a blog by Ian Kennedy
Anthropic, makers of AI Assistant Claude, is going after their competition with a series of ads to designed to give users pause after the Open AI’s announcement that ads would be coming to their product, Chat GPT.
The campaign, Time and a Place, was envisioned by Mother London, extending Claude’s positioning from the Keep Thinking campaign.
The ads launched yesterday, timed for this weekend’s Super Bowl, which will feature two of the spots as detailed by AdWeek.
Tried something different this year, asked ChatGPT to summarize the year for me.
One benefit of having the entire archive of this blog part of OpenAI’s learning model is that it can spit back what it’s learned, not only in substance but also in tone. It’s uncanny.
Here’s how ChatGPT responded:
Absolutely — based on Ian Kennedy’s actual writing on everwas.com (which covers tech policy, AI’s impact on the open web, local NYC issues, and personal essays), a hypothetical 2025 Year-in-Review blog post from him would blend thoughtful analysis of tech trends with sharp local and cultural commentary.
Here’s how Ian Kennedy of everwas.com might write a “2025: A Year in Review” post:
2025 felt like the year the internet finally stopped pretending it was the open playground of ideas and began behaving like what it’s actually become: a contested battleground where ownership, access, and value are constantly being negotiated — not just by corporations, but by governments, communities, and the technology itself.
At the start of the year, conversations around artificial intelligence were dominated by shiny demos and sci-fi ethics. By year’s end, the conversation shifted to who owns the data and who gets paid for it.
Policy makers, IAB task forces, and publishers around the world began framing the debate in terms of rights and compensation, not just innovation. The old model where content was indexed freely by search and repurposed by AI is now being replaced by a future where:
This wasn’t just theory — it became a reality for countless newsrooms and creators struggling to survive in an era where AI can answer queries without sending anyone to click a link.
Machine learning isn’t just a software problem. The massive energy demands of data centers pushing GPUs to their limit became a real infrastructure challenge this year. We saw:
The future of “compute anywhere” suddenly looks a lot more tied to where the electrons actually come from.
Living in this city means Local often becomes National. In 2025 New York city was a microcosm of the larger cultural and political shifts:
The city didn’t just make headlines — it embodied the tension between grassroots citizen engagement and centralized power.
2025 also saw a subtle but unmistakable shift in how technology and culture engage:
It’s hard to overstate how much that matters. When ordinary people begin arguing about the future of search and discovery, the underlying structure of the web itself has already changed.
Beyond the geopolitical and technological, 2025 was also a year of small perspectives — hikes, travel, and moments that reveal a deeper truth about why culture still matters even when platforms shift.
Whether it was a hike near Kamakura or a rumination on a slow waterfall (ed. this is a pretty funny interpretation of this post), these personal essays reminded readers that tech is not just code — it’s lived experience.
If 2025 taught us one thing, it’s this:
The next year won’t be about whether the web changes — it’ll be about who gets to shape that change.
Here’s to the debates, the fights, and the small stories that make it all worth caring about.
It was one of those nights New York throws at you in midwinter, minus seventeen degrees, the kind of cold that silences everything. Pianist Gohei Nishikawa was home alone, the TV murmuring in the background, when he realized too late that he’d forgotten to lock his front door.
The sound came first, a soft rattle, the kind of noise that pulls you out of your half-attentive state. Then, before he could even reach the hallway, the door burst open. Two men shoved their way in, one an older, broad-shouldered African-American; the other, tall and wiry, maybe Latino, definitely younger. Neither had a gun. Instead, one held up a clear plastic case with a syringe inside, the kind of improvised threat that feels even more dangerous for its uncertainty.
Gohei froze, hands instinctively in the air. The younger man started sweeping through drawers and shelves, stuffing things into a bag, an iPad, wallet, whatever he could grab. The fear was real, sharp as the wind outside. But then, as the adrenaline began to settle, something unexpected rose in him, curiosity.
He had once studied to be a teacher before his life turned to music, early childhood education, educational psychology. He found himself wondering, what kind of childhood leads someone to walk into a stranger’s apartment with a syringe?
