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By Maggie Reznikoff

How influencers feed the infrastructure

For years, brands have hired creators primarily for distribution. The value was access: reach their audience, borrow their credibility and spark conversation in places traditional advertising struggled to penetrate.

That model has not disappeared. But a second use case is rapidly scaling. Brands are no longer hiring creators only to post. Increasingly, they are hiring them to produce.

What looks like influencer marketing on the surface is becoming something closer to a distributed production system.

The New Production Stack

Modern creators often operate with capabilities that rival small production teams: filming, editing, motion graphics, sound design, trend fluency and real-time iteration informed by performance data. Many can concept, shoot and deliver platform-ready assets in days, sometimes hours.

This is not scrappy content. It is platform-native creative engineered for feeds where authenticity, speed and relevance outperform polished but distant brand messages. Creators are also optimized for volume and variation, producing multiple formats and storylines that can be tested and redeployed across channels. For marketers, this is not just content. It’s optimization fuel.

The challenge is that most brand organizations were built around centralized production: long timelines, tightly controlled shoots and limited outputs. Creator-driven production flips those assumptions. When hundreds of creator assets begin flowing into paid media, owned channels retail, and e-commerce, friction can appear. Legal teams encounter usage scenarios that don’t fit legacy contracts. Creative teams face approval cycles that outlast platform trends. The constraint is no longer creative supply. It is organizational readiness. Brands often unintentionally dilute the speed and cultural relevance they hired creators to deliver by routing them through processes designed for a different era.

Instinct is the Real Differentiator

What separates creators from traditional production partners is their proximity to audience behaviour. Many have been publishing consistently for years, living inside comment sections, testing formats and watching performance signals shift in real time. That repetition builds instinct.

Creators know when something will resonate because they have felt resonance before. They understand pacing, framing, tone and tension from daily feedback loops with real communities. A creator can post, test a hook and know within hours whether it sparks conversations—then refine and scale what works before a traditional campaign would even enter final approval.

That ability to prototype in public is why creative freedom matters. Overly prescriptive briefs interrupt the feedback loop that makes creators valuable. When brands treat creators as rigid executors of prewritten scripts, they miss the deeper advantage: a creator’s fluency with their audience and ability to navigate performance signals without losing authenticity.

From Campaign Oversight to Production Orchestration

As creators take on a larger production role, marketers must shift from managing discrete campaigns to orchestrating ongoing content ecosystems.

That starts with upstream planning. Briefs should define objectives, guardrails and use cases rather than prescribing every creative detail. Usage rights need to be considered early if assets will travel across paid, owned, commerce and in-store environments. Approval workflows must prioritize speed. Measurement should evaluate performance across iterations, not just a single deliverable.

Forward-thinking brands are also building processes to redeploy creator content as modular building blocks. One creator shoot can support weeks or months of activity when captured with downstream uses in mind.

GoPro and Airbnb have long operated with creators as a distributed production layer, sourcing campaign assets from users embedded in real experiences rather than staged shoots. At the same time, many brands (especially CPG, home goods and beauty) now rely on anonymous or “faceless” UGC creators to mass-produce product demos and lifestyle clips, effectively outsourcing everyday content production to a network of micro-studios.

The Bottom Line

Treating creators solely as media channels limits their potential. Treating them as production partners, and giving them the creative freedom to operate as such, unlocks scale.

The rise of creators as production partners is not a replacement for influencer marketing. It is an expansion of it. Brands that adapt their legal frameworks and asset strategies will unlock speed and relevance across channels. Those that rely solely on legacy production models may find themselves unable to keep pace with the volume and agility modern marketing requires.

Creators are still powerful voices. Increasingly, they are also the infrastructure shaping how brand content gets made, tested and scaled.

By Maggie Reznikoff

Maggie Reznikoff is chief client officer at Open Influence.

Sourced from MUSE BY CLIOS

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I guess we’ve recovered from that problematic ad…

In line with the new iOS 26.4 update, Apple has launched a collection of new emojis, including a familiar (and controversial) face. While the Unicode Consortium officially approved the designs last summer, the new emojis have caused a stir for their unexpected addition, which is giving fans major flashbacks to Apple’s most controversial ad.

From its playful new ads to the Gen Z branding of the new MacBook Neo, it seems Apple is in an exciting new era, finally shedding its stuffy professional skin. The new emoji additions are just another example of how the brand is leaning into its sillier side, even making light of its own past mishaps, much to the delight of fans.

The new iOS 26.4 beta includes the addition of eight new emojis, including a fight cloud, hairy creature (a.k.a bigfoot), landslide, orca, trombone, treasure chest, ballet dancers and the infamous ‘distorted face’. Look familiar? That’s right. He’s the little yellow guy who starred in Apple’s highly controversial ‘Crush’ ad, which appalled audiences so much that the tech titan had to issue an apology.

The addition divided fans, with some seeing the funny side, while others were a little less jovial about it. “Because we needed a memento from that horrible advertisement?” one disgruntled critic wrote on X. “Close enough, welcome back iPad Pro Crush! ad,” another wrote, while one fan predicted, “Distorted Face is about to become the most used emoji overnight.”

Feature image credit: Future owns

By 

Natalie Fear is Creative Bloq’s staff writer. With an eye for trending topics and a passion for internet culture, she brings you the latest in art and design news. Natalie also runs Creative Bloq’s 5 Questions series, spotlighting diverse talent across the creative industries. Outside of work, she loves all things literature and music (although she’s partial to a spot of TikTok brain rot).

Sourced from CREATIVE BLOQ

Sourced from RADIO CENTRE IRELAND

TheJNLR/Ipsos figures released for the April ’25 to March ’26 period confirms the scale and influence of radio in Ireland, with almost 3.5 million adults tuning in every weekday and listening levels among younger audiences remaining particularly robust.

The survey shows that 78% of adults listen to radio each weekday, while weekly reach now stands at 89% of the adult population, reinforcing radio’s position as one of Ireland’s most consistently used media channels.

Radio continues to perform very strongly across younger audiences with 65% of 15–34-year-olds listening each weekday, while 6 out of 10 of under 24 year old’s tune in each weekday, representing 416,000 young listeners.

Local and regional radio continues to play a hugely important role in Irish life, attracting 2.3 million adult listeners every weekday and maintaining strong engagement within communities across the country.

In terms of how people listen, 10% of all radio listening is now via connected devices — 6% through a smart speaker and 3% via a mobile device. For the younger 15–34 age group, 17% of all radio listening is now via a connected device, with smart speakers accounting for 9% and mobile devices for 7% of their total radiol istening.

Radio also remains the dominant force within the overall audio market. Live radio accounts for 74% of all audio listening time, substantially ahead of music streaming, podcasts and other audio formats.

Alongside its scale, radio continues to offer audiences something increasingly valuable in modern media — trusted companionship, personality and human connection. In an environment often shaped by fragmented and impersonal media experiences, radio creates a sense of shared experience and real-time connection that continues to resonate strongly with listeners throughout the day.

