from the follow-the-science? dept

As statehouses ramp up for 2026, we’re seeing a familiar and concerning trend of lawmakers rushing to regulate the internet based on shockingly shaky science. From the California State Assembly to the Massachusetts and Minnesota legislatures, a wave of bills is crashing against the digital lives of young people, with proponents of these measures framing social media access as a “public health epidemic,” or a “mental health crisis,” even though we have yet to see any of the settled science that those labels usually invoke.

As a digital rights organization dedicated to the civil liberties of all users, EFF’s expertise lies in reminding lawmakers that young people enjoy largely the same free speech and privacy rights as adults. EFF is not a social science research shop, but we can read the emerging research. What that research shows is much more nuanced than what is claimed by those proposing to ban young people from social media, and it is clear that research and theories used to justify these sweeping bans is far from settled. The rush to ban access to digital platforms is being fueled by “pop psychology” narratives and a collection of statistically flawed studies that do not meet the rigorous standards required for such a massive infringement on youth autonomy and constitutional rights.

The Lie of A “Settled” Consensus

The current legislative push relies heavily on a specific, media-friendly narrative that the “great rewiring” of the adolescent brain is a proven fact. This theory suggests that smartphones and social media are the primary, if not sole, drivers of a global uptick in teen anxiety, depression, eating disorders, self harm, etc. While this narrative makes for a compelling airport-bookstore read, it quickly collapses under the scrutiny of the broader scientific community.

Independent researchers, including developmental psychologists from institutions like the University of California, Irvine, and Brown University, have repeatedly found that the evidence for such claims is mixed, blurry, and often contradictory. Large-scale meta-analyses covering dozens of countries have failed to show a consistent, measurable association between the rollout of social media and a decline in global well-being. In reality, we are seeing a classic case of what many of our middle school science teachers warned us about: “correlation” being sold as “causation.”  

Additionally, the studies used to support these measures often fail to account for or exclude significant alternative explanations for rising teen anxiety and depression, such as the lasting impact of pandemic-era isolation, the persistent threat of school gun violence, and mounting economic or climate-related stress. By focusing narrowly on social media, these findings frequently overlook the broader societal factors that also impact youth mental health.

The Cult of the “Anxious” Expert

The current push for blanket social media bans relies almost exclusively on the work of Jonathan Haidt, particularly his book The Anxious Generation. While Haidt is an amiable and brilliant storyteller, he is not a clinical psychologist or a specialist in child development. He is a social psychologist who writes about moral psychology at a business school. Nonetheless, the book has made it to every Best Seller list, and with Haidt revered as an expert on podcasts with massive reach, like Oprah, Joe Rogan, Michelle Obama, and Trevor Noah—his message has been heard by a large subset of society, which primarily relies on: no smartphones or social media before age 16, phone-free schools, and more “unsupervised, real-world independence.”

To highlight Haidt’s reach when it comes to legislation banning social media: the California committee analysis for the proposed California social media ban mentions Haidt 20 times; the Governor of Utah promoted the book as a “must-read” months before signing the nation’s first social media ban; Haidt is cited in bill analysis for the bill banning social media in Florida; his work is mentioned in a federal bill aiming to ban phones in schools; and he provided formal testimony before the U.S. Senate Judiciary Committee (Subcommittee on Technology, Privacy, and the Law) in May 2022. 

While Haidt’s research has been paramount to legislation stripping millions of young people of their rights to expression and connection, his conclusions are not without challenge, and many experts in the field argue that the evidence is less than ironclad. 

The “Bad Science” Fueling Social Media Bans

While we can admit that Jonathan Haidt’s “great rewiring” theory makes for a gripping narrative, we cannot ignore that independent researchers and statisticians have identified significant flaws in the data used to justify it. Which means we are currently watching policymakers legislate blanket bans based on evidence that would be rejected in almost any other field of public health.

The reality is that research has consistently disproven the oft-assumed link between social media use and poor mental health in youth, and actually indicates that moderate internet use is a net positive for teens’ development, and negative outcomes are usually due to either lack of access or excessive use. In one major study of 100,000 adolescents, a “U-shaped association emerged where moderate social media use was associated with the best well-being outcomes, while both no use and highest use were associated with poorer well-being.” We also know that young people’s relationship with social media is complex, as it provides them essential spaces for civic engagement, identity exploration, and community building—particularly for LGBTQ+ and marginalized youth who may lack support in their physical environments. 

