until he got them into stationers, toy shops and pharmacies. He built a bridge to a place no-one thought existed.

*The common view of Sinclair: Daily Telegraph obituary, 18 Sept 2021*

We are in something similar now. We have been sitting on a plateau of new, technology-driven consumer products for nigh on a decade now. Interesting technology — materials, blockchain, AI, AR, VR — hasn’t created any real mass market, and that, I believe, is in part due to a lack of imagination and understanding of how bridge-building to new markets works.

I don’t claim to know exactly where those new places are. It could be that some part of AI makes it possible for us to develop a taste for always-new music, say: so instead of us seeking out the familiar when it comes to aural entertainment, we demand AI creates something new for us. (I’ve mentioned before how intriguing I find the likes of udio.com. Here’s a rough stab at “a song in the style of early Yellow Magic Orchestra” with abject apologies to the souls of Yukihiro Takahashi and Ryuichi Sakamoto. )

This is probably too obvious and too narrow an assessment of the market’s potential. Sinclair’s advantage was that he was a nerd first, but a consumer a close second. He dreamed of things he’d like, he understood the technologies, their availability or lack of it, and he cared deeply about form factor. He brought disparate software, materials, circuitry and functionality together to make something that people either never thought they needed, or never imagined they could afford.

Others took his ideas and made them better, cheaper, more reliable: Casio’s calculators (and calculator watches); Amstrad’s computers; even his C5 electric trike, which I’ll explore more deeply elsewhere, became the opening salvo in a decades-long struggle that brought us EV scooters, even the Tesla.

It takes an uncommon mind to see these markets and build the bridges between them. We would not be here if it weren’t for folks like Sinclair who felt people would like these technologies if they were cheap enough, and fun enough, and he understood, at least a little, where we might go with them if we had them.

Now it’s time for someone to ask the same questions and build us some bridges from where we are — computing devices that have been good enough for a decade, software that is mostly a retread of last year’s, and an AI that is undoubtedly impressive, but also depressingly flawed and ultimately dissatisfying.

Over to you.

Anticipating the wave train of AI

By jeremy | July 3, 2024

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We’ve been poor about trying to predict the real, lasting impact of generative AI.

It’s not through lack of trying: some have talked about rethinking the way our economies run and how we think about our lives, to treating it as an existential risk, to treating AI as a foundational, or general purpose, technology that will change everything.

Soldiers gathered around a transistor radio to listen to a broadcast. 1966.
Oliver Noonan/Associated Press

I’m not above a bit of grand predicting, and I’ll make some here, but it took me a while to realise why all these efforts sat awkwardly for me. We’re used to tech players having a very clear and reasoned notion about the likely impact of their technologies, even if they’re wrong: we want information to be free; we want to unlock the value in owned property — cars, houses; we want to empower everyone on the planet by connecting them to the internet.

All fine, but AI, or in particular generative AI, seems to lack one of these clarifying bumper stickers. It’s vague, amorphous, grand but somehow silly, as if we’ve given the pub mic to the only person in the room who has never done stand-up.

It’s partly, I suppose, because of the nature of AI. We have found it useful for stuff: identifying cats, driving cars, taking better pictures, sorting search results. GAI, meanwhile, is a different beast. In a way we’re struggling for a use case that justifies the vast expense in building and running large language models.

But it’s something else. It’s because Silicon Valley has, for much of the past 20 years or so, been built on the idea of disruptive innovation — that technology will always find a way to do something differently, which will somehow find a way to dislodge an incumbent technology.

And not only have we really worked out what that incumbent technology is when it comes to GAI, we have been too uncritical in our belief in the concept of disruptive innovation. We need, I believe, to overhaul the concept, in order for it to be more useful at this point in our technological progress.

Let me show what I mean by talking about humble transistor radio.

*Transistor radios, 2015, by Roadsidepictures*

This cute little fella, smaller than most modern smartphones, is often wheeled out as a great example of disruptive innovation, where a newcomer to the scene spots an opportunity to undercut expensive vacuum-tube radios with cheap and cheerful devices that were “good enough” for consumers. Here’s how the founder of disruptive innovation, Clayton Christensen, told the story in his “The Innovator’s Dilemma”:

In the early 1950s, Akio Morita, the chairman of Sony, took up residence in an inexpensive New York City hotel in order to negotiate a license to AT&T’s patented transistor technology, which its scientists had invented in 1947. Morita found AT&T to be a less-than-willing negotiator and had to visit the company repeatedly badgering AT&T to grant the license. Finally AT&T relented. After the meeting ended in which the licensing documents were signed, an AT&T official asked Morita what Sony planned to do with the license. “We will build small radios,” Morita replied. “Why would anyone care about smaller radios?” the official queried. “We’ll see,” was Morita’s answer.

This isn’t accurate, on several counts. Bell Labs, co-owned by AT&T and Western Electric, had been showing off its transistors’ radio capabilities as early as 1947, though use cases and bugs were still being fixed. It’s unthinkable that AT&T had not already thought of the transistor radio — their problem had been finding consumer manufacturers to partner with.

Christensen continues:

Several months later Sony introduced to the U.S. market the first portable transistor radio. According to the dominant metrics of radio performance in the mainstream market, these early transistor radios were really bad, offering far lower fidelity and much more static than the vacuum tube-based tabletop radios that were the dominant design of the time. But rather than work in his labs until his transistor radios were performance-competitive in the major market (which is what most of the leading electronics companies did with transistor technology), Morita instead found a market that valued the attributes of the technology as it existed at the time — the portable personal radio. Not surprisingly, none of the leading makers of tabletop radios became a leading producer of portable radios, and all were subsequently driven from the radio market.

The little gadget that could

In fact, Sony weren’t actually the first to introduce a small transistor radio, nor were they the ones who first recognised the transistor’s commercial potential. Already by 1950 the idea of the transistor radio was being described as the “find of the century” for commercial usage; three years later the first prototype transistor radios were being appearing in the wild, and one or two journalists were already writing about them. In January 1953 freelance science writer Leonard Engel wrote a piece headlined Curtain Lifts on Little Gadget Likely to Revolutionise Radio:

*Star Weekly (Toronto, Ontario, Canada) · Sat, 10 Jan 1953 · Page 10*

The delay wasn’t only due to indifference. Commercialisation was in part held back due to technical constraints — engineers had yet to master how to mould germanium, a key material, into the special forms required for transistors — but also in part due to the fact that most transistors were “going to the military for secret devices.” (Transistor technology originated in Allied research into radar during the war.)

And while Sony’s Morita may have been quick to recognise the opportunity, the first to market was Texas Instruments, with the launch of the Regency TR-1 in October 1954. They weren’t cheap: adverts at the time showed them retailing around $100 — roughly what an iPhone 15 Pro Max would cost today.