Against every instinct of self-preservation, he asked.
“Can I ask you something?”
The younger man barked back, “Shut up!” His voice was rough, not just angry but wounded. Gohei apologized. “I was just wondering what kind of childhood you had.”
That question hung in the air. The man froze, then finally said, almost quietly,
“You know pain?”
“What kind of pain?”
“I was four,” the man said. “My real mom used to beat me. Then I got put in foster care. My parents left me. I was homeless. You know that kind of pain?”
Gohei, who’d spent years teaching four- and five-year-olds, felt tears sting his eyes. “You’ve been through a lot,” he said softly. “Take whatever you need.”
They did, even started to haul out the TV. But watching their backs, he felt something else: not fear, but a strange tenderness. If that’s the life they’ve lived, he thought, maybe this is the only way they know to keep living.
He surprised himself again:
“Can I give you a hug?”
“Don’t come closer!” they shouted.
Then the older man, the one holding the syringe, asked,
“You Japanese?”
“Yes,” Gohei said.
“I like Japanese people,” the man said gruffly, “You all got a kind culture.”
Something about that moment — there, with his hands still raised — felt absurd and profound at once. Complimented on his culture by the man robbing him. So very New York.
And so, in perfect Japanese fashion, he made an offer.
“I have some green tea from Japan. Would you like to try it?”
To his shock, they both said yes.
He boiled water, his hands trembling so badly the kettle clattered, and brought out some rice crackers. When they smiled and said thank you, he found himself laughing too. They talked. And kept talking. For eight hours.
At some point, they noticed a poster on his wall of a Carnegie Hall performance.
“You played there?”
“In the small hall.”
“What’s that? There’s a small one?”
He explained, and the older man admitted he’d never been inside a concert hall, only ever seen one from the outside. The younger one said quietly, “It’s my birthday today. Play something.”
So Gohei sat down at his piano and played Happy Birthday.
The man cried.
“No one’s ever played for me before,” he said.
Gohei kept playing — a full hour of impromptu recital in the dead of night for two men who’d broken into his home. When he finished, he realized it was still below freezing outside.
“You can’t go out there like that,” he said. “Why not take a hot bath first.”
That’s when the miracle happened. The two robbers, noticing his broken heater, started fixing it. Then they repaired a loose window latch, warning him, half-joking, “A thief could get in through this!”
When they finally left, they hugged him, their idea this time.
The older man looked him in the eye and said,
“Yo — lock your damn door next time.”
They made two promises that night: He wouldn’t call the police, and they’d find honest work.
“If I ever get to play in Carnegie’s main hall,” Gohei said, “I’ll invite you both as VIP guests.”
They exchanged phone numbers.
A year passed. One morning, Gohei’s phone lit up with a message:
“Am I still invited?”
The sender’s name read simply: Dorobō — “Thief.”
He’d seen Gohei’s Christmas concert on TV — a solo performance at Carnegie Hall’s main stage.
“Congratulations,” the message said. “I’m still waiting for my invitation.”
Gohei called the concert organizer, explained everything. The response was pure New York pragmatism:
“You made a promise. Keep it.”
And so, he did. The two men came, wearing suits. They sat in the same box seats once reserved for presidents and royalty. Afterward, they sent a long email:
“Thank you. I’ve been working in cleaning since then, saving money. I finally bought a used car, Made in Japan. I wanted to show you.”
Gohei laughs now when he tells the story. People ask if he made it up. He didn’t.
“I don’t know if it was the right thing to do,” he says. “But I learned that night — if you try to understand someone instead of hating them, things somehow work out.”
Later, one of the men told him he was the first person ever to ask about their childhood. The first who didn’t shut him out.
Somewhere in New Jersey, one of those men, maybe both, is still out there, driving a secondhand Japanese car, cleaning office buildings. And every once in a while, a pianist in New York remembers a winter night when a robbery turned into something like grace.