But again, the image Haidt presents in his book is increasingly at odds with the broader academic consensus. As mentioned, critics argue that the evidence for the mental health impacts of social media is mixed, blurry, and often misinterpreted. NYU statistics expert Aaron Brown, writing for Reason, notes that many of the studies in Haidt’s exhaustive reference list are statistically unreliable or fail to show a strong causal link. Prof. Candace Odgers, a leading voice in psychological science, explains the “selection effect” that legislators often ignore:

“Hundreds of researchers, myself included, have searched for the kind of large effects suggested by Haidt. Our efforts have produced a mix of no, small and mixed associations. Most data are correlative. When associations over time are found, they suggest not that social-media use predicts or causes depression, but that young people who already have mental-health problems use such platforms more often or in different ways from their healthy peers.”

This raises a fundamental question of legislative responsibility: If the science is not settled, how can legislators confidently declare a “public health crisis” to justify stripping away young people’s First Amendment rights? By bypassing the rigorous, nuanced findings of the scientific community in favor of a more convenient narrative, legislators are choosing emotion over evidence. Before imposing such draconian restrictions on young people’s access to information, policymakers have an obligation to do the heavy lifting: to dig into the actual research and listen to the experts who are sounding the alarm on oversimplified conclusions.

The Dangers of “Social Contagion” Narrative

Perhaps the most troubling aspect of Haidt’s crusade is its overlap with ideological rhetoric that pathologizes the identities of marginalized youth, and how that makes its way through efforts to ban social media for youth. A recurring theme in the literature favored by proponents of social media bans is the idea of “social contagion“—specifically regarding the rise in young people identifying as transgender or non-binary. Haidt dedicates an entire chapter of his book to this (ch.6, pt 3, p. 165), talking about “Why Social Media Harms Girls More Than Boys,” stating that: 

“The recent growth in diagnoses of gender dysphoria may also be related in part to social media trends, […] the fact that gender dysphoria is now being diagnosed among many adolescents who showed no signs of it as children all indicate the social influence and sociogenic transmission may be at work as well.”

These harmful theories suggesting that social media is “infecting” young people with gender dysphoria are false and not supported by peer-reviewed clinical research. But by legitimizing “experts” who promote these debunked theories, legislators—especially those in states like California who pride themselves on being a sanctuary for LGBTQ+ youth—are inadvertently platforming the same rhetoric used in other states to ban gender affirming care for youth. This “social contagion” narrative is a tool of exclusion, not a scientific reality, and we must be wary of any “public health” argument that treats community-building and self-discovery among marginalized young people as a “purported mental illness” spread via TikTok.

A Better Path: Digital Wellness, Not Bans

Fortunately, there is a measured, evidence-based alternative already emerging. California’s A.B. 2071, for instance, is a student-authored “digital wellness” bill that offers a measured, evidence-based alternative rather than prohibition. The bill advocates for a curriculum that teaches students how to manage algorithms, recognize cyberbullying, and regulate their own relationship with technology. Instead of trying to completely shield young people from social media, education-based approaches empower young people and have the benefit of providing skills that stay with a young person long after they leave the classroom. 

JustLeadershipUSA, a criminal justice organization, has a slogan that rings true in this instance too: “Those closest to the problem are closest to the solution.” So let’s start listening to what our young people are asking us for—more education—instead of imposing paternalistic, disempowering bans.

Legislating With Precision instead of Emotion 

Adolescent mental health struggles are a complex, multifaceted crisis. It is a crisis that has existed for as long as time, and has been driven by economic instability, the opioid epidemic, the threat of school violence, amongst other issues. To pin all of society’s woes on a smartphone app is not just a scientific error; it is a policy failure that ignores the real, material needs of young people both online and off.

Legislators must stop legislating as “anxious parents” and start acting as measured policymakers. Because for some youth, social media platforms are a lifeline. UNICEF and other global human rights organizations have warned that age-related restrictions and blanket bans can backfire in three critical ways: isolating marginalized youth (like LGBTQ+ youth, students in rural areas, foster youth, or those with disabilities) who social media is often the only place they can find a supportive community; necessitating invasive mass collection of biometric data or government-issued IDs from all users, including adults; and pushing young people toward less-regulated, “darker” corners of the web where content moderation is non-existent and the risks of actual exploitation are significantly higher.