*The Indianapolis News (Indianapolis, Indiana) · Mon, 18 Oct 1954 · Page 31*

And while cheaper versions eventually brought the price down to $5 or less, Sony’s initial offerings such as the TR-63 cost more or less the same as the TR-1. (See The Transistor Radio in Nuts & Volts Magazine.)

This reality doesn’t fit the myth Christensen heard, and it doesn’t fit the disruptive dogma still powering Silicon Valley.

‘Destroying the social life of mankind’

But it’s not just the chronology of those first few years that is skewed. The focus on disrupting market incumbents misses out so much.

The introduction of the transistor radio, and its rapid spread across the globe, had a profound effect on mass communication, including the building of a mass infrastructure to support the radio’s reach and influence. In 1950 there were 46 countries without any radio broadcasting transmitter at all. By 1960 that number had fallen to 14. In 1950 more than half of the 159 countries surveyed had less than 10 radio receivers per 1,000 people. By 1960 that number had halved. The number of radio receivers in the world doubled between 1950 and 1960 — about half of them in the U.S. (Statistics on Radio and Television, 1950–1960, UNESCO, 1963) . The numbers rose even faster as the Beatles gained popularity: sales in the U.S. almost doubled, to 10 million transistor radios, between 1962 and 1963. (Source: Transistor radios: The technology that ignited Beatlemania — CBS News)

UNESCO had realised early on that radio could be a powerful tool for education — particularly given illiteracy, which was as high as 85% in some countries. (UNESCO Technical Needs Commission, Recommendations of the Sub-Commission on Radio, Aug 1948). War, too, had already convinced many countries of radio’s awesome political power: onetime BBC Governor Sir Ian Fraser had called it “an agency of the mind, which, potentially at least, can ennoble or utterly destroy the social life of mankind” (Broadcasting in the UK and US in the 1950s, edited by Jamie Medhurst, Siân Nicholas and Tom O’Malley, 2016). Indeed, both British and German governments had pushed for cheap radio sets to ensure their propaganda could spread as widely and quickly as possible during the war. ( Source: Television and radio in the Second World War | National Science and Media Museum).

Radio stations were a required target for any respecting coup plotter. Edwin Luttwak, in his Coup d’Etat: A Practical Handbook (1968), prescribed the seizing of the key radio station and establishing a monopoly on information by disabling any others, using “cooperative technicians” where possible. He ascribed part of the reason for the failure of Greek King Constantine II’s counter coup in late 1967, was the fact that the government radio station, Radio Larissa, reached only a fraction of the population because of its weak transmitter and unusual wavelength.

A Wall of Tinny Sound

Transistor radios, in other words, changed the way people got information, what they listened to and their habits. The TR-1 was released in October 1954 into a fast-fermenting musical world: Bill Haley released his Shake, Rattle and Roll the same month. By 1963, the now untethered average American teen listened to the radio for slightly more than three hours per day, according to Steve Greenberg’s piece on the Beatles. Bruce Springsteen believed the power and importance of his transistor radio could not be overstated: “I lived with it, tucked it in my schoolbag during the day, and tucked it beneath my pillow all hours of the night.” Radio became a “medium of mobile listening”, in the words of academics Tim Wall and Nick Webber (PDF), and music producers and song-writers adapted accordingly

Phil Spector, for example, built his “wall of sound”, filling the recording studio with mini-orchestras to create a big fat sound that was then fed through special “echo chambers” (See Lance LeSalle’s answer to the question What was Phil Spector’s ‘wall of sound’? on Quora). Spector’s innovations have fed pop music until today.

News spread faster, more immediate: initial reports of JFK’s assassination in November 1963 were largely heard on transistor radios, in fields, buses and on the street. James Sperber described how he heard from a friend who had smuggled a radio into their school in San Diego that JFK had been shot. Meanwhile the teachers, summoned one by one to learn the news themselves from the principal, decided not to burden their pupils with the news unaware many already knew.

The power of the transistor had been proven: from then on the race was to find more uses and scale the technology. Televisions, hearing aids and computers soon followed. Famously IBM president Thomas J. Watson bought 100 Regency radios and ordered that its computers immediately shift to using only transistors. “If that little outfit down in Texas can make these radios work for that kind of money, they can make transistors that will make our computers work, too,” he told executives. (Source: Crystal Fire: The Invention of the Transistor and the Birth of the Information Age)

The Soviet Union’s secret weapon

All this to say: The most disruption caused by transistor radios had very little to do with dislodging the old expensive valve radio manufacturers. It had to do with seismic shifts in behaviours, of consumption, of movement, of accessibility, of attention. It’s not hard, once you’ve absorbed the above tale, to draw a direct line between the transistor radio with the smartphone — via the Walkman, the CD Walkman, the iPod — and to see a certain inevitability. Miniaturisation and mobility became the bywords of consumption: so much so the Soviet Union earned much needed foreign currency by building the world’s smallest radio, the Micro, in the 1960s. It became the rage in Europe and the U.S., especially after Nikita Khrushchev gave one to Queen Elizabeth II (See: Soviet Postcards — “Micro” miniature radio, USSR, 1965–69 ).

*Soviet Amsa Micro radio, 1968 (Micro Transistor Radios, defunct website)*

We tend to think of disruption in terms of what it does to incumbents — companies, industries, workers etc. Really we should be looking beyond that: Much is missed if we assume the first wave of a tsunami is the last. The first is often not the most powerful: what follows is a ‘wave train’, the timings between them uneven, including edge waves, bores and seiches. We lack the imagination to predict and the tools to measure these serial disruptions that follow an innovation.

It is, I agree, not easy to think through the potential long-term impacts of a technology, especially one like AI. But it might help for us to at least be informing ourselves about the technology, its capabilities and its limits. I am an avid user of whatever tools I can lay my hands on, including both commercial services and any open source offerings. But we are too vulnerable to binaries: critical rejection or unquestioning embrace, which the transistor radio story shows us is both predictable and unhelpful to understanding its wave train.

Take, for example, hallucination. Loyal readers will know I’m not impressed by GAI’s ability to be honest. Indeed I would argue, 18 months in, that we’re no closer to solving the problem than we were before. I won’t bore you with the details but every tool I’ve used so far has failed basic robustness tests. If we choose to use these tools to create supposedly factual content, we will accelerate our decline into content mediocrity where every press release, every article, every email, every communication that might conceivably have been done with the help of AI will be dismissed as such.

Spikes and spin

Pretending this is not an issue is impossible, but the trick now seems to be to say that it’s just a blip. Despite its efforts to put a positive spin on the results, McKinsey’s recent survey on AI was forced to acknowledge that

Respondents to the latest survey are more likely than they were last year to say their organizations consider inaccuracy and IP infringement to be relevant to their use of gen AI, and about half continue to view cybersecurity as a risk.