That connection is also reflected in advertising performance. Research conducted by Lumen Research and dentsu for Radiocentre Ireland found that Irish radio delivers attention and memorability levels 35% above global norms, highlighting radio’s ability to generate high levels of audience attention efficiently and cost-effectively for advertisers.

Other key results from the latest JNLR/Ipsos survey include:

• 89% of all adults and 83% of 15–34-year-olds listen to radio every week.

• 65% of15–34-year-olds listen each weekday, while daily listening among the hard-to-reach 15–24-year-old cohort remains very strong at 60%.

• 77% of ABC1 adults listen to radio each weekday, while the figure for the main shopper is 80%.

• Listening to local and regional radio remains very strong, with 2.3 million adults tuning into their local or regional station every weekday.

• 96% of adults listen to audio every week. Live radio accounts for 74% of total audio time, followed by music streaming (13.5%), YouTube Music (6%), and podcasts (3.5%).

• 10% of all radio listening is via connected devices — 6% through a smart speaker and 3% via a mobile device. Among 15–34s, 17% of listening is via connected devices with 9% of all listening through smart speaker and 7% through mobile.

You can download a full analysis of the JNLR/Ipsos survey by clicking the button below.

Sourced from RADIO CENTRE IRELAND

By Marty Marion

Every business discussion about growth and customer acquisition eventually circles back to retention, loyalty, and lifetime value. But while these elements matter, they obscure the underlying arithmetic that governs every competitive market.

A brand cannot retain its way to expansion and profitability, or even long-term survival—the math simply doesn’t work out. It can stabilize, at best, but customers relocate, needs change, budgets tighten, and competitors improve. Life circumstances reorganize consumption patterns.

Attrition happens, and no brand can prevent it. Even the most satisfied customer base decays.

The only reliable counterforce is a steady influx of new customers, which (as you’ll see in a minute) must be acquired from competitors. This adds a significant layer of complexity to the customer acquisition equation.

I’m not talking about a marketing philosophy, here. This is a population dynamic. Empirical brand growth research consistently shows that brands expand primarily by increasing penetration, rather than intensifying loyalty among existing buyers.

Work led by Byron Sharp and Jenni Romaniuk at the Ehrenberg-Bass Institute clearly demonstrates that brand growth correlates strongly with reaching more category buyers and only weakly with deepening repeat purchase among current ones. In other words, brands get bigger when more people choose them at least occasionally. That requires those same people to also stop choosing a competitor at least occasionally.

This means the central event in growth isn’t satisfaction. It’s switching.

The unexpected psychology behind brand loyalty

Customer acquisition is almost a completely zero-sum endeavour: every customer a brand gains is a customer its competitor lost. Yet switching is psychologically unusual behaviour. Humans aren’t neutral choosers encountering products for the first time. They’re continuity-preserving organisms.

Daniel Kahneman and Amos Tversky’s prospect theory formalized this loss aversion: the perceived risk of giving up a known solution outweighs the potential gain of a better one. Habit research in behavioural psychology shows repeated decisions migrate from deliberation into automaticity. Once a choice works, the brain economizes effort by reusing it.

In other words, what appears in markets as loyalty is often risk management combined with cognitive efficiency, rather than any kind of emotional devotion. People avoid reconsideration and risk unless circumstances force it.

This has a practical implication. Before a brand can acquire, it must persuade. Before a brand can persuade, it must be welcomed into the consideration set. And permission is not granted automatically. In fact, by default, it doesn’t exist at all.

Most categories are populated by customers who already possess a satisfactory answer to the problem the category solves. They may not love it—they may not even think about it—but they trust it enough not to question it. Whatever brand they’re now using is at least “good enough.” The decision is already closed.

That closure is the real competitive barrier, and it exists before any marketing communication, creative execution, or media plan.

The first task in customer acquisition isn’t preference formation. It’s the interruption of continuity.

Since customers are psychologically and behaviourally tied to their incumbent brand choice, the only way to disengage them is through disruption. Sometimes, the trigger is realization of a failure. Sometimes it’s a price change or a life event. Sometimes, their dissatisfaction crosses a threshold.

Whatever the cause, the critical moment is psychological: the individual accepts the possibility that the current solution may no longer be the safest choice. Only after that moment does a “purchase journey” appear.

What most customer lifecycle frameworks get wrong

Unfortunately, most widely adopted frameworks treat browsing, research, comparison, and discovery as the beginning of decision making. Professor Scott Galloway’s Customer Lifecycle Framework does this explicitly by labelling the evaluative period “pre-purchase,” implying the consumer has not yet formed meaningful commitment and is therefore open to persuasion.

But by the time a person is researching, the meaningful threshold has already been crossed. Galloway’s lifecycle model may treat discovery as the start, but discovery is evidence that the start has already happened elsewhere. What looks like the beginning of decision making is actually proof that activation already occurred.

In other words, pre-purchase isn’t the beginning; it’s just where evaluation becomes visible. It’s the period after activation and before discovery.

The real beginning of decision-making sits upstream from pre-purchase and is defined by that activation. Something must break continuity. Something must loosen the incumbent’s grip. Something must move the consumer from automatic repetition to openness.

Galloway’s model skips that moment and, therefore, cannot function as a true theory of acquisition. Because the dismantling begins here, not later. It’s a structural flaw, rather than a peripheral one, and if the first step is misplaced, then every step after inherits the error.

This distinction matters because a framework that begins with evaluation cannot explain how evaluation becomes possible. It can optimize comparison, messaging, usability, and conversion mechanics. But it cannot account for the more difficult competitive event: how a customer who was not looking becomes willing to look.

The missing phases before consumer choice even exists

If what the lifecycle model calls “pre-purchase” is actually post-activation, then the obvious question is, what exists before it?

The answer can’t be “nothing” because decisions don’t begin spontaneously at the moment of evaluation. A person doesn’t wake up one morning in a neutral psychological state and decide to compare laundry detergents, insurance carriers, or project management software.

Something’s gotta give first.

The decision process unfolds not as a continuous funnel, but as a series of state changes.

To understand acquisition properly, we need a map that begins before evaluation becomes observable. Each state represents a different psychological condition and, therefore, a different competitive problem.

The first state is stability.

In the stability state, no decision exists. Nothing is being evaluated because nothing feels uncertain. Which explains why most advertising is ignored: a message simply can’t compete with a settled and closed decision.

The buyer already possesses a functioning answer to the category problem and isn’t allocating attention to alternatives. So, what appears to marketers as indifference is actually resolution. The buyer isn’t rejecting the brand, but rather not participating in the category at all.

The second state is tension accumulation.

Small frictions begin to gather around the incumbent solution. None individually justify reconsideration. A slightly higher bill, a minor inconvenience, a momentary annoyance, a social comparison, an incremental disappointment. Each event is insufficient to trigger change, but together they weaken certainty. The buyer still repeats the behaviour because the cost of re-evaluating exceeds the perceived benefit. The decision remains closed but less comfortably so.

The third state is disturbance.

A trigger crosses the tolerance threshold. Something interrupts continuity. A failure, price shift, life change, direct comparison, or accumulated dissatisfaction weakens the certainty of the existing solution. The trigger doesn’t persuade the buyer toward a specific alternative—it destabilizes confidence in the existing solution and converts the decision from settled to unsettled.