Legislators have a valid interest in protecting children, but that interest must be pursued through tailored, measured approaches. We cannot allow emotions or a collection of flawed data sets to justify a historic rollback of digital rights. 

Reposted from the EFF’s Deeplinks blog.

Filed Under: addiction, harm to children, jonathan haidt, protect the children, research, social media

AI + ML

Listening to your customers? Who are you, and what have you done with Microsoft?

Microsoft has made Copilot a little less in-your-face with the option to banish the assistant’s Dynamic Action Button to the toolbar.

The change, rolling out this week, comes after howls of outrage from customers over Microsoft’s decision to drop a Copilot button onto user workspaces. 

Although the desire to get users clicking on the assistant is understandable, obscuring content in its productivity applications was perhaps not the best way to do it.

Microsoft’s forums show plenty of frustration with the floating button. Some call it “infuriating,” while others are less tactful. One Excel user wrote: “Did you let copilot design this idea and no human review it? Such abomination.”

Another said: “Putting a button over the working content was not a good move by Microsoft,” which gets to the heart of the problem. Redesigns and interface tweaks will always generate strong feelings. However, obscuring content with something that many don’t want is arguably a step too far.

There was already a way to turn off Copilot features in Excel and Word via the Settings screen, but the latest update indicates that Microsoft has paid attention to recent feedback. A user commented: “There needs to be a toggle or something to move it back to the ribbon,” and that is pretty much what Microsoft has done.

A new option has been added to the button’s menu, “Move to ribbon,” which does exactly that. Click it, and Copilot is banished to the ribbon. The floating Copilot Dynamic Action Button is no more, although it can be moved back if a user happens to miss that particular design decision.

Microsoft has acknowledged that forcing Copilot on users was not universally welcomed. Windows boss Pavan Davuluri promised a reduction in Copilot entry points and a rethink of how the technology is integrated into the operating system (because of course it isn’t going away any time soon). Earlier in May, Microsoft said it would “streamline” access to Copilot in its productivity applications.

Alas, that “streamline” involved the Copilot button, and plenty of customers asked for the ability to shift it back to the ribbon.

Less than two weeks after the initial announcement, Microsoft has responded. Although Copilot will still be there, the option to move it back to the ribbon is a move in the right direction. ®

Patients who use mobile applications to manage medical conditions including depression and chronic pain might assume the apps have been evaluated by regulatory agencies to be safe and effective. But that isn’t necessarily the case.

Most of the more than 55,000 medical apps that claim to diagnose or treat a condition—or ones that provide clinical decision support, known as “therapeutic” apps—have never been assessed by any trusted neutral bodies or regulatory agencies to evaluate them for technical soundness, ethical design, or clinical benefit. The apps often don’t comply with regional data security and privacy laws to protect people’s sensitive health information.

Medical apps differ from traditional wellness apps, which provide users with insights into becoming healthier by, for example, tracking fitness activities, monitoring blood pressure, and analyzing sleep patterns.

There is no reliable way to verify that therapeutic apps deliver the results they indicate. To help ensure such apps are credible, the IEEE Standards Association (IEEE SA) recently launched the IEEE Global Medical Mobile App Assessment and Registry. The publicly searchable directory is designed to list apps that have been vetted by experts across several criteria including technical soundness, ethical design, compliance with data security and privacy regulations, and clinical efficacy, which is evidence of a clinical benefit for the patient.

“Patients, clinicians, payers, and health care systems often struggle to distinguish clinically meaningful therapeutic apps from those that are simply well-marketed,” says IEEE Senior Member Yuri Quintana, chair of the assessment and registry program. He is chief of the clinical informatics division at Beth Israel Deaconess Medical Center, in Boston. “Our goal is to establish a standardized review method using criteria developed by experts.”

Why regulation is lacking

Because the apps are intended for medical use without being part of a medical implement, they fall under the designation of software as a medical device (SaMD), according to the International Medical Device Regulators Forum. SaMD is supposed to be regulated by public health agencies such as the U.S. Food and Drug Administration, but the apps have developed and grown in popularity so quickly that regulators haven’t been able to keep up, Quintana says. Some companies have received approval, but most have not, he says.