That’s putting it mildly. The percentage of respondents who believed that inaccuracy was a risk rose from 56% to 63% between 2023 and 2024, making it their biggest concern out of the 10 or so on offer — the next one being IP and then cybersecurity, all three being deemed relevant by more than half of respondents. And sure, respondents are looking more closely at mitigating the problem but the number is around half of those who consider it a relevant problem (32% last year, 38% this.)

I’m sorry, but that to me essentially says a good chunk of those asked believe the technology is dangerous. And these people are apparently near the coalface. The 1,363 respondents are described as “representing the full range of regions, industries, company sizes, functional specialties, and tenures.” Nearly three quarters of them said their organizations “had adopted AI in at least one business function” and two thirds said their organizations “were regularly using gen AI in at least one function.” So for them to say in those numbers that GAI is making stuff up is the headline.

And yet the title of the paper is: The state of AI in early 2024: Gen AI adoption spikes and starts to generate value. The race to adopt AI, the race to sell AI-related services and consulting (which of course is what McKinsey is doing here) will unfortunately override the annoying voices in the boardroom saying, what are we doing here exactly?

Take the IP thing. There are some extraordinary, creative GAI tools out there — for making images and videos, music (try Udio), sound effects and text to voice (try out ElevenLabs) , but once again it’s inevitable that the companies behind these tools are either bought out by the bigger players or are bankrupted by intellectual property litigation. Those that survive will either leverage their own IP or retreat to a much more cautious approach, producing bland stuff that doesn’t fool anyone. (Just as it’s now relatively easy to spot visual content that’s been created by AI, so some people are already able to distinguish between AI-produced pop, such as Rick Beato’s son. )

So what we are left with? I’m told that LLM tools that use RAG, Retrieval-Augmented Generation, which confine the corpus an AI draws on, is proving useful in some verticals such as helping call centre support staff better help customers. That’s great but I’m not holding my breath. My experience with RAGs has not been a positive one. So I guess we’re left with writing faster, better emails, product descriptions and the like, none of which sound very exciting to me, nor particularly disruptive.

And, indeed, that is the problem. Companies hate to spend money on customer support, and so any money-throwing at GAI will be in the hope of saving more money later. Use cases like this will be the low-hanging fruit, because it’s relatively easy to sell, replacing one underpaid group of human drones with non-human ones.

Underwhelming. GAI may well have to rethink itself to avoid another AI winter or survive a race to the bottom, where every product and service has an AI feature that ends up being as little used as Siri or Clippy.

But if we’ve learned anything from the transistor radio, it’s that we have learned very little from transistor radios.

‘A revolutionary device’

Take for example what happened both before and after its launch. While Christensen’s founding myth of the cheap transistor radio was off, he was right that there was widespread scepticism about the transistor’s potential, with both academia and engineers only gradually being won over:

After indulging themselves for a year or two in the resentful skepticism with which academia generally greets revolutionary new concepts, physicists and electronics engineers gradually warmed to the expansive new possibilities offered by semiconductor electronics. By 1953, The Engineering Index, an annual compendium of scholarly monographs in technical fields, listed more than 500 papers on transistors and related semiconductor devices. A year later there were twice as many. (Source: The Chip: How Two Americans Invented the Microchip and Launched a Revolution — T.R. Reid)

But the transistor radio’s success quickly threw up another problem: scaling. Even as pocket radios were jumping off the shelves in the late 1950s, “the tyranny of numbers began to emerge. Enthusiasm gave way to frustration, even desperation,” according to Reid. The first transistor radios had 2–7 transistors: The problem was finding an economic and reliable way to cluster the thousands, even tens of thousands necessary for the devices which stood to benefit most from the transistor revolution. A Naval aircraft carrier had 350,000 electronic components; a single computer like the Control Data CD 1604 contained 25,000 transistors, according to Reid.

Solving that problem led to the integrated semiconductor circuits of our era, and the rest, as they say, is history. This story arc, however, is left out of the paeans to disruptive innovation, despite it being one we should be familiar with. A great idea comes along and takes a few visionaries (or good business minds) to see how it might be used. That in turn sparks a movement whose expansion is checked only by some limitations of the technology — usually related to scale. Solving those problems leads to even greater expansion, and we are into that wave train of change.

This describes, arguably, the evolution of AI, and even within AI for the evolution of instances of AI, such as neural networks, and, more recently generative AI. At any point someone predicting the long-term impact of the transistor radio might have looked foolish. Journalist Leonard Engel had been writing about the potential of transistors as far back as 1947, but he was a rare voice writing excitedly about the transistor’s potential. Even he was careful about when this revolution would start. In January 1953 he wrote:

A radio small enough to fit into the palm will be available in a few years. Your portable TV set will be the size of a small typewriter. And for the hard-of-hearing there will be a hearing aid the size of a matchbox which will run for a year on a single set of batteries. What’s even more important, air travel will be safer because better radio aids can be found. These are but a few of the revolutionary devices now possible thanks to a recent invention — a tiny device the size of a kernel of corn called the transistor.

He relegated to the bottom of his piece the real visionary:

Dr. E(lmer) W(illiam) Engstrom, head of the RCA laboratories, says that in less than five years transistors have come as far as vacuum tubes did in 20. He predicts that in another few years this amazing little gadget will be used not only in home radios and TV sets, but in all sorts of revolutionary devices that can scarcely be imagined today.

That last sentence stands the test of time, and that offers a helpful blueprint for thinking about AI. Not the self-serving (and misdirecting) noise about the existential threats, not the banal attempts to make customer service, legal research or content creation simpler and cheaper, but about what new things we might do, how society, health, war, creativity, might change and and how it may impact our lives in the same way that little transistor radio did.

We need to talk about our AI fetish

By jeremy | July 3, 2024

1 Comment

Artificial intelligence puts us in a bind that in some ways is quite new. It’s the first serious challenge to the ideas underpinning the modern state: governance, social and mental health, a balance between capitalism and protecting the individual, the extent of cooperation, collaboration and commerce with other states.

How can we address and wrestle with an amorphous technology that has not defined itself, even as it runs rampant through increasing facets of our lives? I don’t have the answer to that but I do know what we shouldn’t do.

The streets

But in other ways we have been here before, making the same mistakes. Only this time it might not be reversible.

