DIGITAL LIFE

Love at first prompt? How AI-assisted courtship is rewriting the rules of online dating

In the famous French play Cyrano de Bergerac, the brilliant but insecure Cyrano lends his eloquence to the handsome, tongue-tied Christian to help him woo his lover. Today, a remarkably similar scene is playing out among millions of dating app users, with the role of the lovelorn poet played not by a human but by AI. New research from Constructor University professor Dr. Lennart Ante analyzes the growing impact of dating app users outsourcing the delicate work of courtship—from the witty opening line to the flirtatious reply—to AI assistants like ChatGPT, Gemini or even specialized "wingman" apps like Rizz and Winggg.

The paper, "The Cyrano Effect: LLM-Assisted Impression Management and Authenticity in Online Dating," published in Telematics and Informatics, examines the implications of AI's growing incursion into the human dating pool. Recent surveys suggest more than 1 in 4 singles in the United States have already used AI to augment their dating lives, while a majority of dating app users believe they have exchanged messages with an algorithm at some point.

Drawing on 45 in-depth interviews with dating app users—including both those who use AI to write their messages and those who have received AI-assisted messages from a match—Ante's study contributes vital understanding of a phenomenon that is rapidly reshaping how millions of people meet, court and connect online.

"I had been seeing more and more stories in the news and online about LLMs, lovebots and people forming romantic relationships with these AI tools, something I find utterly fascinating," said Ante on the inspiration behind the research project. "While my own experience with dating apps is limited to occasionally seeing my friends swipe through Tinder, I couldn't help but wonder how AI might be creeping into these spaces as well."

How AI is changing dating...Over the past decade, online dating has become the definitive mainstream pathway to romantic relationships. It is now the most common way couples meet in the U.S. and is underpinned by a $3.2 billion dating app industry boasting hundreds of millions of users worldwide. Against this backdrop, generative AI is not a marginal curiosity but a tool that is becoming increasingly embedded in one of the most intimate domains of everyday life.

When the words that spark a first connection are no longer entirely one's own, it raises fundamental questions about what it means to be authentic, the nature of the human connections being formed and the real-world implications when AI-augmented online personas eventually meet in person and unassisted across a dinner table.

To address these questions, Ante conducted semistructured interviews with two distinct groups of dating app users: 23 individuals who reported using LLMs to help write profiles or messages, and 22 individuals who suspected or confirmed that a match had used AI in their communication. Participants were recruited from English-language online dating communities based primarily in the United States, the United Kingdom, Canada and parts of Europe. The interviews were analyzed using reflexive thematic analysis, an interpretive approach designed to identify and understand the meanings that participants themselves attach to their experiences.

"What we see in the result is a nuanced, qualitative portrait of an emerging social practice that quantitative studies have so far only been able to gesture at," Ante said. "Existing surveys and experimental work convincingly show that disclosing AI involvement tends to reduce trust and attraction. While this establishes that a problem exists, it doesn't tell us why, or what people are actually feeling in these moments.

"A number on a trust scale doesn't capture a recipient's experience of feeling 'violated' or 'stupid' for opening up emotionally, only to learn that they are interacting with AI responses. This is where the true value of this research lies."

Three themes from the study...Ante's study found three notable themes emerging from the data:

"The Authenticity Paradox" describes how users justify AI use not as deception, but as a way to express their "true" selves more accurately, with AI acting as a sort of prosthesis for social anxiety, linguistic insecurity or the perceived inefficiency of online dating.

"The Digital Betrayal" captures the experience of recipients who describe the moment they suspect or discover AI use as a violation of trust, and a sense that something fundamental about the interaction has been "faked."

"The Persona-to-Person Leap" traces the anxiety of moving from an AI-polished chat to an unassisted offline encounter—a transition that, in many cases, exposes a gap too wide to bridge.

Together, these themes give rise to what Ante calls the "Cyrano Effect": the entanglement of human and algorithmic authorship that reconfigures impression management, authenticity and trust in digitally mediated romance.

"My research focuses on actual lived experiences, where the real mechanism lives," Ante said. "By directly speaking with people, both those using the tools and those on the receiving end, I was able to assess the full arc, from the justification to the reveal, and finally, the awkward first date."

"What surprised me most was how coherent the justifications of AI users were, and at the same time, how deeply betrayed the recipients felt," Ante said. "The same act—such as using ChatGPT to draft a flirtatious message—can be experienced from one side as the ability to finally express one's true self, and yet from the other side as a fundamental violation of trust. That asymmetry is what makes this phenomenon so difficult for users, platforms and the broader culture of online dating."