Many users are unaware of the regulatory gap, he says.

“Seeing an app from a well-known company often creates the impression that it has been meaningfully vetted for safety and efficacy, even when that is not the case,” he says.

Some companies are using deceptive advertising to sell their product, he adds. Marketing materials might claim that all of a company’s health apps are certified, even though only one app has been approved by a regulatory body to treat a particular condition. Or the verbiage might imply the company has clinical evidence proving its application works, even though the app has never been tested independently.

Another concern is that updated apps aren’t being vetted, says Maria Palombini, IEEE SA’s director of health care and life sciences global practice lead.

“The original app might have received approval from a regulatory agency, but not the updated version,” Palombini says. “There could have been significant changes from the original.”

“Not every medical-related app triggers the same regulatory classification or review across jurisdictions,” Quintana adds. “That leaves a large gray zone of clinically relevant but lower-risk apps that haven’t undergone an independent assessment. The IEEE registry was created to help fill these gaps.

“IEEE is the best organization to address this problem because this is fundamentally a standards, trust, interoperability, and conformity assessment challenge,” he says. IEEE “is the world’s largest technical professional organization, with deep expertise in developing globally recognized standards including in health care, cybersecurity, AI ethics, and interoperability.”

“Through the IEEE Conformity Assessment Program, we already run rigorous assessment and registry programs,” Palombini says. “Our neutral, consensus-driven, multidisciplinary approach—bringing together clinicians, regulators, developers, and ethicists without commercial bias—makes IEEE uniquely positioned to create trustworthy global guardrails that can scale across jurisdictions and support regulatory harmonization.”

How the registry works

The assessment framework was developed by a multidisciplinary group of 35 volunteer experts from 10 countries, Quintana says. The panel includes academics, AI experts, app developers, clinicians, ethicists, mental health experts, patient advocates, regulators, researchers, technologists, and those who assess safety in health care.

The registry is for any app used for clinical care or therapeutics that claims to demonstrate a medical benefit. That includes apps designed for cardiology, diabetes, mental health, neurology, oncology, rehabilitation, and respiratory diseases, Quintana says.

Initially, he says, the focus will be on apps that aim to treat mental health conditions, given the large number of offerings in that area and the registry committee’s expertise.

The submission of apps is voluntary. There is no government mandate that requires a company to use the IEEE registry.

The products will be evaluated against about 150 consensus-based criteria across three major areas:

• Clinical efficacy including therapeutic effectiveness, any sustained benefits, risk management, comparison to standard care, user engagement, and real clinical value.
• Technical soundness including accessibility, privacy and security, error handling, interoperability, AI governance, usability, and operational quality.
• Ethical design including bias prevention, patient consent, data governance, conflict-of-interest transparency, responsible use of AI and large language models, and prioritization of public health benefits.

IEEE charges a nonrefundable submission fee that covers the cost of the assessment plus the registry’s annual subscription for the first year.

Developers first must demonstrate they are a legally established entity before they can complete the app publisher registration form and then submit documentation and attestations about the product.

The IEEE review of an app is estimated to take six to eight weeks, Palombini says. The assessment results will be privately shared with the app publisher, she says, and to be listed in the registry, an app must achieve more than 85 percent compliance in each category.

Upgraded apps must be submitted and reassessed, Palombini says. Similar to how users are notified when an app on their smart devices has , the registry will be notified when listed apps have a new update available, she says.

Applicants who do not pass the assessment are to receive feedback explaining why. They will be given an opportunity to make changes or provide additional documentation, Palombini says.

“It’s a pretty methodological process, with checks and balances,” Quintana says. “We’re being very transparent about the process.”

Approved apps added to the registry receive an IEEE certification badge and submission identifier, which the company can display on its website, app store listings, and marketing materials.

“The badge serves as visible proof that the app has met the independent, consensus-based assessment for clinical value, technical robustness, and ethical design,” Quintana says.

The registry will be publicly available at no cost, he says.

Patients and families seeking safe, trustworthy apps—and payers and insurers evaluating reimbursement potential—will find the registry helpful, he says.

The application website is open. The public registry page does not yet list a specific count of approved apps because assessments are ongoing. Approved apps and their unique identifiers are to be published when the initial reviews are completed.