Back in the 1920s, the idea of a street was not fixed. People “regarded the city street as a public space,open to anyone who did not endanger or obstruct other users”, in the words of Peter Norton, author of a paper called ‘Street Rivals’ that later became a book, ‘Fighting Traffic.’ Already, however, who took precedence was already becoming a loaded — and increasingly bloody — issue. ‘Joy riders’ took on ‘jay walkers’, and judges would usually side with pedestrians in lawsuits. Motorist associations and the car industry lobbied hard to remove pedestrians from streets and for the construction of more vehicle-only thoroughfares. The biggest and fastest technology won — for a century.

*Bangkok traffic, photo by Joan Campderrós-i-Canas*

Only in recent years has there been any concentrated effort to reverse this, with the rise of ‘complete streets’, bicycle and pedestrian infrastructure, woonerfs and traffic calming. Technology is involved — electric micro-mobility provides more options for how people move about without involving cars, improved VR and AR helps designers better visualise what these spaces would look like to the user, modular and prefabricated street design elements and the adoption of thinking such as ‘tactical urbanism’ allows local communities to modify and adapt their landscape in short-term increments.

We are getting there slowly. We are reversing a fetish for the car, with its fast, independent mobility, ending the dominance of a technology over the needs and desires of those who inhabit the landscape. This is not easy to do, and it’s taken changes to our planet’s climate, a pandemic, and the deaths of tens of millions of people in traffic accidents (3.6 million in the U.S. since 1899). If we had better understood the implications of the first automobile technology, perhaps we could have made better decisions.

Let’s not make the same mistake with AI.

Not easy with AI

We have failed to make the right choices because we let the market decide. And by market here, we mean as much those standing to make money from it, as consumers. We’re driven along, like armies on train schedules

Admittedly, it’s not easy to assess the implications of a complex technology like AI if you’re not an expert in it, so we tend to listen to the experts. But listening to the experts should tell you all you need to know about the enormity of the commitment we’re making, and how they see the future of AI. And how they’re most definitely not the people we should be listening to.

First off, the size and impact of AI has already created huge distortions in the world, redirecting massive resources in a twin battle of commercial and nationalist competition.

Nvidia is now the third largest company in the world entirely because its specialised chips account for more than 70 percent of AI chip sales.
The U.S. has just announced it will provide rival chip maker Intel with $2o billion in grants and loans to boost the country’s position in AI.
Memory-maker Micro has mostly run out of high-bandwidth memory (HBM) stocks because of the chips usage in AI — one customer paid $600 million up-front to lock in supply, according to a story by Stack.
Data centres are rapidly converting themselves as into ‘AI data centres’, according to a ‘State of the Data Center’ report by the industry’s professional association AFCOM.
Back in January the International Energy Agency forecast that data centres may more than double their electrical consumption by 2026. (Source: Sandra MacGregor, Data Center Knowledge)
AI is sucking up all the payroll: Those tech workers who don’t have AI skills are finding fewer roles and lower salaries — or their jobs disappearing entirely to automation and AI.. (Source: Belle Lin at WSJ
China may be behind in physical assets but it is moving fast on expertise, generating almost half the worlds top AI researchers (Source: New York Times).

This is not just a blip. Listen to Sam Altman, OpenAI CEO, who sees a future where demand for AI-driven apps is limited only by the amount of computing available at a price the consumer is willing o pay. “Compute is going to be the currency of the future. I think it will be maybe the most precious commodity in the world, and I think we should be investing heavily to make a lot more compute.”

In other words, the scarcest resource is computing to power AI. Meaning that the rise in demand for energy, chips, memory and talent is just the beginning. “There’s a lot of parts of that that are hard. Energy is the hardest part, building data centers is also hard, the supply chain is hard, and then of course, fabricating enough chips is hard. But this seems to be where things are going. We’re going to want an amount of compute that’s just hard to reason about right now.” (Source: Sam Altman on Lex Fridman’s podcast)

*Sam Altman, 2022. Photo courtesy of Village Global*

Altman is probably the most influential thinker on AI right now, and he has huge skin in the game. His company, OpenAI, is currently duking it out with rivals like Claude.ai. So while it’s great that he does interviews, and that he is thinking about all this, listening to only him and his ilk is like talking to motor car manufacturers a century ago. Of course they’ll be talking about the need for more factories, more components — and more roads. For them, the future was their* technology. They framed problems with the technology in their terms, and painted themselves as both creator and saviour. AI is no different.

So what are the dangers?

Well, I’ve gone into this in past posts, so I won’t rehash them here. The main point is that we simply don’t enough to make sensible decisions on how to approach AI.

Consider the following:

We still don’t really know how and why AI models work, and we’re increasingly outsource processes of improving AI to the AI itself. Take, for example, Evolutionary Model Merge, an increasingly popular technique to combine multiple existing models to create a new one, adding further layers of complexity and opacity to an already opaque and complex system. “The central insight here,” writes Harry Law in his Learning from Examples newsletter, “is that AI could do a better job of determining which models to merge than humans, especially when it comes to merging across multiple generations of models.”
We haven’t even agreed on what AI is. There is as yet no science of AI. We don’t agree on definitions. Because of the interdisciplinary nature of AI it can be approached from different angles, with different frameworks, assumptions and objectives. This would be exciting and refreshing were it not simultaneously impacting us all in fast moving ways.
We don’t really know who owns what. We can only be sure of one thing: the big fellas dominate. As Martin Peers wrote in The Information’s Briefing (sub required):”It is an uncomfortable truth of the technology industry currently that we really have little clue what lies behind some of the world’s most important partnerships. Scared about regulators, Big Tech is avoiding acquisitions by partnerships that “involve access to a lot of the things one gets in acquisitions.” Look at Microsoft’s multi-billion dollar alliance with OpenAI and, more recently, with Inflection AI.

Not only does this concentrate resources in the hands of the few, it also spurs the ‘inevitability of the technology’, driven by those dominant companies who have sunk the most into it driven by dreams of the profitability that may come out of it . In short, we’re in danger of imposing a technological lock-in or path dependence which not only limits the range of technologies on offer, but, more seriously, means the most influential players in AI are those who need some serious returns on their investment, colouring their advice and thought leadership.

We’re throwing everything we’ve got at AI. It’s ultimately a bet: If we throw enough at AI now, it will solve the problems that arise — social, environmental, political, economic — from throwing everything we’ve got at AI.

We’ve been here before

The silly thing about all this is that we’ve been here before. Worrying about where AI may take us is nothing new. AI’s ‘founders’ — folk like John von Neumann, I.J. Good — knew where things were going: science fiction writer and professor Vernon Vinge, who died this month, coined the term singularity, but he was not the first to understand that there will come a point where the intelligence that humans build into machines will outstrip human intelligence and, suddenly and rapidly, leave us in the dust.