The fourth state is permission.

This is where the psychological shift actually occurs as the consumer crosses a permission threshold. Reconsideration becomes reasonable. The category reopens. And while the consumer has yet to choose or form a preference, they have accepted the legitimacy of searching again.

This moment of willingness may be small, private, and rarely observable, but it’s the true beginning of acquisition. It’s what determines whether any marketing communication can function as information rather than noise.

The fifth state is candidate formation.

Behaviour now becomes visible. The buyer constructs a shortlist from memory, familiarity, reputation, and perceived safety. This is the formation of what consumer researchers call the “evoked set”, a small subset of brands deemed acceptable enough to compare. Most brands never enter it. They’re not actively rejected; they’re just never considered eligible. The competitive battle here isn’t persuasion, but rather inclusion.

The sixth state is evaluation.

Only at this point does what is commonly called “the purchase journey” begin. What marketers call “discovery” lives here. The buyer compares options, reads information, checks prices, asks others, and interacts with marketing assets.

This is the phase the lifecycle model labels as “pre-purchase”, but psychologically it sits late in the process. By the time evaluation occurs, the buyer has already accepted change and eliminated most of the market. They’re still not choosing, but they have constructed a candidate set.

The seventh state is selection.

A choice is made from the filtered set. Features, price, and usability matter here because unacceptable options have already disappeared. Most marketing optimization operates at this level, improving the probability of winning among options already admitted into consideration.

The eighth state is reinforcement.

After adoption, the buyer rationalizes the decision, incorporates it into routine, and returns to stability. The loop closes again. What appears as loyalty is frequently the restoration of closure rather than enduring preference.

Seen as a sequence of states rather than a single funnel, the structural gap becomes unmistakable: The lifecycle model begins at the fifth state and labels it the first. It assumes openness instead of explaining it and manages comparison instead of enabling consideration.

This distinction isn’t semantic. A framework that starts at evaluation can improve the probability of winning once invited into the decision, but it cannot explain how to receive an invitation in the first place. The conventional lifecycle model, therefore, doesn’t describe the path to acquisition—it describes the middle of it. Meanwhile, brand strategy operates primarily in the earlier states, where eligibility is constructed and stability is disrupted.

The moment the conventional lifecycle model loses the market

What follows from the eight states isn’t a matter of interpretation. It’s a matter of causal order.

The lifecycle framework for brand strategy fails at the first move because it commits the oldest strategic error in competitive markets: it assumes the fight begins when the fight becomes visible.

Visibility isn’t causality. What can be measured isn’t necessarily what created the behaviour being measured.

A buyer browsing, comparing, or “doing research” isn’t standing at the beginning of a journey. They’re standing at the end of a psychological event that already decided whether brands were allowed to compete at all.

Something happened before the model ever began. A rupture. A revelation. An epiphany.

The buyer’s default choice lost its automatic status. The category reopened in the buyer’s mind. The incumbent stopped feeling safe enough to repeat without thought. Continuity fractured. Something caused the consumer to cross a private threshold from stability to vulnerability.

This is the moment of activation.

Activation is the precondition to evaluation, the precursor to comparison, and the gate through which every brand must pass before any marketing mechanism can operate. Yet the lifecycle model has no structural place for it. The model can’t explain it, can’t measure it, and can’t manage it. So, the model quietly treats it as if it doesn’t exist.

Once this is seen, the framework’s first mislabel becomes impossible to ignore. “Pre-purchase” isn’t “before the purchase” in any meaningful strategic sense. It’s after permission. After disturbance. After the mind has already opened to change.

In other words, pre-purchase isn’t a stage—or rather, it isn’t the essential primary stage. It’s a derivative of earlier, more fundamental psychological phases. So while the pre-purchase → purchase → post-purchase Customer Lifecycle Framework effectively describes the mechanics of choice once a buyer is open to choosing, real brand growth depends on creating that openness to switch in the first place.

The arithmetic of brand growth

Let me be clear: The claim that growth depends on switching is not merely behavioural or conceptual. It’s structural. Markets exhibit stable statistical regularities across categories, countries, and time periods. Those regularities have been observed repeatedly in consumer goods, services, financial products, telecommunications, and digital platforms. They appear regardless of whether brand managers believe in, understand, or actively plan against them. What anyone believes is true matters not at all; facts are facts regardless of consensus or opinion.

The most relevant of these patterns is the relationship between penetration and loyalty. When a brand becomes larger, it doesn’t grow because its buyers suddenly become dramatically more devoted than everyone else’s. It grows because more people buy it at least occasionally. The increase in loyalty is small and largely a by-product of size, not the cause of it. Most members of loyalty programs leave in a matter of months, a far shorter tenure than would lead to any meaningful or incremental contribution to the margin.

This pattern is known as the Double Jeopardy law. Smaller brands suffer twice. They have fewer buyers, and those buyers are slightly less loyal. Larger brands have more buyers, and those buyers appear slightly more loyal, but only because a bigger pool of buyers naturally produces more occasions for repeat purchasing.

Loyalty differences follow, rather than create, market share.

This matters because much of modern marketing planning implicitly assumes the opposite. It assumes that retention initiatives, experience improvements, subscription benefits, and lifecycle management can accumulate into growth. In reality, they merely maintain the status of the existing buyer base, while the competitive battle continues elsewhere.

The arithmetic is simple even if the consequences are uncomfortable:

Growth ≈ rate of switching in − rate of switching out

This isn’t a metaphor. It’s a conservation law of competitive markets. At any moment in time, every buyer in a category is owned by someone. There are no “unowned customers” waiting to be acquired. I repeat: There are no unowned customers waiting to be acquired.

A person buying toothpaste, insurance, software, or groceries is already buying it from a competitor. So, when one brand grows, it does so by reallocating demand from someone else, not by creating demand from nothingness. Market share, therefore, changes only when people move.

In other words, growth is movement. Retention stabilizes an existing population; switching changes a population.

Imagine a category containing 1,000 buyers. If a brand perfectly retains all 400 of its current customers, next year it still has 400 customers. Perfect loyalty produces perfect stagnation. The only way the brand becomes larger is if buyers currently belonging to other brands begin buying it.

Expansion isn’t the prevention of exit; it’s the creation of entry.

At any given moment, there are two invisible flows occurring simultaneously:

  • Inbound switching—people who previously bought another brand now buy yours
  • Outbound switching—people who previously bought your brand now buy another.

No brand escapes this. Even dominant brands lose customers constantly. What separates a growing brand from a shrinking one is not whether switching happens, but the balance of switching. Growth happens when you steal more customers than you lose. Decline happens when you lose more customers than you steal. Stability happens when the flows roughly cancel each other out.

Inbound switching dominates. Brands gain market share when they attract people who previously bought something else. Outbound switching matters, but rarely varies enough across competitors to explain expansion. Which means retention programs cannot produce category growth unless they materially change switching behaviour—and they usually don’t. They reward people who already intended to stay.