This post is a translated transcription of an Instagram reel excerpt from an story told by pianist Gohei Nishikawa. I used Summary AI to transcribe the Japanese text and Chat GPT to translate the dialog into English and transform it into a blog post “in the style of Ian Kennedy’s blog everwas.com” which I lightly edited (mostly removing the em-dashes).
Source Material
Cloudflare sees about 20% of the world’s internet traffic cross its network. Matthew Prince, CloudFlare’s CEO, has a pretty good handle on trending internet behavior.
In the video below, he summarizes the impact of AI “answer engines” that summarize what they find in response to questions put into AI chatbots such as Google’s AI Overview or Open AI’s Chat GPT.
What he concludes is that the exchange that allowed the search engines to index a site in return for referred pageviews is no longer equitable and is growing increasingly lopsided.
The data, according to Cloudflare;
No one is saying is what we all know in our hearts. No one is clicking through to the footnoted sites on an Answer Engine. The AI crawlers are taking more than they are giving back.
It’s worth watching the entirety of Matthew’s talk in context of an announcement he references in the video. I expect it will be something related to their Bot Management suite. But I also look forward to hearing more about CloudFlare’s vision to remake the internet into one that rewards knowledge creation.
While the introduction of AI Answer Engines is a current and immediate threat to the online publishing ecosystem as we have known it, there is a nascent opportunity to re-build the internet on a new ecosystem built around different incentives.
What if we rebuilt the internet into one that rewarded Knowledge and not Attention. The “attention economy” brought us clickbait and distraction. What if we rebuilt the internet into one that rewarded publishers that gave more than they took away? Am I naive?
I am looking forward to learning more about CloudFlare’s plan.
Update: I was there!
In honor of Gene Hackman, I re-watched his classic role as the gritty NYC detective, Jimmy “Popeye” Doyle in the 1971 film, The French Connection. As any New Yorker will know, many of the locations in the film are familiar but the passage of time has made it harder to pinpoint exactly where.
Enter Perplexity Pro. Here is the first of what I think may be a series of AI-augmented blog posts called, “Cool things I asked AI.”
What follows is the output from Perplexity from my prompt
Where in NYC was the French Connection filmed?
The 1971 film “The French Connection,” directed by William Friedkin, is widely celebrated for its authentic portrayal of New York City’s gritty landscape during the early 1970s. This groundbreaking crime thriller, which won five Academy Awards including Best Picture, utilized numerous locations throughout the five boroughs to create its distinctive documentary-like atmosphere. Before beginning my detailed exploration of the film’s New York City locations, it’s important to note that “The French Connection” stands as one of the most ambitious location shoots ever undertaken in the city, utilizing 86 separate filming sites and capturing a New York landscape that has substantially changed over the subsequent decades.
Manhattan served as a critical backdrop for many pivotal scenes in “The French Connection.” The film effectively utilized various neighborhoods to establish the urban landscape against which the drug trafficking investigation unfolds. One notable location was Le Copain restaurant at 891 1st Avenue, where Charnier dines during a key sequence in the film. The busy streets of midtown provided several important settings, including the scene where Doyle waits outside a restaurant near 50th Street and First Avenue.
The affluent Upper East Side was featured prominently, with Weinstock’s apartment filmed near 82nd Street and Fifth Avenue, close to the Metropolitan Museum of Art. This upscale neighborhood also housed the Westbury Hotel at 15 East 69th Street, which served as Charnier’s accommodations in the film. Another significant Upper East Side location was Ronaldo Maia Flowers at 27 East 67th Street, where the clever Charnier gives Detective Doyle the slip in one of the film’s most tension-filled moments.
The Roosevelt Hotel at 45th Street and Madison Avenue appears in a critical scene when Detective Russo first encounters “Frog One,” Alain Charnier. Grand Central Terminal also features prominently, with the 42nd Street Shuttle platform serving as the setting for a tense pursuit sequence. The Lower East Side, with its unique character and gritty atmosphere, provided several important locations, including Ratner’s Restaurant at 138 Delancey Street, a famous Kosher deli where Sal and Angie emerge during surveillance. According to location historians, Ratner’s was once a hangout for gangsters Meyer Lansky and Bugsy Siegel before it finally closed its doors in 2002.