Why, then, have we not better prepared ourselves for this moment? Vinge first wrote of this more than 40 years ago. In 1993 he even gave an idea of when it might happen — between 2005 and 2030. Von Neumann, considered the father of AI, saw the possibility in the 1950s, according to Polish-born nuclear physicist Stanislav Ulam, who quoted him as saying:

The ever-accelerating progress of technology and changes in the mode of human life give the appearance of approaching some essential singularity in the history of the race beyond which human affairs, as we know them, could not continue.

The problem can be explained quite simply: we fetishise technological progress, as if it is itself synonymous with human progress. And so we choose the rosiest part of a technology and ask users: would you not want this? What’s not to like?

The problem is that this is the starting point, the entry drug, the bait and switch, for something far less benevolent.

Economist David McWilliams calls it the dehumanisation of curiosity — as each new social technology wave washes over us, it demands less and less of our cognitive resources until eventually all agency is lost. At first Google search required us to define what it was that we wanted; Facebook et al required us to do define who and what we wanted to share our day with, and Twitter required us to be pithy, thoughtful, incisive, to debate. Tiktok just required us to scroll. At the end it turned out the whole social media thing was not about us creating and sharing wisdom, intelligent content, but for the platforms to outsource the expensive bit — creating entertainment — to those who would be willing to sell themselves, their lives, hawking crap or doing pratfalls.

AI has not reached that point. Yet. We’re in this early-Google summer where we have to think about what we want our technology to do for us. The search prompt would sit there awaiting us, cursor blinking, as it does for us in ChatGPT or Claude. But this is just a phase. Generative AI will soon anticipate what we want, or at least a bastardised version of what we want. It will deliver a lowest-common denominator version which, because it doesn’t require us to say it out loud, and so see in text see what a waste of our time we are dedicating to it, strip away while our ability to compute — to think — along with our ability, and desire, to do complex things for which we might be paid a salary or stock options.

AI is, ultimately, just another algorithm.

We need to talk

We need to think hard about not just AI, but what kind of world we want to live in. This needn’t be an airy-fairy discussion, but it has to be one based on a human principles, and a willingness of those we have elected to office to make unpopular decisions. When back in 1945 UK Prime Minister Clement Atlee and his minister Aneurin Bevan sought to build a national health service free to all, they faced significant entrenched opposition — much of it from sources that would later change their mind. The Conservative Party under Winston Churchill voted against it 21 times, with Churchill calling it “a first step to turn Britain into a National Socialist (Nazi) economy.” (A former chairman of the British Medical Association used similar language). Doctors voted against it 10:1. Charities, churches and local authorities fought it.

*Anenurin Bevan, Minister of Health, on the first day of the National Health Service, 5 July 1948 at Park Hospital, Davyhulme, near Manchester. Photo courtesy University of Liverpool*

But Bevan won out, because as a young miner in the slums of southern Wales, he had helped develop the NHS in microcosm: a ‘mutual aid society’ that by 1933 was supplying the medical needs of the 95% of the local population, in return for a subscription of pennies per week. Bevan had seen the future, understood its power, and haggled, cajoled and mobilised until his vision was reality. The result: one of the most popular British institutions, and a clear advantage over countries without a similar system: In 1948 infant mortality in the UK and US was more or less the same — around 33 deaths per 1,000 live births. By 2018 the number had fallen to 3.8 in the UK, but only to 5.7 for the United States. That’s 1.3 million Brits that survived being born, according to my (probably incorrect) maths. (Sources: West End at War, How Labour built the NHS – LSE)

AI is not so simple. Those debating it tend to be those who don’t understand it at all, and those who understand it too well. The former fish for sound-bites while the latter — those who build it — often claim that it is only they who can map our future. What’s missing is a discussion about what we want our technology to do for us. This is not a discussion about AI; it’s a discussion about where we want our world to go. This seems obvious, but nearly always the discussion doesn’t happen — partly because of our technology fetish, but also because entrenched interests will not be honest about what might happen. We’ve never had a proper debate about the pernicious effects of Western-built social media, but our politicians are happy to wave angry fingers at China over TikTok.

Magic minerals and miracle cures

We have a terrible track record of learning enough about a new technology to make an informed decision about what is best for us, instead allowing our system to be bent by powerful lobbies and self-interest. Cars are not the only example. The building industry knew there were health risks associated with asbestos since the 1920s, but it kept it secret and fought regulation. Production of asbestos — once called the ‘magic mineral’ — production kept rising, only peaking in the late 1970s. The industry employed now-familiar tactics to muzzle dissent: “organizing front and public relations companies, influencing the regulatory process, discrediting critics, and manufacturing an alternative science (or history).” (Source: Defending the Indefensible, 2008) As many as 250,000 people still die globally of asbestos-related diseases each year — 25 years after it was banned in the UK.

*Operator Clémence Gagnon watches a machine carding asbestos fibre, Johns Manville factory, Asbestos, Que., 1944 Photo courtesy of Library and Archives Canada*

Another mass killer, thalidomide, was promoted and protected in a similar manner. Its manufacturers, Chemie Grünenthal, “definitely knew about the association of the drug with polyneuritis (damage to the peripheral nervous system)” even before it brought it to market. Ignoring or downplaying reports of problems, the company hired a private detective to discredit critical doctors, and only apologised for producing the drug, and remaining silent about the defects in 2012. (Source: The Thalidomide Catastrophe, 2018)

I could go on: leaded gasoline, CFCs, plastics, agent orange. There are nearly always powerful incentives for companies, governments or armies to use a technology even after they become aware of its side-effects. In the case of tetraethyl lead in cars, the U.S. Public Health Service warned of its menace to public health in 1923, but that didn’t stop Big Oil from setting up a corporation the following year to produce and market leaded gasoline, launching a PR campaign to promote its supposed safety and discredit its critics, while funding research which downplayed health risks and and lobbying against attempts to regulate. It was only banned entirely in 1996.

An AI Buildup

We are now at a key inflection point. We should be closely scrutinising the industry to promote competition, but we should also be looking at harms, and potential harms — to mental health, to employment, to the environment, to privacy, to whether AI represents an existential threat. But instead Big Tech and Big Government are focusing on hoarding resources and funding an ‘AI buildup.’ In other words, just at a time when we should be discussing how to direct and where to circumscribe AI we are locked in an arms race where the goal is to achieve some kind of AI advantage, or supremacy.

AI is not a distant concept. It is fundamentally changing our lives at a clip we’ve never experienced. To allow those developing AI to lead the debate about its future is an error we may not get a chance to correct.

Yes, we should care about Julian Assange

By jeremy | July 3, 2024

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*Still from Annotated short version, Collateral Murder, WikiLeaks*

It’s easy for most people — journalists included — to look the other way as Julian Assange’s case grinds to its (likely) grim end. He doesn’t fit neat holes — is he a journalist? An activist? A political operator? A source? An intermediary? A publisher? A whistleblower?