To learn more, you can watch a webinar recorded in March.

The assessment framework that underpins the registry is supporting the formal recognition of IEEE P3962 Standard for Criteria Assessment Framework f

from the I’m-sorry-I-can’t-do-that,-Dave dept

Late last year we wrote about a new startup that was flooding the internet with AI-generated podcast slop. Featuring fake hosts having fake discussions, the startup proudly stated it was creating about 3,000 new AI-generated podcasts every single week. The owners of the startup (who called critics of AI slop “Luddites,”) stated that because they cost so little to produce, even selling 30 episodes for a dollar nets them a tidy profit when scaled up appropriately.

That this results in an internet positively full of lazy mass-produced cack — and what that does to the public interest, authentic creators, and informed consensus — doesn’t really enter into it.

Not to be outdone, Amazon appears poised to join the AI slop podcast race. The company announced this week that it had begun mass producing AI-generated podcasts featuring two fake experts having conversations about all sorts of stuff. More specifically, Amazon is reformatting Alexa+’s extended answers on different topics and turning them into “podcasts.”

During this process, Jeff Bezos owned software will express manufactured opinions on all sorts of things, from the death of monoculture to the health of the U.S. recording industry:

“In an example clip shared by Amazon of the new Alexa Podcasts feature, the two AI-generated hosts discuss “the latest music releases.” A male Alexa+ narrator says more than 50% of music listening now comes from unsigned artists. “The monoculture is just gone,” a female-voiced Alexa+ narrator chimes in. The male Alexa+ host says there has been “stoner metal,” indie pop and experimental hip-hop music “all dropping on the same Friday,” and adds, “That’s not chaos — that’s the healthiest the music ecosystem has ever been.”

Cool.

For some reason the Variety story didn’t quote the best part of the shared Amazon example clip; namely where software in a female voice informs you that there’s no gatekeeping anymore and authenticity rules the day:

“There’s no gatekeeping anymore. If you make something real people are going to find it, and the algorithm is working for artists in a way it wasn’t five years ago.”

Clearly concerned that people would accuse them of creating yet more lazy and quickly automated engagement slop in the era of AI obituary scams, Amazon is pinky swearing that journalists will play a central role in fact-checking the content:

“Seemingly to dispel the notion that these “podcasts” will be AI audio slop, Amazon emphasized that it has deals with major news organizations to ensure “accurate, real-time news and information.” Those include the Associated Press, Reuters, the Washington Post, Time magazine, Forbes, Business Insider, Politico and USA Today; publications from Condé Nast, Hearst and Vox Media; and more than 200 local newspapers across the U.S.”

All that extra journalistic manpower just laying around from places like the Jeff Bezos owned Washington Post (which just fired 300 journalists and shitcanned its last black female opinion columnist). Or Business Insider, one of the cornerstones of what I call “CEO said a thing!” pseudo journalism. Or Forbes, which now just lets any random yahoo contribute as a “regular columnist.” Or Vox, which is about to be sold off to Rupert Murdoch’s kid. Or Politico, the website owned by a rich German Trump fan.

You know, all the places that have been hollowed out by layoffs and mismanaged into the ground by incompetent billionaires who have no idea how anything works and are keen to produce a giant badly automated engagement ouroborus that shits money without needing to pay human beings a living wage (or health insurance).

In effect they’re using software automation to algorithmically hijack and repackage the informed expertise of other people, then reselling it to you as something new. With some lip service to the idea that there are enough journalists left to maintain factual quality control over large language models prone to errors, plagiarism, and all sorts of disastrous fuckery at scale.

I desperately want to believe that as we accelerate into the era of badly automated mass engagement slop, there will be a value premium placed on authentic expertise. That the bland homogenized vibe coded half-assed sameness being plattered up at impossible new scale will usher forth a renaissance for real connection, genuine skill, actual talent, and human expertise.

But then I remember what most people buy at the grocery store. And the kind of people dictating the contours of both large language models and our increasingly consolidated, authoritarian-friendly media gatekeeping systems. And I quickly have my doubts that authentic expertise and connection has any meaningful chance of being heard above the din.

Filed Under: ai, ai slop, authenticity, engagement, expertise, jeff bezos, media, podcasts

Companies: amazon

Biometric authentication is no longer limited to fingerprints and face unlock. Researchers are now exploring whether your earbuds can recognize you simply by listening to the tiny vibrations created by your heartbeat.