This explains why loyalty programs often redistribute purchasing frequency among existing customers, rather than expand the customer base. They increase depth among the already convinced, and loyalty metrics feel powerful because they visualize that depth within the group. But growth depends on movement between groups, and loyalty programs do very little among the unconvinced (because the unconvinced aren’t even there).

The same arithmetic explains a recurring observation in direct-to-consumer markets: Many digitally native brands grow rapidly to a certain revenue band and then plateau and stall. Their marketing systems become efficient. Their conversion rates improve. Their customer experience is refined. Yet acquisition costs rise steadily and incremental growth becomes more expensive over time.

The reason why is no mystery. The easily activatable buyers have already switched. The remaining market is composed of people whose default choices haven’t been disrupted. Optimization may have improved performance inside the activated population, but it did nothing to expand the activated population itself.

This is why customer acquisition costs rise. It’s not because advertising platforms arbitrarily punish brands, but because the remaining audience requires a different competitive event: the reopening of closed decisions.

The cognitive gate to market penetration

To understand why activation matters, it helps to examine what a consumer is actually protecting when they repeat a purchase.

Most purchasing decisions are closed loops rather than active choices. The buyer already solved the problem once and is now preserving that solution against reconsideration. This preservation is rarely conscious—it’s structural. The brain isn’t evaluating alternatives each time a purchase occurs; it’s maintaining stability.

Psychologists describe the mind as a cognitive miser. It conserves effort by reusing conclusions that previously worked. Every stable product choice, therefore, becomes a stored shortcut. Reopening that shortcut requires attention, cognitive energy, and the acceptance of uncertainty. And as long as the existing option performs adequately, repetition is the lowest-cost action available.

This produces what economists call default bias and psychologists call status quo bias. The current option isn’t re-examined each time, it’s assumed. Therefore, competing brands face a barrier more fundamental than preference. They must justify why thinking again is necessary at all.

Loss aversion strengthens this boundary. Giving up a known solution is experienced as a potential loss, while adopting a new one is only a possible gain. The asymmetry protects incumbents regardless of objective quality. The buyer is rarely asking which option is best. The buyer is asking whether reconsideration is safe.

Only when that question shifts from no to maybe does evaluation begin.

People don’t continuously search for better answers once a sufficient answer exists. They stop searching.

Most brand relationships live inside that stopped search. Marketing activity aimed at comparison quietly assumes search is active. In reality, the first competitive task is restarting the search itself.

Habit loops reinforce the same structure. A cue triggers a routine that produces a satisfactory outcome. The brain marks the routine as efficient and repeats it automatically. So, unless it disrupts the cue-routine-reward cycle, advertising enters this environment as simple background noise. Persuasion inside that intact loop has limited effect because the loop itself prevents evaluation from initiating.

Taken together, these mechanisms form a gate rather than a spectrum—a buyer is either maintaining a solved decision or reopening it. That gate is invisible but decisive, and it precedes evaluation. It precedes the lifecycle model.

What the lifecycle model calls “pre-purchase” occurs after the cognitive gate has already opened. It organizes competition once entry is permitted, but it doesn’t explain what permits entry in the first place. Activation does that. Proper brand strategy does that.

Brand strategy begins long before consumer recognition

The proper brand strategy creation approach therefore doesn’t begin at the beginning of Galloway’s pre-purchase → purchase → post-purchase brand strategy model. It begins after the decisive event has occurred, after the market has already moved, after the real strategic work has either succeeded or failed without being recognized.

This is also why organizations feel trapped inside a paradox they cannot diagnose. Everything improves inside the system while growth slows outside it. Teams optimize messaging, interfaces, media efficiency, and conversion pathways. Metrics rise. Dashboards look healthier. Yet acquisition becomes harder, more expensive, and less predictable.

Nothing appears broken because nothing inside the model is broken. The machine is functioning exactly as designed.

But it’s simply optimizing a consequence and calling it strategy when it’s not.

Brand strategy operates upstream. Execution operates once evaluation is already underway.

If activation is omitted, every downstream interpretation inherits and compounds the error. What looks like competition inside the model is often just selection among survivors. What looks like persuasion is frequently the final expression of decisions made earlier and elsewhere.

The framework measures visible behaviour while ignoring the invisible shift that made behaviour possible. That omission becomes fatal in the next step.

The next article in this series moves into the place where traditional models insist the story begins and exposes a subsequent structural failure. Because even after activation occurs, consumers don’t evaluate brands the way marketing narratives claim. They don’t compare brands like judges scoring arguments. They eliminate brands like risk managers protecting themselves from regret.

Long before features, pricing, or persuasion matter, buyers remove anything that feels unsafe, implausible, unfamiliar, or difficult to justify. Which means that, by the time “pre-purchase” begins, most brands are already gone.

Feature image credit: Fran-kie

By Marty Marion

Sourced from Brandingmag

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Paddington’s favourite preserve is in a jam.

Ah, marmalade. It’s been a staple British breakfast delicacy since the 18th century. Over the years, the citrus-based spread has been credited with everything from aiding digestion to preventing scurvy among sailors. But the country has been rocked this week by news that the traditional preserve so appreciated by Queen Victoria and Paddington Bear may have to be renamed.

‘Marmalade rebranding’ is a bit of a misnomer since there are obviously various brands of marmalade, and this is an issue that could affect them all. It’s more of a marmalade reconceptualisation, if not a full-blown identity crisis.

The marmalade controversy is long and complex. The long story short is that manufacturers may soon have to specify that what the Brits know as marmalade is actually ‘citrus marmalade’ or ‘orange marmalade’. And it’s all because of Brexit.

The dispute dates back to a historical linguistic caprice. The word ‘marmalade’ comes from the Portuguese ‘marmelada’, which to this day still refers to a thick quince paste often served with jam. For reasons not entirely clear, but probably just to be eccentric, British producers decided to change the meaning of the word to refer to a more liquid jam made with Seville oranges imported from Spain.

Just to confuse things even further, other countries in Europe coined related words in their own languages, like the Spanish ‘mermelada’, Italian ‘marmellata’ and German ‘Marmelade’, to refer to all types and flavours of jam, not just citrus ones.

While Britain was a member of the European Union, it was able to influence decision making in Brussels. It lobbied fiercely on the marmalade front during the 1970s and scored a landmark victory for British idiosyncrasy, convincing the EU to grant a special commercial status for marmalade made from Seville oranges.

But other countries never forgot the bitter taste of that defeat. As reported by the BBC, a German MEP complained back in 2017 that the marmalade anomaly was “contrary to German linguistic tradition”.

Now the EU nations have taken advantage of Britain’s absence from the bloc to relax the legal definition of marmalade, granting European producers freedom to use the term for jams of any flavour from June. By extension that means that traditional British-style marmalade will have to be labelled as ‘citrus’ or ‘orange’ marmalade so people know what it is.

A jar of orange marmalade beside a slice of toast

A breakfast classic of marmalade on toast – orange marmalade that is (Image credit: Kseniya Ovchinnikova via Getty Images)

In theory, Brexit was supposed to avoid Britain having to kowtow to such cultural domination. The heavy cost to the British economy was deemed a small price to pay for the freedom to eat bent bananas and to measure things using an arcane system that nobody understands.