Additional Manhattan locations included scenes shot in Little Italy, specifically at the 177 Mulberry Street drop point, and the foot of Manhattan Bridge at South Street and Market Street, where Doyle is shown emerging from a bar in his disheveled state.
Brooklyn provided some of the most memorable locations in “The French Connection,” most notably the setting for what many film historians consider one of the greatest car chase sequences in cinematic history. This iconic chase was filmed in Bensonhurst, Brooklyn, running under the BMT West End Line (then the B train, now the D train). The sequence specifically follows Stillwell Avenue, continues along 86th Street, and then turns right onto New Utrecht Avenue, culminating near the 62nd Street station. This complex action sequence took an astonishing five weeks to film and has become an enduring piece of cinema history.
Beyond the chase, Brooklyn offered numerous other locations that contributed to the film’s authentic atmosphere. Bushwick provided the setting for Sal and Angie’s Cafe at 91 Wyckoff Avenue. The now-demolished Rio Piedras theater at 914 Broadway on the Bushwick/Bed-Stuy border served as the location for the opening Santa Claus chase sequence. According to historical records, this was originally the Loew’s Broadway, built in 1904 with seating for 2,000, before being torn down in 1988, leaving a vacant lot in its place.
The Marlboro Housing Project, located near Avenues V, W, and X off Stillwell Avenue, was used to represent where Detective Popeye Doyle lived. Other significant Brooklyn locations included Columbia Heights at Squibb Hill, where Sal parks the Lincoln automobile that contains the smuggled heroin, and Remsen Street, where Charnier and Nicoli observe the car being unloaded.
While Manhattan and Brooklyn received the most screen time, “The French Connection” utilized locations throughout the city’s other boroughs as well. In Queens, several scenes were filmed in the Ridgewood neighborhood, specifically along Forest Avenue and Putnam Avenue, as well as Onderdonk Avenue. The film also shot scenes in Maspeth, creating a comprehensive view of the borough.
The Bronx was represented in the film through scenes shot in the Hunt’s Point area, though these locations weren’t as extensively used as those in other boroughs. Two island locations proved critical to the film’s narrative: Randalls Island in the East River appears in several sequences, while Wards Island served as the setting for the film’s climactic final shootout.
The Triborough Bridge to Randall’s Island toll bridge at the east end of 125th Street was used for scenes where Sal Boca is tailed by the detectives. This infrastructure element helped connect the film’s various geographical components while providing a stark visual backdrop for the unfolding investigation.
“The French Connection” captured New York City during a particularly challenging period in its history. As noted by filming location experts, the city’s decay is front and center in nearly every frame, from “abandoned, grime-covered buildings and derelict cars to crumbling warehouses and trash-strewn lots”. This visual representation of urban decay provided an authentic backdrop for the story’s dark themes.
Producer Philip D’Antoni faced significant logistical challenges during production, as the film was shot primarily during New York’s unpredictable winter months of December through February to match when the actual events occurred. These weather conditions added another layer of difficulty to an already complex location shoot but contributed significantly to the film’s realistic atmosphere.
It’s worth noting that the film provides a fascinating historical document of the city’s appearance during this period. Some shots even captured the World Trade Center under construction, with the completed North Tower and partially completed South Tower visible in background scenes at the shipyard after Devereaux arrives in New York.
Over the decades since filming, many of these locations have undergone significant changes. The beautification of New York City over the past 25 years has come at a price, with many classic New York establishments and mom-and-pop stores replaced by more generic businesses. The gritty New York captured in “The French Connection” largely exists only in films now, providing an important historical record of the city’s visual character during the early 1970s.
“The French Connection” stands as a landmark achievement in location filming, utilizing the authentic landscapes of New York City to create a visceral, documentary-like crime thriller. The film’s extensive use of real locations throughout Manhattan, Brooklyn, Queens, the Bronx, and the city’s islands provided viewers with an unvarnished look at urban America in the early 1970s. From the iconic car chase beneath Brooklyn’s elevated subway lines to tense surveillance sequences in Manhattan’s diverse neighborhoods, the city itself becomes a central character in the narrative.