A new study published on the arXiv preprint server introduces “AccLock,” a passive authentication system that uses standard earphone hardware to verify a user’s identity. Instead of relying on microphones or voice prompts, the system works through built-in accelerometers already found in many modern earbuds.

Your heartbeat may become your next password

The technology captures heartbeat-induced vibrations inside the ear canal, known as ballistocardiography (BCG) signals. These signals travel through bones and tissues, creating patterns unique to each person. That uniqueness is what makes the system interesting. Once the earbuds register a user’s BCG signal, they can continuously check whether the same person is still wearing them. If another user puts on the earbuds, the authentication fails automatically.

Unlike older earphone-based authentication systems, AccLock does not require users to actively interact with the device. The entire process runs quietly in the background, which could eventually make tasks like unlocking devices, approving payments, or entering smart homes feel almost invisible.

It works well — until too much movement is involved

To improve reliability, the researchers used a deep learning model and a multi-stage denoising system to separate user-specific heartbeat patterns from environmental noise and general body movement. In tests involving 33 participants, the system achieved false acceptance and false rejection rates of 3.13% and 2.99%, respectively, which is fairly promising for an experimental prototype.

However, heavy movement remains a major problem. Walking, talking, or shaking the head significantly increased error rates, showing that the system still struggles in real-world conditions. The researchers also tested the technology on Apple AirPods and found that it remained functional despite hardware limitations. While AccLock is far from becoming a commercial feature today, it offers a glimpse of a future where your earbuds quietly recognize you before you even unlock your phone.

I recently wrote an article on why I am excited about the upcoming MacBook Pro. One of the reasons mentioned there was the expected display upgrades, which will include the move to an OLED panel and quite possibly the addition of a touch screen. 

It seems that the OLED rumor is almost confirmed. According to TheElec, the OLED panels for MacBook Pro have already entered the mass production phase. Samsung Display has crossed a major manufacturing milestone, achieving a yield of over 90% for its 8.6th-generation OLED panels. 

What does yield even mean?

In simple terms, yield refers to the percentage of panels that come out of production without defects. The display industry considers anything around 90% to be the sweet spot for mass production. Samsung has not only hit that number but pushed some individual processes to 95%, which the company calls a “golden yield.”

The process had only a 80% yield last month, so getting here in just over a month is impressive. Higher yields mean lower production costs, which can eventually translate into more affordable products for consumers. Although if Apple’s past record is anything to go by, the cost benefit will not be passed on to its users. 

Samsung Display is currently running one production line at half its total capacity, producing 7,500 sheets per month. The panels are headed straight for Apple’s 14-inch and 16-inch MacBook Pro models, with shipments expected to begin as early as next month and a supply volume of around 2 million units estimated for this year.

Why is making laptop OLEDs so hard?

Laptop OLED displays are significantly harder to manufacture than smartphone panels. They are larger, stay on for longer periods, and require higher brightness, better lifespan, and brightness uniformity across a larger surface area. 

Samsung’s panel uses a two-stack tandem structure that layers two light-emitting layers on top of each other, which is one of the reasons securing high yield has been such a challenge. It’s the same tandem-OLED technology that Apple uses in its iPad Pro lineup, which packs some of the best OLED displays on the market. 

If sales of OLED MacBook Pros go well, Samsung is ready to activate its second production line, which would double output almost immediately. MacBook Neo has already become a runaway success for Apple, and Apple might be looking for a repeat. 

However, the upcoming MacBook Pros are also rumored to receive a significant price hike, which might curtail some enthusiasm.

It’s been 17 years since I sat in on the iconic weekly search quality meeting in the Ouagadougou conference room at Google’s Mountain View campus. That Thursday morning, around three dozen engineers, product managers, and executives sat at a table or sprawled on the floor to discuss why certain search queries or categories didn’t yield a perfect result and to suggest fixes. In 2010 those meetings led Google to make 550 changes to its search algorithm, a number that seemed impressive at the time.