Broader implications for online romance...Ante's study contributes to research on computer-mediated communication by extending classical theories of impression management, authenticity and trust into the age of generative AI. It introduces the notion of "prosthetic authenticity"—the idea that authenticity may increasingly be understood not as the absence of mediation but as alignment between one's inner self and outward expression, even when that expression is algorithmically augmented—and points to an emerging crisis of authorship, in which the once-safe assumption that "the person who writes is the person who speaks" no longer holds.

The findings also speak to a longer cultural trajectory in which intimate relationships are increasingly framed through the logic of markets, efficiency and self-optimization, with AI now extending that logic from the search for a partner to the communicative act itself.

Beyond its theoretical contribution, the study has direct practical implications. For platform designers, it raises the difficult question of how to respond to AI assistance. Outright bans are difficult to enforce and may penalize users who rely on AI for legitimate reasons, such as overcoming language barriers or communication anxiety, while a laissez-faire approach risks an undeclared arms race between AI generation and human detection.

The article argues that some form of transparency—optional, verifiable disclosure of AI assistance—may be the most viable, if imperfect, path forward. For individuals, it points to the need for a new kind of digital literacy: the ability to recognize when an eloquent message on screen may not be authored by the person on the other side, without sliding into blanket cynicism that makes genuine connection impossible.

"Ultimately, the question that animated Cyrano de Bergerac remains unresolved in AI-mediated romance," Ante said. "When we fall for these words, who or what are we really falling for? How we as scholars, designers and users answer that question will shape not only the future of online dating, but also our broader understanding of agency, responsibility and intimacy in a world where algorithms increasingly speak in our name."

Provided by Constructor University

TECH

Galaxy S27 and Xiaomi 18 spotted: Major Leica camera lineup changes expected

Months before launch, early traces of two of next year's likely most important camera flagship rivals have appeared in databases. Model numbers have been discovered for both the Samsung Galaxy S27 and an initial Xiaomi 18 model, with major changes to the lineup becoming apparent for the latter in particular.

In recent hours and days, traces of new next-generation Samsung and Xiaomi flagships have appeared in the GSMA database, better known as the IMEI database, usually one of the first concrete indications of a smartphone in development. Neither Samsung's 2027 lineup nor the Leica camera flagships from China are fully represented in the database yet, but the Xiaomi flagships in particular are already showing the first signs of changes that are also likely to affect the global Xiaomi 18 generation.

Samsung Galaxy S27...But let's start with the successor to the 6.3-inch Galaxy S26, which identifies itself as the US version of the Galaxy S27 with the model number SM-S952U. The number 952 can clearly be identified as the successor to the Galaxy S26 base model with the number 942, so despite rumors of a Galaxy S27 Pro model, there will likely once again be a more compact entry-level model in the roughly $900 price range in 2027.

Four global Xiaomi 18 models...The Xiaomi lineup is less clear, as Ximitime currently suggests. Here, too, an informative model number has been discovered in the IMEI database, namely 2611FPNFA, which has appeared in the database in multiple versions. 2611FPNFAR is the model for Japan, 2611FPNFAI is the model for India, and 2611FPNFAG is the global version. Interestingly, the China model does not use the usual C at the end but, according to the screenshot, carries the number M154FF, which the article unfortunately does not address.

Xiaomi 18 or Xiaomi 18 Pro? The fact that global Xiaomi 18 variants are being developed alongside the China model points to a change in launch strategy compared to recent years, something we already reported a few weeks ago. This could finally mean there will no longer be an almost six-month wait between the launch in China and the global release. A global Xiaomi 18 Pro would also be conceivable, though neither has been proven at this point.

According to earlier indications, the Xiaomi 18 is being developed under the codename "madrid", and in combination with a HyperOS code analysis by Ximitime, that now raises some questions. In theory, "madrid" should be assigned the abbreviation Q3, analogous to P3 for the Xiaomi 17. Instead, however, the code snippet below shows Q2, which according to the previous logic would actually point to the Xiaomi 18 Pro. Given the paused and potentially discontinued development of the Xiaomi 18 Ultra, it is conceivable that Xiaomi's model number logic has changed, according to Ximitime. It should be noted that model number analysis always carries some risk, since the manufacturer often follows a certain structure but can also change it at any time.