Beyond its cinematic achievements, “The French Connection” serves as an important visual document of New York during a specific historical period, capturing landscapes and establishments that have since been transformed or disappeared entirely. The film’s commitment to location shooting contributed significantly to its enduring impact and continues to influence filmmakers seeking to capture authentic urban environments on screen.
Sources
[1] The French Connection (1971) – Filming & production – IMDb
[2] Photographing The French Connection – American Cinematographer
[3] The French Connection (film) – Wikipedia
[4] The French Connection | Plot, Cast, Awards, & Facts | Britannica
[5] The French Connection (1971) – IMDb
[6] Filming Locations for The French Connection – Movie Locations
[7] French Connection II – Wikipedia
[8] Filming Locations of The French Connection – MovieLoci.com
[9] French Connection Tour – Tapatalk
[10] The Filming Locations of The French Connection, Then and Now
[11] The French Connection Film Locations
[12] French Connection – Wikipedia
[13] Jimmy “Popeye” Doyle – Wikipedia
[14] The French Connection (film) – Wikiquote
[15] Exclusive | Secrets of ‘The French Connection’ on 50th anniversary
Last September, I gave a talk at the Media Party conference in New York to propose a method to track the origin of text as it travels through a Large Language Model (LLM). Tracking provenance is important because to evaluate reputation and assign credit to properly allocate licensing revenues to publishers that provide source material to an LLM.
What follows are the slides from the talk with some annotations to help explain.
The rough outline of the proposal is a simple type of HTML markup which allows the publisher or author of a page to mark unique phrases, facts, quotes or figures for which they would like to retain credit. This markup, if retained along with the indexed text, would allow the LLMs to store and trace the origin of these unique phrases back to the originating url or domain tracking the “knowledge” as it travels from the originating website to an LLM and then back out via a genAI chatbot in the form of an “answer.”
Setting some historical context, I explained how incentives can shape ecosystems . The pageview & advertising economy of online publishing incentivizes publishers to seek out traffic and has given rise to an ecosystem that put Google and their “ten blue links” at the center. A link drives traffic and traffic drives ad impressions which equals revenue in this ecosystem.
This well-established ecosystem is being upended by AI chatbots which efficiently extract knowledge from a page and serve it back to the user without generating a pageview. This cuts out an important way for publishers to make money, grow audience, and promote their brand.
To get a jump on this new ecosystem, large publishers are cutting deals with the AI companies but only the biggest will have the resources to benefit from such arrangements. Smaller publishers will be left out.
SimpleFeed (where I work) released a simple WordPress plugin that monitors your site to see who is crawling your site and allows the site admin to block selected bots. The idea is to educate smaller site owners how much indexing is going on and build awareness of how the LLMs are interacting with their content.
According to CloudFlare, bots make up 30% of a site’s traffic and this figure will surely increase.
Referrals from social networks are falling. This puts pressure on site owners who wish to control who comes to crawl their site. Who do you let in, who to block? The act of publishing something is to distribute your information far and wide but, right now, many are defending their sites from aggressive crawlers strip-mining their sites without compensation.
If we plot this situation to it’s conclusion, the largest publishes will survive off of whatever licensing terms they can secure while the smaller sites get starved of traffic and miss out on any significant licensing revenue. The result is that we lose the diversity of the web. This leads to the gentrification of anything going into and coming out of the LLMs. This is what is called, an ecosystem collapse.
Tim O’Reilly is my North Star when it comes to understanding technological tectonic shifts. Much of my thinking here is inspired by an O’Reilly piece, How to Fix “AI’s Original Sin” in which he writes about how incentives can influence ecosystem design and how pageview incentives of past result in the block & tackle behavior of publishers towards the LLM platforms today.