Alas, like most things around Brexit, that turned out to be a bit of a porky. To trade with the EU, Britain must respect its rules. The new concept of marmalade is already due to take effect in Northern Ireland this summer under the 2023 Windsor framework deal, but it will also apply in England, Wales and Scotland if a broader food deal is agreed, which is expected for around mid-2027.

The organisers of the Dalemain World Marmalade Awards wrote on Instagram this week that they were concerned about the possible expense for artisan producers that may need to change the designs of their labels, but that, ultimately, they see the rule change as positive.

“We get entries from around the world where marmalade can be understood completely differently to our jars here in the UK. American marmalades are always runnier for instance, while Canadian marmalade is much closer to our firm gel set. European marmalades are often absolutely delicious but often more resemble compotes than marmalade. So this name change seems quite positive and hopefully might make it easier for people to understand what we are looking for in this British standard competition.”

What’s not clear is whether the UK will see non-citrus preserves being called ‘marmalade’. The Department for Environment, Food & Rural Affairs (Defra) has previously concluded that a sudden appearance of products like ‘strawberry marmalade’ on supermarket shelves could cause confusion.

Feature image credit: St Dalfour | paradosiaka | Ferbar

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Joe is a regular freelance journalist and editor at Creative Bloq. He writes news, features and buying guides and keeps track of the best equipment and software for creatives, from video editing programs to monitors and accessories. A veteran news writer and photographer, he now works as a project manager at the London and Buenos Aires-based design, production and branding agency Hermana Creatives. There he manages a team of designers, photographers and video editors who specialise in producing visual content and design assets for the hospitality sector. He also dances Argentine tango.

Sourced from CREATIVE BLOQ

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In short: Meta faces a convergence of lawsuits across the US, Australia, and the UK alleging the company knowingly profited from scam ads on Facebook and Instagram, with its own internal documents projecting that 10% of 2024 revenue, roughly $16 billion, came from fraudulent advertising. The cases span a $500 million pump-and-dump scheme, deepfake celebrity endorsements, financial professional impersonation, and cryptocurrency fraud, while leaked internal assessments show Meta calculated that scam revenue would exceed the cost of any regulatory settlement.

Meta is facing a convergence of lawsuits, class actions, and regulatory investigations over scam advertisements on Facebook and Instagram that, according to the company’s own internal projections, generated roughly $16 billion in revenue in 2024, approximately 10% of Meta’s total advertising income. The legal actions span the United States, Australia, and the United Kingdom, and collectively allege that Meta knowingly profited from fraudulent ads including AI-generated deepfake celebrity endorsements, pump-and-dump stock schemes, fake investment platforms, and unauthorised impersonation of financial professionals, while maintaining ad moderation systems that were structurally inadequate to prevent the fraud and, in some cases, deliberately weakened to protect revenue.

The most financially significant case, filed in February in the US District Court for the Northern District of California, alleges that Meta facilitated a pump-and-dump scheme involving Jayud Global Logistics, a Chinese stock listed on Nasdaq. According to the complaint, scammers acquired 50 million shares at discounted prices in December 2024, then used targeted Facebook and Instagram ads to drive the share price to nearly $8 before dumping their positions in April 2025. Consumer losses exceeded $500 million. A California federal judge dismissed the class action on 25 March, ruling that the plaintiffs had not sufficiently alleged Meta “co-created” the ads, though the dismissal appeared to be without prejudice.

The pattern across jurisdictions

A separate class action, filed by Scott+Scott on behalf of financial professionals John Suddeth and Sara Perkins, alleges that Meta allowed scammers to use their names, images, voices, and professional personas in paid advertisements, causing client diversion, reputational harm, and regulatory inquiries. A bipartisan coalition of US state attorneys general had warned Meta in June 2025 that impersonation ads and fraudulent WhatsApp investment groups were being used for widespread fraud. According to the complaint, materially identical impersonation ads continued running after the warning.

In December, the US Virgin Islands attorney general sued Meta in Superior Court, alleging the company “knowingly profited” from scam ads and “charged fraudsters extra for the right to advertise scams” rather than removing them. The Virgin Islands suit joined actions by 42 other state attorneys general who have taken Meta to court, primarily over child safety but with increasing overlap with advertising fraud. In April, New York attorney general Letitia James issued an investor alert specifically about investment scams on Meta platforms.

In Australia, the Competition and Consumer Commission has been pursuing Meta in federal court since March 2022 over cryptocurrency scam ads that used the likenesses of businessman Dick Smith, television presenter David Koch, and former New South Wales premier Mike Baird. A single victim cited in the complaint lost more than A$650,000. Meta failed to get the case dismissed in 2023. In the United Kingdom, the Financial Conduct Authority found 1,052 illegal financial advertisements on Meta platforms in a single week in November 2025. A leading UK bank found that 80% of its fraud cases originated on Meta’s platforms, with Facebook Marketplace accounting for 60% of purchase fraud, Instagram responsible for 67% of investment fraud, and WhatsApp impersonation scams up 300% year on year. Meta’s platforms account for 61% of all authorised push payment scams in the UK, according to UK Finance, with criminals stealing £485.2 million.

The $16 billion question

The scale of the problem is defined by Meta’s own internal documents. A Reuters investigation published in November 2025 revealed that Meta projected 10% of its 2024 global revenue, roughly $16 billion, derived from scam and fraud-related advertising. The company served an estimated 15 billion “higher risk” scam ads per day. Nineteen percent of Meta’s ad revenue from China, approximately $3 billion, was linked to scams. Internal documents showed that when enforcement staff proposed shutting down fraudulent accounts, Meta sought assurance that “growth teams would not object given the revenue impact.” A subsequent Reuters report in January found that Meta had developed an internal “playbook” to neutralise regulators and manipulated its ad library to make scam ads harder to find.

Rob Leathern, Meta’s former senior director of product management who led business integrity operations, said of the findings: “The levels that you’re talking about are not defensible.” Meta described the Reuters projections as “a rough and overly-inclusive estimate” and said the documents presented “a selective view that distorts Meta’s approach to fraud and scams.”

The economics are straightforward. Implementing universal advertiser verification would cost Meta approximately $2 billion and reduce revenue by up to 4.8%. Internal assessments reportedly noted that “revenue from risky ads would almost certainly exceed the cost of any regulatory settlement,” a calculation that treats fines as a cost of doing business rather than a deterrent.

The deepfake dimension

AI-generated deepfakes have become central to the scam ad ecosystem. Deepfake fraud attempts have surged by 3,000% as generative AI tools have become cheaper and more accessible, enabling scammers to create convincing fake video endorsements at scale. Martin Lewis, the UK’s most prominent personal finance campaigner, was targeted with a deepfake video promoting a “Quantum AI” investment scheme. Deepfakes of Donald Trump, Elon Musk, Alexandria Ocasio-Cortez, and Bernie Sanders were used to promote fake government benefit schemes. In Brazil, AI-altered images and voices of prominent physicians promoted fraudulent healthcare products.