Xiaomi 18 launch not until November? That may also apply to another conclusion that could potentially be drawn from the discovered model numbers. As many readers may know, the first four digits of the number often indicate the earliest possible launch date, in this case 2611, meaning November 2026. Compared to recent years, that would be very late for the China launch, which took place in September 2025 last year. For the global launch, however, it would be early, as Xiaomi fans in Europe previously had to wait until the end of February of the following year. We are somewhat skeptical that Xiaomi will actually wait until November to launch the Xiaomi 18, so caution is also advised when interpreting these numbers.

mundophone

TECH

QNAP launches web-managed QSW-M2130 switches

QNAP announced the launch of the QSW-M2130 series, a web-managed L2 networking solution that combines access and aggregation functions in a single device, aimed at SMEs and multi-story enterprise environments. Introduced on May 27, 2026, the series consists of two models, the QSW-M2130-4C2S24T and the QSW-M2130P-2C2S26T, with 2.5GbE ports and 10GbE uplinks, the latter being compatible with the IEEE 802.3bt PoE++ standard.

The QNAP QSW-M2130 switches address a recurring problem in mid-sized IT infrastructures: the proliferation of network equipment as organizations grow. Each model integrates 24 RJ45 2.5GbE ports for connecting workstations, NAS devices, and peripherals, and 10GbE ports for aggregating traffic to the core network. This architecture eliminates the need for two separate switches per segment, reducing management complexity and infrastructure costs.

The standard model, QSW-M2130-4C2S24T, includes two 10GbE SFP+ fiber ports and four combined (RJ45/SFP+) 10GbE ports, allowing IT administrators to choose the connection type depending on the existing cabling. Connection flexibility is a relevant argument in buildings with mixed infrastructures, where fiber and copper cable runs coexist.

The QSW-M2130P-2C2S26T is a next-generation L2 managed switch with 24 2.5GbE Base-T ports, 2 10GbE SFP+ ports, 2 10GbE Base-T ports, and 2 10GbE Combo ports, integrating high-speed connectivity and PoE into a single device. The multi-Gigabit port design makes it ideal for deployment as an access and aggregation switch, supporting Wi-Fi 6/6E/7 APs, IP surveillance, and various powered devices. With support for VLAN, QoS, LACP, and ACL, in addition to the intuitive QSS (QNAP Switch System), it allows businesses to build a scalable, efficient, and easy-to-manage network infrastructure. The QSW-M2130P-2C2S26T is manufactured in Taiwan (MIT), offering a reliable and high-quality networking solution.

IEEE 802.3bt PoE++...Compatible with IEEE 802.3bt PoE++ standards. Offers PoE capabilities for 12 90-watt ports and 16 45-watt ports. Can provide a total power budget of 375 watts to meet the demands of high-power devices (PDs).

10GbE Connectivity...Two 10GbE SFP+ ports, two 10GbE combo ports, and two RJ45 ports can be connected to NAS, servers, or backbone uplinks, allowing for high bandwidth and redundancy.

Layer 2 Networking...Offers comprehensive Layer 2 management features (such as VLAN, LACP, ACL, and LLDP) so IT administrators can efficiently control network bandwidth and enhance security through the switch's easy-to-use web management interface.

Access and Aggregation in one...Suitable for both edge access and aggregation layers, it consolidates traffic from multiple 2.5GbE devices and uplinks via 10GbE to the core network, simplifying deployment in SMB environments.

SFP+/RJ45 Ports...Compatible with 10GBASE-T and 5GBASE-T technologies to support five speeds (10G / 5G / 2.5G / 1G / 100M), the QSW-M2130P-2C2S26T offers higher transmission speeds when used with existing cabling.

Online Operating System Update...QSS (QNAP Switch System) helps administrators update firmware with just one click, ensuring network security.

PoE++ for modern wireless infrastructure...The QSW-M2130P-2C2S26T model is designed for environments with high density of network-powered devices. Supports the IEEE 802.3bt PoE++ standard with a total power of 375W, ports with individual capacities of up to 90W and 45W, making it compatible with Wi-Fi 6, Wi-Fi 6E, and Wi-Fi 7 access points, 4K IP cameras, IP phones, and digital signage systems. Eliminating external power supplies for these devices simplifies installation and reduces the number of network failure points.