This means that those who are supporting his case are a rather motley bunch, from the left (the late John Pilger, Jeremy Corbyn, Noam Chomsky) to the far right (Tucker Carlson, Sarah Palin, for example). And then there are people in the middle, who feel that both principles and laws are being trampled upon. (Opposition to Assange is also a varied crowd, including Hillary Clinton and Mitch McConnell.)

This should create a broad coalition, but opinion towards Assange is not fixed. When a UN panel ruled in 2016 that Assange had been held arbitrarily by the UK and Sweden, two thirds of Britons surveyed disapproved the ruling. While there was crowd outside the court for deliberation on his extradition, a petition to grant amnesty to Assange posted on Avaaz.org in 2019, has been unable to reach 300 signatures and his name is nowhere to be found on the website’s homepage. Indeed, the sheer length of Assange’s case — running for 14 years now, since Swedish prosecutors issued an arrest warrant for him in 2010 — makes consistent support and publicity for his case difficult.

Chilling episode

So why should we care?

Whatever happens to him, Assange will leave a significant legacy. He changed journalism in a way most of us in the profession are reluctant to acknowledge. It’s now commonplace for journalists and newsrooms to actively solicit secret documents, and advertise the lengths they will go to to protect the source. While investigative journalism didn’t start with Assange, he helped usher in a minor revolution in the occupation — not least by the trove of stories written based on Wikileaks material. Journalists, in the words of Christian Christensen, a Sweden-based professor of media studies, should recognise that “Assange was a key part in the journalistic process, and by criminalising his participation you thereby criminalise that process.”

In my view, there’s one thing that Assange did that makes his freedom a moral requirement. It is his release on April 5 2010 of a video that Wikileaks called “Collateral Murder.” The 39-minute video, obtained by Chelsea Manning, is the view of a Baghdad street from an Apache helicopter gun-sight on July 12 2007, and in Wikileaks’ words “clearly shows the unprovoked slaying of a wounded Reuters employee and his rescuers.” The video, and the accompanying radio-chatter, combine to engrave a chilling episode in the history of warfare, comparable to the images of a Vietnamese girl, Kim Phúc, caught in a US napalm attack, the torture of Abdou Hussain Saad Faleh and other Iraqi prisoners in Abu Ghraib, or the image of the body of Syrian refugee Alan Kurdi, 3, washed up on a Turkish beach in 2015.

There’s a long backstory to (and fallout from) this case which I won’t repeat here. But certain points are worth stressing (I should declare an interest; I am a former Reuters employee, and I am friends with Dean Yates, the Reuters bureau chief in Baghdad at the time of the incident. Much of the following is taken from his 2023 book Line in the Sand; a statement by Dean was submitted to the court currently considering Assange’s extradition).

Hostile intent

Reuters had been shown only a small fraction of the recording in the wake of the killing, which in isolation seemed to support the US army argument that the helicopter crew had good reason to believe the group, which included two Reuters journalists Saeed Chmagh and Namir Noor-Eldeen, also had among them a man apparently carrying a rocket-propelled grenade, or RPG. They could be ‘engaged,’ Dean is told, because the presence of supposedly armed men was an expression of ‘hostile intent.’

Reuters was not allowed to keep a copy of the video or any of the material shown to Dean, and the company had been trying to obtain the video through legal channels unsuccessfully up to the time of its release by Wikileaks. The U.S. had blocked such requests at every turn, telling anyone who asked that it couldn’t be found.

The release of the full video by Wikileaks three years later showed several things: firstly, that the subsequent attack on the family trying to rescue the injured likely broke not only the Geneva Convention on attacking wounded, but also the military’s own rules of engagement. In his book Dean describes the video this way:

“It was pure truth-telling. No military officials could deflect, sanitise, provide ‘context’. There is also no tape like it from any war in history in public domain.”

This public domain aspect is key, and perhaps goes to the heart of Assange’s take-no-prisoners approach. Dean points out the only comparable video of an alleged war-crime happening is the execution of a communist Vietnamese prisoner, Nguyễn Văn Lém, by South Vietnam’s police chief Nguyễn Ngọc Loan on 1 February 1968. A photo of the moment when the is accessible enough, but the video remains the property of NBC and can only be obtained with special permission. “Everyone remembers the Pulitzer Prize-winning photo by Eddie Adams,” writes Dean. “But not the footage because it’s not a mouse-click away.”

Watching the execution of Nguyễn Văn Lém: from Mark Long, Jim Demonakos, and Nate Powell’s The Silence of Our Friends, via Interminable Rambling

Moving snapshot

When the video was first aired on NBC in 1968 it “led people to see major problems with the war,” in the words of Safia Swimelar, Political Science and Policy Professor at Elon University. “Many have said that photo and video also just illustrated the moral ambiguity of the war, since it showed that both sides were engaged in violence and possible war crimes.”

By making the Iraq video available with a mouse click, it could be argued Assange has ‘cheapened’ the content, desensitising us to its horror. But probably the opposite is true. We know that it’s there, a defiant finger to the authorities that tried to hide it from the families of the deceased and others seeking the truth about what happened, and, more generally, what the war in Iraq really looked like. It’s understandable that NBC wants to maximise its asset, but it could also be argued that it should by now — 56 years later — at least be in the public domain, a moving snapshot of the Vietnam War as much as Collateral Murder has come to define the Iraq conflict.

Neutral technology

It’s also clear that the U.S. knows it is on shaky ground. While it formed a key part of Chelsea Manning’s indictment, the video is not mentioned anywhere in Assange’s indictments. It’s likely that the U.S. really doesn’t want to go down that route: Much of the rest of Wikileaks’ (and Manning’s) material is that it shows professionals — soldiers, diplomats, analysts, spies — going about their work.

The secrets revealed, whether or not they’re in the public interest, are those that might embarrass a government or highlight its hypocrisy, or possibly endanger a U.S. official going about their proper business. Collateral Murder, on the other hand, exposes something different: not just the abuse of existing rules of engagement, but the absurdity of the “notion of neutral technology at the service of human development,” in the words of Christian Christensen, in a 2014 paper on the ‘afterlife’ of the video. Armies make particular effort to characterise their weaponry as smart in their behaviour, surgical in their impact, and while most of us know this is not really the case, it takes behind-the-scenes videos like this to remind us. Technology in war rarely reduces the harmfulness of a weapon, least of all for bystanders.