That memory seems like a tintype. At Google’s I/O developer conference this week, a keynote speaker—head of search Liz Reid—officially down-ranked good old-fashioned search to virtual oblivion. This was a continuation of a process that began two years ago, when Google introduced “AI Overview,” its summaries that sit at the top of its search results page and literally lurk over the famous “10 blue links.” By then those links had already been degraded, so that all too often the most relevant ones were buried beneath aggregators, spam, and Google’s own shopping results and maps. Now, in what Reid described as the most significant change to the search box in the company’s history, users are in direct communication with the latest version of Google’s Gemini. Even the term “query” seems outdated, as human inputs are conversation starters for the AI to collaborate. The process can also incorporate personal information Google knows about you, which can be a lot. The answer to a query could be a bespoke presentation, maybe bolstered by AI agents that forage digital backroads to root out information. The transformation is complete. Onstage, Google said it out loud: “Google Search is AI Search.”

The search box used to be a portal to the web. The new “intelligent” box is an invitation to order up a Gemini-powered, customized response to a user’s queries, sometimes even creating on the fly a bespoke mini-publication with charts, bullet points, and even animations. Google used to pride itself on interpreting cryptic search terms to divine user intent. Now it encourages searchers to engage with Gemini in a conversational prompt-a-thon. To emphasize the change, Google representatives at the conference wore T-shirts saying “Ask Me Anything,” reflecting the prompt that Gemini offers. Just as with the computerized version, if you asked for directions from these smiling aides, the answer did not result in a click to a website.

Our digital life these days is perched at an uncomfortable transition point. AI seems to be driving every business model, and giants like Google are weaving AI into all their products and operations. At the same time, there’s rising resistance and even disgust as this powerful and scary technology worms its way into our lives. Just note the boos when commencement speakers mention AI. But as Google sees it, AI search—if you still want to call it that—is an inevitability that even AI haters will embrace.

I was among those who recoiled at the introduction of AI Overview in 2024. Now I acknowledge that Overview—and the deeper “AI Mode” that it encourages you to use—is simply better for many things, whether finding out if Saturday Night Live has a new episode, getting an explanation of an agentic harness, or even finding a link. When I searched for my WIRED article where I described the meeting in the Ouagadougou, the blue links were less than useful. But when I explained in plain language what I was looking for, I found it immediately.

So it’s working. Google claims that more than a billion people a month are searching with AI Mode, a separate tab on Google’s website where links are even more peripheral. AI Mode queries are doubling every quarter.

Investing your money at the right time and right place is key to fighting rapidly growing inflation. But when we invest our hard-earned money, it is essential to know where the money is going, who is managing it, and how. There are numerous schemes and ways to invest your money. While doing so, we often come across many heavy financial jargons, and one of them is AUM. You must have often heard this in mutual funds. So what is AUM in finance, and why is it so important? 

Keep reading to discover interesting financial facts about AUM. 

What does AUM mean?

AUM refers to Assets Under Management, which is the total market value of investments managed by an investment manager/organization on behalf of their investor, with their consent. These assets can be anything, including stocks, bonds, mutual funds, ETFs, and other investment options. 

The global asset under management (AUM) is expected to reach $200 trillion by 2030, growing at a CAGR of 6.2%. See the detailed market reports here. 

How to calculate AUM? 

It is calculated by adding the total current market value of all investments being managed.

AUM = ⅀ (Current Market Value of all Assets)

The formula, which is used to calculate the daily AUM value:

AUM_today = AUM_yesterday + Net Inflows + Market Profit/Losses

Here, net inflows are your new investments minus the redemptions, and market gains & losses are value changes of assets due to price movements. 

How is your money turned into assets? 

When you invest your money, it is converted into assets that are far more valuable than your paper money. These are the things bought with that money. And the value of these things keeps increasing faster than actual money. It can be anything, such as digital gold, ETFs, mutual funds, shares, stocks, and property. 

Types of AUM Assets

As discussed above, your money can be converted into different types of assets by using it to buy various things. Let me tell you about some of them.