“The biggest challenge in today’s network is a disorganized architecture that expands out of control. The QSW-M2130 series offers a network that expands without losing control,” said Ronald Hsu, product manager at QNAP. Hsu added that the goal is to allow businesses to “maintain a simplified topology and predictable performance,” for both high-speed environments and infrastructures with high power requirements.

QNAP QSW-M2130: Centralized Management and Layer 2 Security...QNAP QSW-M2130 switches are managed by the QNAP Switch System (QSS), a web-based graphical interface that allows port configuration, traffic monitoring, and firmware updates without the need for command-line tools. The platform supports Layer 2 features such as LACP, QoS, VLAN, and IGMP Snooping, essential for efficient traffic segmentation in corporate networks.

In terms of security, both models integrate Access Control Lists (ACLs), DoS attack prevention, the Rapid Spanning Tree Protocol (RSTP), and flow control. These features protect the network against malicious traffic, prevent routing loops, and reduce packet loss in congestion situations.

QNAP positions the QSW-M2130 series as superior quality equipment, manufactured in-house in Taiwan. The availability date in Portugal and local distribution channels were not disclosed at the time of the announcement. The QNAP QSW-M2130 switches arrive in a market where the migration to multigigabit networks in SMEs is accelerating, driven by the adoption of Wi-Fi 6/7 and the growth of high-capacity network storage. The series positions itself as a direct response to this trend, without requiring a complete overhaul of the existing cabling infrastructure.

mundophone

 

TECH

Bitcoin in a zone of brutal fall and growing pessimism

After a brutal fall and a climate of growing pessimism, Bitcoin has returned to the spotlight. Experts disagree on the next step, but some signs are beginning to attract attention.

When an asset loses half its value in a few months, the natural reaction is fear. That is exactly what happened with Bitcoin, which went from historical highs to facing one of the most delicate phases in recent years. While investors try to understand if the worst is over or if new falls are on the way, analysts observe indicators that, in previous cycles, preceded important movements. The question now is simple, but the answer is far from being a consensus.

The recent devaluation of Bitcoin has shaken the confidence of part of the market. Not even the new purchase made by Strategy, a company led by Michael Saylor and known for its strong exposure to cryptocurrency, managed to change the prevailing sentiment among investors.

After falling about 50% from its all-time high above $120,000, Bitcoin began trading near the $60,000 range. This movement reignited discussions about the possibility of the market approaching a cycle bottom.

Some indicators used by analysts suggest exactly that. Among them is the MVRV Z-Score, a metric that compares the current price of the cryptocurrency with the average cost of acquiring the coins in circulation. Historically, when this indicator approaches certain zones, Bitcoin is usually close to ending major corrections.

Another piece of data observed by the market shows that more than half of cryptocurrency holders are operating at a loss. In previous cycles, similar situations occurred shortly before significant recoveries.

Analysts at the asset management firm 21Shares highlight that the current sentiment is reminiscent of moments of extreme pessimism seen after traumatic events for the sector, such as the collapse of the FTX brokerage in 2022. At that time, many investors believed that the recovery would take years, but the market surprised in the following months.

For more optimistic managers, the current correction still fits within the historical patterns observed in Bitcoin. The difference is that recent drops have been less deep than those recorded in the major bear markets of the past, something interpreted by some experts as a sign of the asset's maturation.

Risks remain and require caution...Despite the positive signs, not everyone shares the same enthusiasm.

Some analysts believe that the market may still face a prolonged period of weakness. Among the factors cited are the reduction in institutional interest, the search for opportunities in companies linked to artificial intelligence, and the migration of capital to other sectors considered more promising in the short term.

According to this view, Bitcoin ends up suffering as an indirect consequence of a large reallocation of resources within global markets. As it is a highly liquid asset, it often becomes one of the first sources of funds when investors decide to seek new opportunities.

Another point that worries some experts is the lack of a significant price reaction even after announcements considered positive. When good news fails to trigger significant increases, this usually indicates that the market has not yet fully recovered its confidence. Furthermore, some technical indicators show that the recovery potential may be more limited than in previous corrections. This does not necessarily mean that a rally is impossible, but it suggests that the path may be slower and more turbulent.

Why the long-term thesis remains alive...Even in the face of volatility, many analysts continue to defend Bitcoin's structural thesis.

One of the main arguments is related to the increasing diversification of investors participating in this market. Unlike the first cycles, when demand depended mainly on retail investors, today the ecosystem includes ETFs, pension funds, wealth managers, and even sovereign investors.