Secrets impose a cost, usually on the victim or their loved ones. To properly understand their wound they need to understand what happened, and why. For Dean the video’s release began a journey, illustrating on a micro-scale how the truth, however unpalatable, can set you free. Dean has struggled with PTSD and its brother moral injury, in part because he had not come to terms with the incident and his own feelings about the two men he lost on his watch. The release of the video — the full, unvarnished truth of the incident as it unfolds — highlights how damaging the keeping of secrets can be. In his struggle to come to terms with his PTSD Dean sought the forgiveness of the families of Saaed and Namir, and also tried to reach out to the occupants of the Apache as well, hoping they might share their stories too, and “help the healing” of everyone involved, including themselves.

It’s understandable the U.S. doesn’t want to start discussing all this in public again. But it also helps illustrate a truism that we too readily forget: that governments keep secrets for the wrong reasons — usually to conceal from their own citizens that rules have been broken. But at the same time it goes out of its way to punish as severely as it can any individual like Manning or Assange — pour encourager les autres. That, so far, hasn’t worked: Think of all the whistleblowers who have followed in Assange’s wake — Snowden, Antoine Deltour (LuxLeaks), Maria Efimova (Malta), Reality Winner (NSA), Frances Haugen (Facebook), Hervé Falciani (HSBC), Rudolf Elmer (Julius Baer), the still anonymous Panama Papers leaker, Xavier Justo (1MDB), Howard Wilkinson (Danske Bank), nearly all of whom have through their bravery helped launch investigations and/or changes in policy, despite great peril to themselves and the journalists who report their stories. (Maltese investigative journalist Daphne Caruana Galizia was assassinated in 2017 for her work based on Efimova’s whistleblowing.)

Do we deserve the sacrifice?

By releasing the video Manning and Assange wrote themselves into the history books, showing the graphic truth of what advanced U.S. military power looks like in practice. Perhaps, 14 years on, we are still too close to it to recognise the impact of that truth — or perhaps we have too readily forgotten it. Both understood the gravity of the material in their hands — after retrieving the video Chelsea Manning immediately searched for the rules of engagement each occupant of the helicopter would have been carrying — but perhaps neither may have thought too deeply about the personal sacrifice they would ultimately be making. We should not blame them for that.

Still from Dunkirk (1958) , directed by Leslie Norman

In 1958 Michael Balcon of Ealing Studios produced a fictional film based around the evacuation of Dunkirk, not because he wanted to eulogise the recent past, but because he wanted to disturb audiences, which he felt by the late 1950s had grown complacent, individualistic, unworthy of the sacrifices made for their benefit. He wanted them to ask themselves: “Was Dunkirk worthwhile? Have we deserved the sacrifice? Do we remember what war is?” Assange’s fate is in our hands, and Collateral Murder is the evidence of sacrifices made — both by the people killed or wounded that day, and by a handful of individuals to bring that crime to light — that we should not ignore.

Why do journalists destroy those they love?

By jeremy | February 16, 2024

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There’s a moment in Lynn Alleway’s documentary “Camila’s Kids Company: The Inside Story where Camila Batmanghelidjh emerges from a UK parliamentary grilling and the paparazzi are there, calling out her name as if they know her personally — “Camila! Camila!” — to get the best shot. Batmanghelidjh stands on the steps of the building, her smile wobbling. This moment would mark the end of her career as what one Labour MP called the “poster girl” for a new way of helping those in need. It also marked the beginning of the end of her life.

I explore her case to illustrate another chapter in “How Journalists Think“, with the question: Why does journalism tend to destroy those it once adored? How do these stories develop in the newsroom, and is it something that can be anticipated by those trying to protect those figures from public damnation?

Perhaps that’s too facile a way of putting it. Boiled down, the arc is this: Journalists are always looking for something — or someone — remarkable, that allow themselves to become, or courts the media in helping them become, a ‘celebrity’ figure. In a lot of cases the celebrity status is the end in itself, but it can also be a means to an end. For such people being a celebrity is a useful step in serving some other purpose — usually promoting something they are trying to sell. In the case of Batmanghelidjh, it was trying to sell a new approach in helping the disadvantaged to deep-pocketed politicians and high-net worth individuals (including celebrities.)

Squeeze out the anger

The story of Camila Batmanghelidjh is, briefly this (here’s a much better telling of her story): A Iranian-Belgian, she was educated in England and made it her home. She developed an approach for abused and damaged kids that was startlingly different to how others looked at them: embrace them, she preached. And she would, squeezing a lot of the anger and hatred out of those she worked with. She also believed in giving out cash: she was extremely generous with those she felt needed her largesse, arguing that having, not just basic necessities, but also nice things was part of restoring self-esteem.

UK PM David Cameron and Labour MP Frank Field with Batmanghelidjh, in Liverpool, 2010 (Demos, CC)

She made enemies from the get-go, but she also made powerful friends, and where she could she used those connections to draw funding, expanding her small charity in Peckham to a multi-million pound operation that at its height, she said, was looking after 36,000 ‘clients.’ She was showered with awards and high-profile photo-ops. Her fall from grace was fast: allegations of abuse piled onto allegations of financial mismanagement, and, although she and the charity were largely exonerated, that came too late to save either. Batmanghelidjh died on January 1, 2024, less than a decade after Kids Company had collapsed.

For a journalist there are five main phases to her story.

Niche: interest is largely confined to specialist media and journalists covering poverty, inner cities, social benefits etc. Her dramatic profile may actually work against her at this point, because it may be considered frivolous and attention-seeking. A word like ‘controversial’ might be used in coverage, which can have both good and bad connotations. Being controversial means the subject is worthy of coverage in the journalists’ mind.
Media Darling: As soon as she appears in public alongside senior politicians (including prime ministers and future kings) she enters a different kind of coverage, covered by a different kind of journalist. At this point she becomes a visual and written subject in her own right, and courting the media has advantages for both sides. She is able to attract funding on the back of this, and that in turn becomes part of her media appeal.
Pivot point: She will also attract the counter-force by those questioning the veracity of her claims, and those journalists who spot a possibility of challenging the image she now has in the media. This is the point at which things could go either way. The investigative stuff will force other journalists to include language like “sometimes controversial” as they prod the edges of their previously positive coverage: given the established nature of the story words like “controversial” are no longer a good thing.
The Slide from Grace: Momentum builds and if there’s enough material, the negative stories will pile up on one another inexorably. This is where Batmanghelidjh loses control of how she is perceived and gradually (and sometimes quickly) the tide will turn against her, and journalists who once wrote positively about her will fade away.
Coup de grâce: This is when journalists draw a line under the story, where essentially the subject is covered with their name preceded by words like scandal-hit, disgraced, bankrupt and where that becomes the justification for the story. No longer is the subject able to affect how journalists cover the story. In Batmanghelidjh’s case, this period lasted from late 2015 to her death.