The challenge for the LLMs to break out of this cycle is to create a system for “detecting content ownership and providing compensation” so that LLMs can share the enormous, untapped potential everyone anticipates for the LLM platforms. In O’Reilly’s words,
This is one of the great business opportunities of the next few years, awaiting the kind of breakthrough that pay-per-click search advertising brought to the World Wide Web.
In the world of digital art (audio, photos, videos), the people and companies behind Content Credentials are already hard at work in creating this system.
If a picture is worth 1,000 words, there must be value assigned to text. If something has a value, it’s worth tracking. I propose a few elements worth tracking. Quotes, Statistics, and even unique phrases.
The next few slides told the story of how, when blogs and blogging were just getting started, there was a huge problem with comment spam. This was largely the result of incentives to get a high reputation site to link back to the commenter’s website to help improve their ranking in Google’s search results.
Over the course of a few days (the internet was a smaller place back then), engineers at Google and Six Apart (where I worked at the time) agreed to negate the relevance of the link back to the commenter’s site on a comment and dealt a blow to the comment spam problem. A small group of engineer’s extended the web and, in a very simple way, removed the incentives that rewarded bad behavior.
I told this story because I see the rel= link qualifier as something that could be used to markup text and prove provenance. I proposed something called a “knowledge unit” or KU for short.
The syntax of the markup worked alongside HTML, just bracket anything you want to track in the rel=ku markup and, as long as the consuming LLM keeps that markup intact, that text will be tagged as something originating from the url cited in the markup.
This provenance can be used to track the number of times a particular knowledge unit is mentioned in an LLM’s response. This enables a fundamentally different ecosystem from that of pageviews in that there is no need to constantly re-post something you wrote years ago to keep it fresh, relevant, and trending in Google’s search results. Hard work to produce durable knowledge should pay dividends on into the future.
More akin to the Wikipedia reputation model, a good, unique fact can continue to be cited over time and, in fact, revenues should flow towards durable knowledge units and will hopefully reward those that gather and present unique knowledge rather that the hot takes and re-writes that are rewarded in today’s pageview economy.
Taken a step further, we will then return to a web before ad targeting and enragement metrics to a world where we reward those that teach us something new.
This new internet no longer drives you to “acquire” a “user” to package up and sell to an advertiser. Publishers no longer need to lock their stories behind a paywall to prevent non-monetized access. In this new ecosystem, the incentive is to share knowledge, getting paid directly for the broad distribution and citation of your work.
This is just the germ of an idea that may well be totally naive. While I do like the bottoms-up, simplicity of the markup approach, it requires everyone to adopt and trust each other to collectively make it work.
What is to keep bad actors from hijacking Knowledge Units and claiming something as their own? Page index timestamps will need to be the arbitrator of provenance I suppose but how do you guarantee delivery of your post over others?
Also, why would LLMs adopt such a system that would fundamentally make their indexes more complex and expensive? My hope is that the LLMs eventually see that strip-mining the web is unsustainable. Just as in agriculture, an ecosystem that does not replenish it’s resources, both large and small, is not a diverse, healthy, and long-lasting ecosystem.
If you’ve made it this far, I’m super-interested in your thoughts and encourage you to get in touch.
Going through some papers from this year’s Online News Association conference in Atlanta, I found this handout put together by the folks at Verify.
I couldn’t find any reference to it online so I thought I’d post it here for posterity.
Tim O’Reilly popularized the term “Web 2.0” to explain the network effects of the participatory web enabled by dynamic web pages tied to personalization. He is excellent at summarizing large technical trends in a way that not only makes it relatable but also provides a useful framework when I need to explain these concepts to others.
So it was with great anticipation that I saw that O’Reilly has posted his thoughts on the intersection of copyright and AI.
If the long-term health of AI requires the ongoing production of carefully written and edited content—as the currency of AI knowledge certainly does—only the most short-term of business advantage can be found by drying up the river AI companies drink from. Facts are not copyrightable, but AI model developers standing on the letter of the law will find cold comfort in that if news and other sources of curated content are driven out of business.