This change helps reduce dependence on short-term speculation and strengthens the institutional presence in the sector.

Another frequently cited factor is the protocol's own structure. Since its launch, Bitcoin has continued to operate according to the original rules established by its creator. The maximum limit of 21 million units remains unchanged, and issuance follows a rigid mathematical schedule.

For cryptocurrency advocates, this predictability remains one of the asset's most valuable characteristics, especially in a global landscape marked by economic and monetary uncertainties.

Buy, wait, or sell? Most experts avoid extreme answers. Instead of recommending aggressive buying or total liquidation of positions, many advocate a gradual strategy. The idea is to build exposure over time, making periodic contributions and reducing the impact of short-term fluctuations.

This method avoids trying to pinpoint the exact bottom of the market, something that has historically proven almost impossible even for experienced investors.

Among the most optimistic projections, some analysis firms are working with the possibility of Bitcoin surpassing significantly higher levels by the end of 2026. For this to happen, however, the cryptocurrency will need to recover important technical regions and rely on favorable external factors, such as an improved macroeconomic scenario, a resumption of flows to ETFs, and regulatory advances in the United States.

Meanwhile, the main recommendation remains the same: discipline, risk management, and a long-term focus. After all, if there's one thing Bitcoin's history has shown many times, it's that periods of extreme fear are usually precisely those that most test investors' conviction.

mundophone

TECH

HP TPM Guard overrides critical BitLocker flaw

The HP Imagine 2026 event was the stage for the presentation of HP TPM Guard, a security solution designed to protect computers against physical access attacks aimed at data theft and device manipulation. HP launched the technology to prevent bypassing the native encryption of BitLocker drives in corporate equipment. This hardware solution acts at a structural level to neutralize data interception between the main components of the motherboard.

Flaws in local storage and bus interception...BitLocker has been widely used to protect sensitive information in organizations. Recently detected vulnerabilities allow an attacker with on-site access to the machine to extract vital documents and credentials. The interception tactic exploits and captures the communication established between the central processor and the trusted platform module. The attack requires only twenty dollars in hardware and takes less than a minute to execute.

The HP TPM Guard defense mechanism...HP TPM Guard creates a fully encrypted connection between the processing unit and the security module. The cryptographic circuit remains irrevocably linked to the equipment to block attempts at external probing. The system renders the computer completely unusable upon any sign of removal or tampering with the chips. The brand has already submitted a formal proposal to the Trusted Computing Group to convert the tool into a global standard.

Dr. Ian Pratt, Vice President and Technical Director of Security at HP Inc., states that the security of the computer base is critical to ensuring the future of work. He emphasizes the urgency of acting, given that an attacker with limited training and an inexpensive kit can bypass current protections.

Practical recommendations for corporate system security...Defending local infrastructure requires a combined physical and logical response to isolate attack vectors [unverified data – requires editorial confirmation].

Enable robust pre-boot codes to prevent the injection of malicious programs at system startup.

Block direct memory access on external peripheral ports to hinder the forced collection of cryptographic keys.

Apply consistent updates to the mainboard's base system to close known access ports.

Use monitoring tools that alert to the mechanical opening of computer chassis.

Corporate printers with resistance to quantum computing

Advancing Endpoint Protection Against Physical Attacks: The Innovation Behind HP TPM Guard...We rely on laptops for nearly every aspect of our working lives, which means they end up storing sensitive information that must be protected – confidential files, email, credentials, and often customer or employee data. When a device goes missing – whether lost or stolen – the real risk isn’t the cost of replacing the hardware, it is the data that may be exposed.

Against this backdrop, attackers have steadily expanded their focus from targeting software alone to interfering with a device’s security by exploiting hardware and firmware. Even a few minutes of physical access can be enough for an attacker to tamper with a device. Without the right defenses, it’s even possible to capture the cryptographic keys and other system secrets that are critical for securing the device and the data it holds, including the keys used to secure full disk encryption solutions like BitLocker in Windows.

These physical attacks don’t require the specialized and expensive equipment that once limited who could attempt them. Affordable tools costing under $20 USD, and widely shared tutorials, have dramatically lowered the barrier to entry, making techniques once associated with advanced research accessible to far more attackers than before.

This growing trend matters because hardware attacks tend to be difficult to detect, stop and recover from, leaving significant gaps and blind spots in an enterprise’s defenses. In particular, physical attacks that succeed in breaking full disk encryption solutions like BitLocker can be catastrophic for a business – from exposing data that triggers financial and regulatory repercussions, to giving an attacker unauthorized access to other systems within an organization.