• Equities or Stocks: These are shares, or say you buy a certain percentage of a publicly traded company, including large-cap, mid-cap, and small-cap stocks.
• Debt Funds: These assets are essential components of mutual funds and emphasize fixed-income securities such as government bonds, corporate bonds, treasury bills, and marketable securities. They often have lower risks and a predictive outcome. 
• Hybrid Funds: It is where investment managers diversify your money across assets like equities, debt, and sometimes even instruments like gold. It gives investors a wider portfolio and a good option for people choosing growth with less volatility.
• Thematic & Sectoral Investment: These are specified mutual funds for targeted industries or well-rounded investment themes. These have high growth potential but also come with significant risks due to condensed exposure. The risks are generally due to economic lows or sector-specific downfalls.
• IFs and ETFs: The index funds or exchange-traded funds are passive investments that track the performance of a specific market index. People like their simplicity and cost efficiency. Mostly, retailers and institutional investors prefer these investments. 
• Alternative Investments: These investment approaches are different than traditional ones. Here you can invest in land, real estate, commodities, and gold. This can be used to diversify a portfolio, offer great returns over time, but comes with high risk. 

Each of these investment types has more in-depth subcategories.

Factors that Affect AUM

The AUM value often keeps fluctuating; sometimes you gain, and sometimes you lose. There are different factors behind this, and some of them are listed below.

1. Market Graphs

The market often experiences upswings and downturns, and your underlying assets increase and decrease in value, respectively. Highly volatile assets such as stocks, commodities, crypto currencies etc can be frequently impacted. 

2. Investor Activities

Here, AUM is affected by the investor’s action. Where there are inflows (new investments by investment) like buying new units, increasing capital, etc., the value of AUM increases. On the other hand, if there are outflows or redemptions by investors pulling out their money directly decreases the AUM. 

3. Distribution

When a fund pays out dividends or interest, the AUM reduces, and if these payouts are compensated or reinvested, the value increases. When the funds with better performance outperform, the benchmarks tend to attract people to invest more, and this leads to increased AUM. 

There are also some other factors, like sales and marketing. Different fund types, such as open-ended funds and different fund structures, also impact the AUM. 

How do AUM Managers Earn?

You must be wondering if someone is using the brains and resources to invest your money, then what do they benefit? So here is how asset management companies make money. 

These companies generally sell the investment solutions as products to their clients. They sell mutual funds, ETFs, and manage private accounts of other companies. In return, they either charge a fee or a percentage of assets under management. 

The charges consider some factors such as investment type, asset class, investment sector, and transaction complexity. For instance, when an investment strategy involves a cultured process and tools like trading or taking short positions, then the clients can be charged a high fee. 

Ongoing charge fee (OCF), performance fees, initial and exit charges, etc., are some charges incurred by companies that these agents charge to clients. 

Types of Asset Management Companies

Different types of investment are managed by different specialized companies for the same purpose. 

1. Mutual Fund Companies

These companies use the investor’s money to buy stocks, bonds, and other securities that align with the fund’s objective. These companies are best chosen by retail investors. The clients get fund units, and returns as per market performance. 

2. Hedge Fund Companies

This is most opted for by high-net-worth people and institutional investors, where they use plans like leverage, short selling, and derivatives. The aim is to gain high returns in all sorts of market fluctuations. This involves high risk but has fewer regulatory restrictions. 

3. Private Equity Firms

These are companies that invest directly in unlisted/private companies, or they pool capital from institutional investors and high-net-worth clients to take over, restructure, and improve private companies. Their goal is to increase their company’s worth over a period of time before selling it for a profit. 

4. Real Estate Investment Trusts (REITs)

The firms invest in income-generating assets of real estate, like commercial spaces. The investors earn returns from real estate without actually owning the property. These corporations manage high-value real estate portfolios. Leasing, selling, and collecting rents, and later distributing among the shareholders as their incomes and dividends. 

AUM vs. NAV

Benefits of Asset Under Management

• Shows you trust and scalability, a higher AUM indicates that the fund or company is a trusted one. It reflects credibility, market position, and investor confidence.
• Larger AUM shows that fund managers can help you diversify your investments. 
• When a company has bigger AUM, it can spread fixed costs for clients, which leads to lower expense ratios for investors. 
• Fund houses with larger AUMs have better negotiating power and broader investment opportunities.
• Better AUM indicates the stability of a fund management company. 

Conclusion

I hope this blog helped you understand what is AUM in finance. When you invest, you must know how and where the investment is happening. Learning and understanding about assets under management is the first step to doing so. We have discussed various aspects of it, such as types, risks involved, benefits, and how you can calculate AUM. I have also stated the clear difference between NAV and AUM, which often confuses investors. Keep reading, keep learning. And let me know in the comments, how you choose to invest your money? 

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