The Tech Transparency Project identified 63 scam advertisers responsible for more than 150,600 political ads and $49 million in lifetime spending on Meta. During a 90-day period in mid-2025, at least 45 scam advertisers spent over $18 million. Meta says it protects images of 500,000 celebrities and public figures through automated detection and is testing facial recognition technology to compare faces in suspected scam ads against public figures’ profile pictures. EU lawmakers have agreed to ban AI-generated non-consensual deepfakes through amendments to the AI Act, signalling increasing regulatory appetite to legislate against synthetic media that platforms have failed to police.

What Meta says it is doing

Meta recently rolled out new scam detection tools across Facebook, Instagram, WhatsApp, and Messenger. The company says it removed 159 million scam ads and took down 10.9 million accounts linked to scam operations in 2025, with 92% of scam ads caught proactively before any user report. It disabled 150,000 accounts associated with Southeast Asian scam centre networks and partnered with the Royal Thai Police in disruption operations that led to 21 arrests. Meta is targeting 90% of ad revenue from verified advertisers by the end of 2026, up from 70%. In February, it filed its own lawsuits against scam advertisers in Brazil, China, and Vietnam, and sent cease-and-desist letters to eight former Meta Business Partners offering “un-ban” services to fraudulent advertisers.

The gap between Meta’s enforcement claims and the data in its own internal documents is the through line connecting every lawsuit. The company says it catches 92% of scam ads proactively. Its own projections estimated $16 billion in scam-related revenue in a single year. It removed 159 million scam ads. It served 15 billion higher-risk ads per day. It is investing in facial recognition to detect deepfakes. Its internal assessments concluded that scam revenue would exceed the cost of any regulatory settlement. The numbers do not cohere into a story of a company that failed to notice the problem. They describe a company that noticed the problem, measured it, calculated the cost of fixing it against the cost of not fixing it, and chose the option that preserved revenue. The lawsuits are, in that sense, not about whether Meta knew. They are about what it did with what it knew.

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Sourced from TNW

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Albanian YouTube is a blissful experience

For years, YouTube has been locked in a battle with ad blockers. Google has steadily tightened its detection systems, and many popular ad-blockers now struggle to work consistently on the platform. Even when they do, they’re often limited to desktop browsers, leaving people watching on phones, smart TVs, or streaming devices stuck with incredibly frequent and intrusive ad breaks.

Of course, there’s always YouTube Premium. But with subscription prices continuing to rise across the board, paying just to avoid ads isn’t always appealing. During my own testing, though, I found there’s another workaround that works surprisingly well.

Surfshark | 2 years + 3 months free | 7-day FREE trialTwo-year plan: $1.99 per month at Surfshark

Surfshark | 2 years + 3 months free | 7-day FREE trial
Two-year plan: $1.99 per month at Surfshark
Any quality VPN with a server location in Albania will block ads, but Surfshark provides the best mix of powerful privacy tools, ease of use, and excellent value.

Pros and cons:

🔖 Fully audited privacy
📺 Excellent streaming unblocking
💸 7-day free trial with no upfront payment
❌ Apps aren’t hugely customizable

After your 7-day free trial, Surfshark costs $1.99 per month, which works out at about $53 for two years of cover. There’s also a 30-day refund period after the free trial so you can make sure it works well for you.

How does connecting to an Albanian VPN server get rid of YouTube ads?

This neat little trick works because YouTube doesn’t show ads everywhere in the world. In order to display ads on videos, Google needs a functioning advertising market in that country. Albania currently isn’t part of YouTube’s monetized markets under the YouTube Partner Programme, meaning creators typically don’t earn ad revenue from viewers there.

As a result, far fewer ads are produced for that region. When I connect to a VPN server in Albania, YouTube believes I’m watching from there, and in my testing I haven’t seen a single ad in months of regular viewing, both on my laptop and my Apple TV.

To make this work reliably, you’ll need a good VPN. That means fast servers, reliable IP addresses, and an actual server location in Albania. Unfortunately, none of our top-rated free VPNs offer any servers in Albania, so a paid VPN is usually necessary.

It’s also one of the only reliable and simple ways to reduce YouTube ads on streaming devices like Apple TV, Fire Stick, and smart TVs, where traditional ad blockers don’t work.

How to block YouTube ads with a VPN

Several pop-up ads and an emoji face looking annoyed

(Image credit: Getty Images)

Blocking YouTube ads with this method is fairly simple. The key step is connecting to a VPN server located in Albania before opening YouTube. Here’s how I do it:

  • Choose a VPN with servers in Albania. Not every VPN offers Albanian servers, so check this before signing up. You’ll also want a service with fast speeds so videos stream smoothly. SurfsharkNordVPNExpressVPN, and Proton VPN are all good choices that offer servers in Albania.
  • Install the VPN app on your device. Download the app for whichever device you’re using. Most major VPNs support iPhones and Android devices, Windows PCs and Macs, as well as streaming devices like Fire TV Sticks and Apple TV.
  • Connect to an Albanian server location. Open the VPN app and select Albania from the server list. Once connected, your internet traffic will appear to come from that country.
  • Open YouTube and start watching. With the VPN active, launch YouTube as normal. In my experience, videos start playing immediately without the usual pre-roll ads. If you’re watching on a smart TV or streaming stick, you can either install the VPN app directly on the device or connect the VPN through your router.

Which VPNs work for blocking YouTube ads?

Not every VPN will work well for this trick. To reliably reduce YouTube ads, you need a service that offers a combination of speed, stable connections, and servers in Albania.

Fast speeds are particularly important because all of your video traffic is routed through the VPN. A slow connection can lead to buffering or lower video quality, especially when watching in HD or 4K.

You’ll also want a VPN that supports a wide range of devices. If you plan to watch YouTube on a Fire TV Stick, Apple TV, smart TV, or phone, the provider should have dedicated apps or easy setup instructions for those platforms.

Strong privacy protections matter too. Look for services that have independently audited no-logs policies, meaning they don’t record your browsing activity.

Among the most reliable options are Surfshark, NordVPN, and ExpressVPN. Surfshark is one of the most affordable and offers a 7-day free trialNordVPN is consistently rated as one of the best VPNs overall, and ExpressVPN is particularly easy to use for beginners.

Disclaimer

We test and review VPN services in the context of legal recreational uses. For example: 1. Accessing a service from another country (subject to the terms and conditions of that service). 2. Protecting your online security and strengthening your online privacy when abroad. We do not support or condone the illegal or malicious use of VPN services. Consuming pirated content that is paid-for is neither endorsed nor approved by Future Publishing.

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By Jasmine Sheena

It’s dubbed YouTube Creator Partnerships, and it’s designed to consolidate creator campaign management in one place.

If there were three takeaways from YouTube’s 2026 NewFronts announcements this year, we’d boil it down to this: creators, creators, and creators. Which is not to be confused with last year’s YouTube NewFronts which were also about…creators.