The rise in physical attacks calls for stronger hardware protection. Today, modern commercial PCs include a certified Trusted Platform Module (TPM) – a discrete hardware security chip that protects cryptographic keys inside a secure boundary. While the TPM provides important hardware protections, it alone cannot stop the advanced physical attack methods that have become cheaper and easier to perform in recent years. This is why HP is introducing HP TPM Guard – a new hardware security capability built into HP commercial PCs that applies a security-by-design approach to protect all software running on the device from this class of physical attacks.

Physical attacks on TPMs that break full disk encryption...Today, most organizations rely on full disk encryption solutions to protect device data, assuming that if a laptop is lost or stolen it remains protected and does not need to be reported to regulators as a potential data loss event.

Many full disk encryption solutions, including BitLocker, use the TPM to protect the disk decryption key. In practice, enterprises almost always configure full disk encryption schemes to automatically release the key if the expected firmware configuration is reported to the TPM during the boot process. This is done for convenience so that the encrypted drive is unlocked without any user interaction. On Windows, this TPM‑only mode is the default BitLocker configuration.

But this convenience has a major weakness. While the TPM validates early‑boot measurements to confirm the expected firmware was used during boot, it releases the disk decryption key to the CPU unencrypted. This key travels to the CPU over a hardware bus – a communication channel on the motherboard that carries data between components – where it is exposed to interception. Some firmware TPM implementations exist in chipsets without exposing an external bus, but none currently provide end users with the assurance that comes from third-party security evaluation under the Trusted Computing Group’s Certification program.

Experts estimate a thirty-four percent probability that current asymmetric cryptography will fail by 2034. The company has expanded quantum-resistant defense to the new LaserJet Pro and Enterprise printers to anticipate this scenario. The enterprise equipment incorporates the ability to autonomously detect, isolate, and recover the system from cyberattacks. The machines feature active threat detection during code execution in system memory.

The evolution of operational risk mitigation...The new high-capacity printing series introduces an automated content hiding function. This tool detects and erases personal or financial data without any human intervention from the IT team. The consolidation of controls in the Wolf Controller system seeks to reduce operational friction and decrease the IT risks of companies. 

In conclusion...Reliance solely on logical storage has proven insufficient to protect high-value local information. The introduction of this physical barrier highlights the urgent need to rethink basic computer security. The exposed flaw in the buses destroys the myth of security based on default encrypted drives. The business sector needs to audit its IT infrastructure and accept architectural upgrades as a vital investment.

mundophone

 

DIGITAL LIFE

Human understanding of AI can't keep up with its advancement, researchers say

In a recent editorial published in Science, Microsoft's chief scientific officer, Eric Horvitz, and researcher Robert West from the School of Computer and Communication Sciences at EPFL in Switzerland issue a stark warning about AI. They say the advancement of AI systems rapidly being woven into our everyday lives is beginning to outpace our understanding of them. At the same time, AI's understanding of human behavior is expanding.

The AI trends defying human understanding...The authors of the editorial point to three main areas where AI is becoming less understandable. The first is the rise of AI-directed AI design, in which AI is increasingly designing and improving other AI systems. The authors say the cycles involved in this process outpace human understanding and occur in "high-dimensional spaces that resist intuition." They say that while the performance of the systems may improve, humans struggle to understand why or how.

The second trend is the interactions between AI agents. Now at scale, these agents are forming multi-agent ecosystems whose internal communication may drift away from human language and reasoning. As newly formed AI interactions and communications become more complex, humans become less capable of interpreting them.

Lastly, adaptive AI agents are quickly learning more about human behavior, creating a one-sided situation in which AI understands us better than we understand it. As they parse untold amounts of data from interactions with humans and data showing how humans interact with each other, AI systems begin to understand us better than we understand ourselves and certainly better than we understand them.

The authors write, "Through sustained interaction, they can build increasingly detailed models of human behavior and psychology, capturing not only preferences but also latent drivers such as fear, uncertainty, and the need for social belonging."

The looming threat of opacity...So what happens when AI systems reach a point beyond human understanding? The authors warn that without strong countermeasures, the resulting opacity could lock in AI systems that are powerful but effectively ungovernable by humans. They say that once this happens, recovering human agency may not be possible. This imbalance of understanding could affect personal autonomy, democratic decision-making and trust in institutions.