The demon of Peckham

I’m not saying that these are the only stories to be told, but a journalist swimming against the tide in any particular phase will find it a hard sell to editors. A journalist in the first phase would probably approach it as a visual story, as Batmanghelidjh was photogenic, charismatic and playful. This would help move the story from the ‘community’ pages to the more commanding ‘social’ pages. Likewise, once the negative reports start to ooze out it would be a brave journalist who might try to write a ‘yes, but’ story which presented Batmanghelidjh’s case that the charges were politically motivated and without substance.

Something worth noting here: a symbiosis can emerge where journalists find themselves in alliance with groups within the story. Batmanghelidjh won a lot of friends and attracted a lot of funding, but that in turn put noses out of joint, and may also have raised legitimate concerns about her work. The journalists who were first to follow up on sources or hunches that not all was as it seemed fed their findings to local councillors, creating a positive feedback loop in which both were emboldened to investigate claims.

Camila Batmanghelidjh plenary questions with Sarah Montague, NHS Confederation annual conference & exhibition 2011, creative commons

It’s instructive to watch the documentary to see how Batmanghelidjh handled all this. She courted Alleway, a documentary maker who had previously released a glowing documentary about her a decade earlier, to follow her and video the process by which she hoped to spike the guns of her detractors and turn her financial problems around. It’s clear early on that while she directs events as much as she can, she is severely underestimating the hole she is in, and even a sympathetic documentary maker starts to lose faith both that Batmanghelidjh will manage her conjuring trick — and that she is being wholly honest about where the money is going. It’s a painful ride. Batmanghelidjh seemed to grasp the Shakespearian dynamics of her story but not the need to take her detractors seriously: “It’s revenge, round one,” she tells Alleway. “They are about to murder the very thing that works.” And then, later: “They made me the angel of Peckham and now they’re going to make me the demon of Peckham.”

“This one is bad”

Batmanghelidjh does have a media strategist and head of PR, but it’s clear that he has little control over what Batmanghelidjh says or does — even, I sense, over whether he was consulted about allowing a documentary maker fly-on-the-wall access. His efforts to tighten whatever is coming out of the charity in emails and statements, let alone what is coming out of Batmanghelidjh herself, bear little fruit. Batmanghelidjh’s charisma and passion are not enough to save her when she is dragged before a parliamentary committee, conveying vagueness and umbrage in equal measure.

Could she and her advisors done better? Easy to say with hindsight, but it’s clear from one scene that the team is selective in which journalist it responds to. They struggle over a response to allegations that Batmanghelidjh’s driver has received significant funds despite his limited function, but even as the PR manager, Laurence Guinness, tries to prepare a statement Batmanghelidjh, painting her nails bright red, suggests they mention she uses another driver for other trips. Guinness is quick to scotch that, pointing out that “the bill for that runs into 30, 40,000 (pounds) a year…” Then a story comes through about a house with swimming pool that is being rented, and they look at the iPad together. “Oh no, this is the one that is bad, very bad,” he says. “I just ignored him.” And they decide to continue to ignore him.

The story is a fatal blow, and it would have been written with or without their being involved. And when the documentary maker is shown the house and swimming pool in question, it’s clear to both her and the audience that Batmanghelidjh’s description of the pool as tiny is incorrect. It is after this story that her credibility collapsed. There’s nothing really that Guinness could have done — although you might have hoped they would have realised early on in this part of Batmanghelidjh’s trajectory that losing the house might have been a good move.

The truth is that once the tide turns nothing can stop it. Soon after one or two stories land other journalists will be under pressure to distance themselves from previous glowing stories about her, either by staying quiet or by finding ones that float with the turning tide. A good PR would be asking for keys to the skeleton cupboard to anticipate what story might be next, and threaten to walk if the keys aren’t provided. But when your boss, rather than the organisation, is the story, that’s often hard to do. But at least recognising the warning signs of a turning tide might help you be better prepared. A fly-on-the-wall documentary maker might seem like a good idea, but even if they produce something sympathetic, it’s not going to be done in a timeframe that helps, and it may anyway not help move the needle.

Charisma and elbows

This is another reason why I am not a fan of PR thinking up, or thinking in terms of, ‘narratives’ for their clients. Batmanghelidjh at her best was a great story, because she challenged so many orthodoxies. Her charisma attracted political patrons who sought to capture some of that charisma, so a photo of her sitting next to Prime Minister David Cameron in the cabinet room at 10 Downing Street is media gold. The reality behind the picture is a little different: Batmanghelidjh was enticed into that chair and for her the meeting itself lacked substance. She found the wives of political figures much more in tune with what she was trying to do. But those contacts enabled her to short-circuit usual funding routes and attract both large-scale grants as well as envy, disdain and grudges from those elbowed out to make way.

A journalist will see what they want to see, and it’s a PR person’s job to try to shape that. They will follow closely the 4 steps I’ve listed above, and any attempt to alter that substantially will fail. What can be done is to recognise both the advantages and pitfalls of allowing a charismatic leader to overshadow the organisation they are fronting. In many cases this is impossible. But by allowing media and leader to dance together into the stratosphere, there is only one way left to go, and that’s down. For one thing it makes both founder and organisation hostage to fortune: the more successful they are, the sooner the organisation will need more professional hands running it, creating a well-known challenge called founder syndrome. In Batmanghelidjh’s case it was obvious within a few seconds of the documentary beginning that she presided over something that had become a monster — miles of expensive office space, lots of employees at computers more redolent of a blue chip company than a scrappy NGO — and that her fate was sealed.

Better counsel would be to gradually limit media access to Batmanghelidjh herself and focus on the more professional side of the company, making scale the next version of the story, and the calibre of those being brought in to help. In other words, a more solid strategy would be to dial down the story about Batmanghelidjh and dial up the story about scale and next steps — and to start strategising what negative stories journalists might be looking for and help to neutralise them. Frankly, ignoring a journalist asking about a negative story never ends well as we’ve discussed before.

Do journalists feel bad about what they do? Some. It’s not a nice feeling to see someone you’ve written about impacted by your story, even if the story was the truth and a corrective to public perceptions. I’ve had the daughter of a prominent figure I wrote an exposé about weeping as she asks me why I hated her father so much. We always say it’s not personal, but it sometimes is. One journalist who led the investigative work which started the unravelling, Chris Cook, wrote on Twitter after her death that “61 is no age, and she was gifted at dealing with tough young people – but should not have got £40mn+ in public funds.” Perhaps unsurprisingly, the tweet prompted some strong responses.

Journalism is never definitive. It’s always the best effort at the time, in the time allowed. I suspect that at some point attention will return to her ideas, laid out in several books, and she will be regarded as a visionary of sorts. Unfortunately there’s no room for that kind of journalism until we build a decent time machine.