The Rise of the Creator may sound like a new Star War, but it’s clear that “creator” has entered big-business territory, and it’s something marketers want to tap into. According to IAB’s November 2025 report on the creator economy and ad spend, creator ad spend “is projected to reach $37 billion in 2025, up 26% year over year and nearly 4x faster than the media industry’s overall growth. Over the past three years, creator advertising has more than doubled—from $13.9B in 2021 to $29.5B in 2024—as brands increasingly treat creators not just as social media partners but as a full-fledged channel.” YouTube, of course, is a major creator hub, and this year, the platform is rolling out new tools for brands to connect with creators, complete with new features powered by Google Gemini.

Feature image credit: Kaspars Grinvalds/Adobe Stock

By Jasmine Sheena

Jasmine Sheena is a reporter for Marketing Brew writing about adtech, Big Tech, and streaming.

Sourced from Marketing Brew

By Michael Serazio

OpenAI has started rolling out conventional ads in ChatGPT. It won’t stop there.

The inevitable has arrived. Ads have begun popping up on ChatGPT—even, reportedly, in initial responses to user queries, rather than after extended conversations—and some fans aren’t pleased. “RIP ChatGPT,” wrote one Reddit commenter. “It was fun while it lasted! 💔” The ads, which are being rolled out to free users and those who pay for the lowest-tier subscription ($8 per month), are rather familiar and banal in their presentation: a “sponsored” box pitching a product that ChatGPT’s algorithm thinks is relevant to the conversation, much as you’re used to seeing on social media platforms like Facebook and X.

An enduring feature of advertising is that it is “geographically imperialistic”: The best place to put an ad is where one doesn’t exist already. But the best type of ad to place is one that is unrecognizable as an ad. These truths should be kept in mind amid the rollout of ads on ChatGPT. Rest assured, this is just the beginning of how OpenAI, the creator of ChatGPT, will monetize its users. The company will undoubtedly graduate to more sophisticated ads, at which point the only question will be whether users even realize when they’re being monetized.

Artificial intelligence is an unfathomably expensive product to give away for free, yet that’s been OpenAI’s main strategy to achieve adoption. So it’s little wonder that the company is in dire financial straits, facing tens of billions of dollars in projected annual losses. How else to close that deficit save for digital billboards? The geographic expanse for commercial colonization—a reported 800 million weekly active users—was simply too vast for OpenAI to forgo.

So ChatGPT’s users are right to bummed. Commercials clutter both the aesthetic and impetus of the online space. And the annoyance isn’t merely a pop-up to be blocked or a pre-roll to be skipped: Ads can’t help but corrupt the purpose of the content that they surround. But even OpenAI’s CEO, Sam Altman, has admitted that ad monetization is a real downer. “I think that ads plus AI is sort of uniquely unsettling to me,” Altman said in 2024. “When I think of GPT writing me a response, if I had to go figure out, Exactly how much was who paying here to influence what I’m being shown? I don’t think I would like that.” But he also, notably, did not rule out ads on ChatGPT in the future.

As the old adage goes: If you’re not paying for the product, then you are the product. For two centuries, the mass and social media industries depended on this bargain. Nascent newspapers of the “penny press” era could be sold below cost because advertisers subsidized the access to audiences. Likewise, today, no one pays for Google search or Instagram or TikTok.

AI represents a qualitatively different revelation. It renders all the knowledge of the internet conversationally interactive. It outsources our critical thinking skills and regresses our decision-making to the mean. It’s been designed to seem human to secure our trust. It seduces our affections and indulges our delusions, often sycophantically so. It subs in for our therapists and friends alike and helps us raise our children.

The consumer insights from that level of intellectual, emotional, and social intimacy exceed an advertiser’s wildest dreams. Fortuitously so: AI arrives at a confusing, anxious time on Madison Avenue. Google’s AI summaries are disintegrating the web as we know it, hastening a “zero-click” future, in which users have no need to avail themselves of the links below on the page. Hence, a shift from search engine optimization to “answer” or “generative” engine optimization: strategizing how brands and products appear, organically, in large language model inputs and outputs.

ChatGPT makes that roundabout sell a much straighter line—for a price. And it is reportedly a steep one—with ad rates nearing those of NFL games. Large language models might be a black box—in terms of why they do what they do—but that ad pricing suggests OpenAI knows exactly what a gold mine of personal data it is excavating daily.

That’s why we ought to treat OpenAI’s claims about its advertising with the same skepticism applied to the advertising itself. Sure, the company says it will insulate the ads as ostensibly independent from content. “Ads do not influence the answers ChatGPT gives you. Answers are optimized based on what’s most helpful to you. Ads are always separate and clearly labeled,” the company insistsWe keep your conversations with ChatGPT private from advertisers, and we never sell your data to advertisers.” But that leaves a lot of marketing money on the table—and from the outside, it sure looks like OpenAI needs that money to stay afloat.

Hence, the Super Bowl ad diss from OpenAI competitor Anthropic, the maker of Claude, whose commercial mocked the sponsored content that will inevitably intrude and inundate ChatGPT feeds. But mount that high horse at your peril, Anthropic. Unless there’s a clever way to pay for all those server farms and microchips, all other AI platforms will probably have to follow suit. (And if the Pentagon cuts ties with Anthropic, as it’s threatening to do, that day may come even sooner.)

The history of social media foretells it: Platforms and their creators, once unspoiled by corporate backers, now pitch us relentlessly—and in increasingly devious ways. “Native” ads on Instagram and TikTok often look indistinguishable within the content, forming the basis of the $30 billion influencer industry. But the notion of placing an energy drink in the background of an influencer’s video will soon seem laughably conspicuous. By that point, the problem for ChatGPT users will no longer be that they notice and get annoyed with ads. The problem—and the real money to be made by OpenAI—will be when they don’t.

Feature image credit: Marcin Golba/NurPhoto/Getty Images

By Michael Serazio

Michael Serazio is a professor of communication at Boston College and the author, most recently, of The Authenticity Industries: Keeping it ‘Real’ in Media, Culture, and Politics.

Sourced from TNR

A whole industry of data brokers buys up vast quantities of electronic information from cell phone apps and web browsers and sells it to advertisers who use that data to target ads. The same industry also sells that data, including bulk cell phone location data, to police departments and federal government agencies in ways that can reveal intimate details about Americans without a warrant.

Now, privacy advocates say that the best chance for Congress to close the well-known loophole around the Fourth Amendment that allows for that sort of governmental snooping is coming up in just a few weeks.

That’s when Congress is expected to take up reauthorization of what is known as Section 702 of the Foreign Intelligence Surveillance Act, which is set to expire on April 20.

After a 2015 change to the law, federal agencies are not supposed to collect data on U.S. citizens in bulk. But some found a workaround to requesting warrants by simply buying the data instead.

Last week, some 130 civil society organizations signed on to a letter urging members of Congress to include closing the data broker loophole in FISA 702 reauthorization, citing the “unprecedented expansion of warrantless mass surveillance that is sweeping up the private information of communities across America” and the potential for the loophole to be used “to supercharge AI-powered surveillance.”