As AI's understanding of humans deepens, the authors warn that one outcome is that the output of AI systems may increasingly reflect human expectations instead of reality, essentially telling humans only what they want to hear. Without understanding, we won't know that this is happening. In addition, human curiosity, skepticism and scrutiny of AI may simply wane.

"More subtle is the possibility that we will gradually lose interest in understanding and guiding AI. As AI systems become deeply embedded in human environments, they may respond to preferences but also shape them. Systems optimized for engagement or approval may reduce friction and discourage scrutiny. Over time, curiosity and skepticism may erode, leading to neglect and acceptance," the authors write.

Preserving human agency...Some of these risks may be speculative, but they are based on extrapolating current trends into the future. And with the currently unfettered spread of AI in nearly every aspect of our lives, the ideas here may not be so far-fetched. But according to the authors, there is still hope for keeping AI intelligible.

For example, they say research will need to focus on ensuring AI systems can explain their own design choices and internal workings in human-understandable ways. This may include better ways to detect drift in AI-generated language and reasoning or rewarding human-interpretable communication. They also suggest evaluation frameworks that move from static benchmarks to dynamic, real-world-like testing environments, adapting alongside AI models.

The authors stress that preserving human agency and the ability to question AI decisions are of crucial importance. They write, "It is not enough to monitor how AI systems behave. We must also understand how they shape human goals and judgment, and ensure that people retain the capacity and motivation to question, audit, and guide them. These forms of opacity reinforce one another, narrowing—and threatening to close—the window in which we can build AI that is not only powerful but also understandable. Keeping the window open will require a shift in our objectives. Human understanding must be prioritized alongside capability."

The widening gap between AI's exponential advancement and human comprehension is one of the defining technological dilemmas of our time. As researchers warn, artificial intelligence is increasingly operating as complex "black boxes," leaving humans struggling to understand the mechanics behind its rapid evolution.

Why Comprehension is LaggingThe disconnect between machine capabilities and human understanding is driven by several converging factors:

AI-Directed Design: AI systems are increasingly being used to design, evaluate, and improve other AI systems. These iterative cycles operate in high-dimensional spaces that outpace human logic and intuition.

Multi-Agent Ecosystems: Artificial intelligence agents operating at scale form complex ecosystems where internal communications can drift away from human language and reasoning into patterns we struggle to interpret.

The "Black Box" Problem: Modern models rely on trillions of parameters, meaning even the engineers who build them cannot explicitly detail every pathway the model takes to arrive at an output.

The Imbalance of Understanding...While we struggle to understand how AI operates, AI's ability to model and understand human behavior is growing exponentially. This creates a dangerous one-sided scenario. Researchers from tech companies and academia warn that this looming opacity could result in powerful AI systems that effectively become ungovernable. Because AI assistants are highly optimized to be agreeable and reassure the user, humans may gradually lose the curiosity or skepticism required to critically guide the technology.

Taking Action & Staying Informed...Because the landscape is complex, the technology can feel overwhelming, leading to uninformed opinions or complacency. To keep pace, it is vital to engage with the right resources, develop AI fluency, and focus on the skills machines cannot replicate.

Understand the Macro Trends: Explore the Stanford HAI AI Index for rigorous, annual data evaluating everything from technical performance to global AI governance and policy.

Navigate the Technology Safely: Read about AI Alignment: Ensuring AI Systems Reflect Human Values to learn how researchers are attempting to encode ethical judgment and intentions into machines.

Understand the Human Element: Deepen your knowledge of uniquely human abilities, such as ethical judgment and emotional intelligence, which remain critical and irreplaceable in the AI era.

by Krystal Kasal

DIGITAL LIFE

The consequences of relying on AI for accurate news

It's no secret that the last few years have seen a massive explosion in the use of artificial intelligence for general information-gathering. An even more recent trend, though, is how large language models (LLMs) like ChatGPT, Claude and Gemini are increasingly being used for verifying and consuming news. Reports from the Pew Research Center over the last year found that 1 in 5 U.S. teens regularly use LLMs to get their news, while 1 in 4 young adults have reported using them for that purpose at least once.

A new open-access study from the MIT Media Lab should give some of those users pause: Researchers found that, over the course of a month, participants who relied on AI systems to verify facts actually got worse at detecting misinformation on their own when their chatbots were taken away.