How to Fix “AI’s Original Sin”
While large licensing deals are being cut by publishers that have the leverage & lawyers to negotiate massive, one-time deals, these are ultimately short-lived and only serve to build up the large AI-providers that can afford to subsidize premium materials for their users. These deals just make the rich even richer.
The longer term, sustainable opportunity he proposes is in allowing the internet-of-many to share in the revenues enabled by the output from these large AI systems.
But what is missing is a more generalized infrastructure for detecting content ownership and providing compensation in a general purpose way. This is one of the great business opportunities of the next few years, awaiting the kind of breakthrough that pay-per-click search advertising brought to the World Wide Web.
How to Fix “AI’s Original Sin”
Build a shared provenience and attribution service that keeps track of all documents available to AI systems and the permissions and royalty payment requirements around those documents.
O’Reilly alludes to the UNIX/LINUX filesystem architecture of files with permissions set at the global, group, and user levels as a potential solution to what publishers allow to AI vendors seeking out material for their training sets.
If we expand this analogy out to internet scale, could we apply the architecture of Hosts tables and the modern Domain Name Service to provide a dynamic infrastructure that could maintain a public “lookup” service so any particular AI could locate the origin of any attributable fact, quote or yet-to-be-determined “knowledge unit” and the license fee should an AI wish to leverage that data.
In UNIX, the chmod command is used to change permissions. Could setting copyright permissions via a specialized version of “chmod” be the key to a new way to control access and compensate publishers at scale?
Food for thought.
Behind every freakishly algorithm is a group of often underpaid and overworked “digital serfs” busy labeling and reviewing the data streams that make the technology work. Expensify SmartScan for receipts? In 2017, someone discovered some of these receipts turned up on Mechanical Turk.
Amazon announced last week that it’s shutting down its “Just Walk Out” technology that powered the experimental Amazon Go shopping experience that removed the need for cash registers and cashiers in stores. When it was launched, Amazon claimed that an array of cameras was feeding which items which items were taken off the shelf so they could later be charged to the account of the person scanning their Amazon ID as they walked in.
As with any new technology, there was quite a bit of hesitancy to embrace this new way of shopping that didn’t quite “feel” right.
Saturday Night Live even spoofed the tech as skeptical New Yorkers were again confronted with “this will never work in reality” use cases dreamed up by big tech.
Now we learn, six years later, that the technology never got off the ground.
The Information revealed the myriad tech problems Amazon was still having with the idea six years after the initial announcement. The report said that “Amazon had more than 1,000 people in India working on Just Walk Out as of mid-2022 whose jobs included manually reviewing transactions and labeling images from videos to train Just Walk Out’s machine learning model.
Amazon Fresh kills “Just Walk Out” shopping tech—it never really worked
While it’s funny to poke fun at a “fake it ’til you make it” business ideas that never reach sustainability, there is a real cost associated with a deep-pocketed company leveraging their brand and technology to launch a new way of doing business that relies on low-cost offshore labor masked behind a shiny new AI. Think of the stores put out of business during the six years Amazon was paying offshore workers to ring up purchases for Amazon Go customers. What about the poor souls doing the mind-numbing work of tagging items by watching a livestream from a camera on their monitor in the middle of the night, totally removed from human interaction?
All of these are, separately, quite funny stories. But collectively they paint a picture of a society, and a culture, utterly unequipped to register the violence that is being done to it, merely because historical process is draped in the ribbons of “technology”. This violence is enacted simultaneously on the high street and the global stage. What makes me angry about how often we keep falling for it is not merely that we should know better, but what the costs of doing so actually are.
So, Amazon’s ‘AI-powered’ cashier-free shops use a lot of … humans. Here’s why that shouldn’t surprise you
Amazon has issued a statement on the news to clarify while they are shutting down the “Just Walk Out” platform, they will keep the stores cashierless but, instead, ask the shoppers to tag items as they put them in their tech-enabled Dash Cart grocery carts used in their Whole Foods stores.
So instead of someone in an offshore facility doing the work, we’ll be doing it for them instead.
UPDATE: offshore cashiers are still a thing
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