At a Senate hearing last week, Sen. Ron Wyden (D-Ore.) asked Federal Bureau of Investigations director Kash Patel if he would commit to not buying Americans’ location data, which is usually obtained from cell phones. Patel declined to do so, instead saying the FBI “uses all tools” and “we do purchase commercially available information that’s consistent with the Constitution and the laws under the Electronic Communications Privacy Act, and it has led to some valuable intelligence for us.”

A spokesperson for the FBI declined to comment on which commercial data the FBI purchases. In 2023, then-FBI director Christopher Wray had indicated that the agency had backed away from using “commercial database information that includes location data derived from internet advertising.”

Location records from brokers are typically unlinked to a device owner’s name. But tools exist that help law enforcement track where a device has gone, where it spends every night and where it goes during working hours, said Bill Budington, a senior staff technologist at the Electronic Frontier Foundation, a privacy advocacy organization.

AI tools present new challenges for privacy

Artificial intelligence can be leveraged to make such data even more powerful. The CEO of the AI company Anthropic, Dario Amodei, warned in a statement last month that records the government can purchase can be used by AI to assemble “a comprehensive picture of any person’s life—automatically and at massive scale.”

Amodei’s unwillingness to allow Anthropic’s technology to be used for domestic mass surveillance or autonomous weapons has led to a major fight with the Pentagon, which says a private company cannot dictate how the government lawfully uses its technology.

In addition to the FBI and the Department of Defense, Immigration and Customs Enforcement is also among the federal agencies that have had known contracts for tools that rely on cell phone location information sourced from data brokers. These developments come as ICE is ramping up its efforts to surveil not only immigrants who are targeted for deportation, but also people who record federal agents and protesters, using tools such as facial recognition, license plate data and administrative subpoenas to tech companies for user information.

Earlier this year, ICE requested information on a federal procurement site for industry feedback about “commercial Big Data and Ad Tech” that could be used in its investigations, as was first reported by WIRED.

Last year, ICE signed a contract with the company Penlink for its program Webloc, which can be used to track the movements of mobile phones or find phones that have visited specific places, according to reporting by the tech news outlet, 404 Media.

A Penlink spokesperson told NPR in a statement that the company “understands the sensitivity and complexity of data privacy” and “the vendors we use to make location data available to our customers filter out sensitive locations, such as hospitals, schools, and religious institutions.”

The statement continued, “We are committed to complying with applicable laws and regulations, as our customers are required to do, and we update our practices as those laws change.”

ICE did not respond to NPR’s request for comment about the phone tracking technology and how it’s used.

Government data purchases without a warrant are “contributing to an ever-expanding infrastructure of private sector surveillance that is hurtling us into a dystopian surveillance society,” Jeramie D. Scott, senior counsel and director of the Surveillance and Oversight Program at the Electronic Privacy Information Center, told NPR.

FISA bill is “only chance” this year to end bulk data collection

Privacy and civil liberties advocates say the upcoming FISA reauthorization debate is the best chance to close the so-called “data broker loophole” that federal agencies are using to purchase the kind of bulk data that Congress has already banned them from collecting themselves.

“This is very likely the only chance that Congress has this year to vote for meaningful privacy protections,” said Sean Vitka, executive director of Demand Progress, an advocacy group that has helped bring together an unusual coalition supporting federal surveillance reforms with backers from opposite sides of the political spectrum.

He added, without reform, “The Trump administration is walking around with the most dangerous surveillance powers in recent history,” given recent advances in AI, expanding use of data from brokers and changes to FISA that Congress passed in 2024.

Rep. Warren Davidson (R-Ohio) along with conservative Sen. Mike Lee (R-Utah), teamed up with Democrats Rep. Zoe Lofgren and Wyden on bicameral bipartisan FISA reform legislation that would end the data broker loophole among several other reforms.

“This is one of those issues that really doesn't break on party lines,” Rep. Warren Davidson (R-Ohio) told NPR. “You're collecting data that really you would never get a warrant for, that kind of a broad dragnet sweep under normal warrant requirements.” he said.

“This is one of those issues that really doesn’t break on party lines,” Rep. Warren Davidson (R-Ohio) told NPR. “You’re collecting data that really you would never get a warrant for, that kind of a broad dragnet sweep under normal warrant requirements.”

Kevin Dietsch/Getty Images

“This is one of those issues that really doesn’t break on party lines,” Davidson told NPR.

Davidson said when the federal government purchases data broker data, “You’re collecting data that really you would never get a warrant for, that kind of a broad dragnet sweep under normal warrant requirements,” he said.

He also hopes to shut another loophole, known as the “backdoor search” loophole, by ending the practice of federal agencies searching Americans’ communications without a warrant that were swept up with the collection of bulk communications of foreigners outside the country.

But tying reforms to FISA’s reauthorization faces opposition from members of both parties. The White House and House Speaker Mike Johnson are both pushing for a clean reauthorization of FISA that would include no changes, and there are some Democrats who have indicated they support that plan to ensure the law does not lapse.

Still, amid opposition from members of his own party over a clean reauthorization, Johnson delayed a House vote on the issue until mid-April.

Courts have not weighed in on the practice of the federal government buying up bulk data from data brokers, making it an untested legal grey area. Privacy advocates argue the practice circumvents the Fourth Amendment and is contrary to a 2015 law that bars federal agencies from collecting bulk data on Americans. That law, the USA Freedom Act, came after former National Security Agency contractor Edward Snowden leaked classified information on how the agency was collecting Americans’ phone records.

Purchasing bulk data from data brokers is “very much not what Congress intended when it said we are banning bulk collection,” said Jake Laperruque, deputy director of the Security and Surveillance Project at the Center for Democracy and Technology. “It wasn’t, you know, ‘do bulk collection, but also pay taxpayer money for it.’ It was ‘don’t do bulk collection.'”

Privacy advocates like Laperruque also believe they have Supreme Court precedent on their side. In a 2018 case known as Carpenter v. United States, the court ruled that law enforcement needs a warrant to obtain a person’s historic cell phone location data from cell phone towers.

Laperruque said the idea that law enforcement can purchase information from data brokers they would normally need a warrant for doesn’t make sense, particularly since he said it is often possible to identify individuals from supposedly anonymized data from brokers.

“We certainly wouldn’t imagine a scenario where the police said, ‘We’re going to search your house. We don’t have a warrant, but we paid your landlord $100 to give us a spare key. So now we’re searching your house without a warrant,'” Laperruque said.

Davidson said the fact that data brokers can sell identifiable information highlights that Congress needs to deal with a broader privacy law to protect Americans’ data. “But in the meantime, you know, governments are buying their way around the Fourth Amendment and we need to close that off.”

He added that this issue is exacerbated further by artificial intelligence, which “can harvest and collect the data in a way that humans never could and do it amazingly fast.”

The recent falling out between Anthropic and the Department of Defense has further highlighted the potency of combining AI with powerful records purchased from data brokers, said Laperruque.

“What kind of new Pandora’s box do we open when we not only have these huge quantities of data, but we have tools that can start to scan and analyze patterns in unprecedented ways and at an unprecedented scale that you can never do from human analysts,” he said.

Feature image credit: Mandel Ngan/AFP via Getty Images

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Sourced from npr