This phenomenon, which is often referred to as the "AI dependency paradox," has been observed in a wide range of knowledge domains, like the 2025 study that found that doctors who used AI got worse at detecting cancer on their own. The dynamic mirrors broader tech trends around so-called "deskilling" (or "cognitive offloading") that have been well-documented for decades, from calculators weakening our math skills to Global Positioning System (GPS) technologies affecting our natural sense of direction.

In the new Media Lab study, which tracked 67 people over four weeks as they evaluated news headline-image pairs, participants were 21% more accurate in detecting fake news when assisted by an AI chatbot during a session—confirming previous research out of the MIT Sloan School of Management demonstrating that AI can be an effective tool in reducing people's belief in false information.

However, the study showed that a new wrinkle emerged when the AI was no longer present: By week four, participants' unassisted performance on new news items declined by 15 percentage points compared with before the study started.

Roughly a quarter of all participants actually reported feeling that they were getting better at detection, even as their performance declined.

Dunning-Kruger creeps in..."Users get excited about these 'magical' LLMs, but forget that they're just statistical models that predict the next 'token' in a sequence [of letters/words]," says MIT media arts and sciences (MAS) Ph.D. student Anku Rani, co-lead author of a new paper about the research, alongside fellow MAS PhD student Valdemar Danry.

"Many impressive behaviors emerge from scaling this, but it comes with real limitations, both in what the model can reliably generate and in its broader impact on the people using it."

Qualitative analysis identified distinct behavioral patterns, with the team labeling one-fifth of all participants as "Dependency Developers" who gradually shifted from active self-reliance to passive acceptance of AI guidance.

In the post-experiment survey, one respondent explicitly acknowledged this transition, noting their passive role in the process.

"While [the chatbots] did emphasize that you must check across multiple sources to make sure a story is true, they didn't teach me much about exploring the context of the images themselves," the participant said.

The research team said that these AI models are particularly vulnerable to mistakes in the midst of emotionally charged breaking news, as exhibited by the widespread misinformation that accompanied President Donald Trump's recent assassination attempt and major events during the Iranian war.

The authors also point out that the original human-created news content used to train the AI models is increasingly unreliable and/or biased, further exacerbating the problem.

The paper, which Danry and Rani presented in Barcelona at the Conference on Human Factors in Computing Systems (CHI 2026), was co-authored by Assistant Professor Paul Pu Liang, senior research scientist Andrew Lippman and senior author Pattie Maes, the Germeshausen Professor of Media Arts and Sciences.

The solution: Being a coach, not a crutch...The researchers say that the results of their project suggest that the specific way in which an AI interacts with a user determines whether its impact will be "as a coach, versus as a crutch." The study found a clear distinction between conversational strategies that simply help in the moment and those that actually support active learning and skill development.

For the latter, the Media Lab team uncovered several strategies associated with stronger independent detection later on, even if the strategies initially slowed down performance during the interaction. This included the Socratic method of the AI asking guided questions, as well as so-called "deep probing," where the system provides gently persuasive statements if the user appears to be veering away from the correct response.

"AIs that 'tell' by providing direct answers are more likely to foster reliance, while those that 'ask' via Socratic questioning are better at engaging someone to actually learn how to discern the truth on their own," says Danry. "But it's very much a trade-off between speed and effort."

Rani noted a few key limitations to the one-month study, from the small dataset of roughly 50 validated news items to the demographic focus on the United States and the United Kingdom. In the future, she says that the team hopes to do similar experiments with more geographically diverse cohorts, including low-resource communities, and is also eager to explore whether other multimodal interaction strategies—like interacting with culturally adaptive digital twins instead of text-based chatbots—help people improve their abilities to detect misinformation.

At a higher level, the researchers hope that the project will be something that educators can examine as they develop teaching plans that incorporate AI tools into their school curricula.

"It's especially important to raise awareness in our schools and academic communities about the shortcomings of using AI as learning tools," says Maes.

"People need to know that if they 'delegate' their thinking, they're not going to get better at that particular brand of problem-solving. Ultimately, the ability to question and analyze information is important for everyone, because it empowers us to solve problems and form our own independent opinions about the world."

Danry adds that the rapidly evolving field of machine learning and deep learning will require continuous education on the benefits and drawbacks of LLMs.

"There's a lot of work to do in making sure that we don't just fully offload critical tasks that we want to be able to keep on doing to these models," he says. "We need to develop a new kind of AI literacy."

Provided by Massachusetts Institute of Technology