Thursday, February 19, 2026

Survey Results from the Library 2.0 2026 "What You Need to Know About AI and Libraries" Event + Session Recording Link

SESSION RECORDING:

Click HERE to watch the recorded session. You need to be a member (free) of Library 2.0 to access the recording.


SURVEY RESULTS:

We received 1395 submissions (registrations for the event + survey responses). Here are the results.

Forms response chart. Question title: Type of Library. Number of responses: 1,359 responses.

Forms response chart. Question title: Your Primary Role. Number of responses: 1,358 responses.

Forms response chart. Question title: On a scale of 1 - 10 (1 lowest, 10 highest), are you concerned, worried, or fearful of the impact of AI on your job or career?. Number of responses: 1,314 responses.

Forms response chart. Question title: On a scale of 1 - 10 (1 lowest, 10 highest), are you excited or enthusiastic to learn more about AI and how you can use it personally and professionally?. Number of responses: 1,309 responses.

Forms response chart. Question title: Which best describes how you feel about AI right now?. Number of responses: 1,316 responses.

What are your biggest concerns about AI (personal and/or work-related)?  (Summary)

  • Impact on Critical Thinking and Skills: A major concern is the decline of critical thinking, research, and writing skills, particularly among students, due to over-reliance on AI for assignments and tasks, leading to "dumbing down" of the future workforce and electorate.

  • Misinformation and Accuracy: Frequent mentions of AI "hallucinations," "fake news," and the spread of misinformation/disinformation, including deepfakes, raise concerns about the validity, accuracy, and trustworthiness of AI-generated content, making it difficult to discern truth from falsehood.

  • Job Displacement and Workforce Impact: Many respondents are concerned about job loss, mass unemployment, and the potential for AI to replace workers, especially as management may overestimate AI's current capabilities.

  • Ethical, Privacy, and Security Issues: Significant concerns revolve around data privacy and security, copyright infringement (especially the theft of intellectual property from artists/creators), and the ethical use and bias embedded in AI models.

  • Environmental Impact: The negative environmental consequences of AI, including the significant energy and water consumption by data centers, are a frequently mentioned concern.

  • Speed of Development and Lack of Regulation: The rapid development of AI technology is concerning because it is outpacing regulation, oversight, and people's ability to keep up with the changes and understand the implications.

What is most exciting to you about AI (personal and/or work-related)?  (Summary)

  • Efficiency and Time Savings: A large number of respondents are excited about AI's potential to save time, increase efficiency and productivity, and automate or streamline mundane, routine, or tedious tasks, both personally and professionally. This includes help with administrative work, coding, organizing, data analysis, and creating documents/presentations.

  • Idea Generation and Creativity: Many respondents view AI as a useful tool for brainstorming, generating ideas, creating content (like writing drafts, emails, social media posts, images), and enhancing creativity.

  • Advancements in Science and Medicine: A significant number of responses highlight the exciting implications of AI for medical diagnostics, scientific discoveries, solving big global problems (e.g., climate change, disease), and processing large datasets in fields like astrophysics.

  • Information and Learning Support: Respondents are interested in AI's ability to quickly synthesize, summarize, and retrieve information, assist with research and literature searches, and provide support for learning, including for students and those with special needs.

  • Potential and Possibilities: A recurring theme is the sheer potential and vast possibilities of AI technology, with a desire to learn more about its applications and to use it as a powerful new tool in various aspects of life and work.

Forms response chart. Question title: How is AI currently showing up in your library or organization?. Number of responses: 1,263 responses.

Forms response chart. Question title: How would you describe your current level of AI use at work?. Number of responses: 1,268 responses.

Forms response chart. Question title: What would be most helpful for you and/or your library in the next 6–12 months?. Number of responses: 1,252 responses.

Comments on any of the topics or things that we might have missed that you would like us to be focused on? (Summary)

  • Ethical Concerns and Negative Impacts: A significant number of responses highlighted concerns about the ethics of AI, including environmental impact, intellectual property theft, privacy, potential for scams and general abuses, surveillance, and the broader negative societal effects. Many also mentioned the need for clear ethical guidance, policies (especially for academic libraries), and actively advocating against these harms.

  • Practical Application and Use Cases in Libraries: Respondents frequently asked for specific, practical examples of how AI can be used effectively in various library settings, including cataloging, technical services, research, reporting, and general library operations. There was also interest in building custom LLMs for libraries.

  • Information Literacy and Training: A major theme was the need to educate users (students, patrons, older adults, and even staff) on AI literacy, including how to use it ethically, how to apply critical thinking when evaluating AI results, recognizing AI-generated content (like books/covers), and training users to retain a healthy level of skepticism regarding issues like hallucinations and misinformation.

  • Policy and Institutional Guidance: There is a request for guidance on establishing clear institutional policies regarding AI use, especially in academic libraries where faculty opinions vary and students are starting to use it.

  • Basic Understanding and Fear Mitigation: Several respondents expressed a need for basic, simply stated information about AI, acknowledging they are new to the topic, want to overcome fear, and understand "how real the hype is."

Monday, February 16, 2026

The Four-Hour School Day (And Why We'll Never Do It)

Here's a thought experiment. If you could design a school day from scratch, based on everything we know about how humans actually learn, about cognitive science, about motivation, about child development, how long would it be?

It almost certainly wouldn't be seven hours. It probably wouldn't be six. If you were honest about it, and if you could free yourself from the gravitational pull of how things have always been done, you'd land somewhere around four hours. Maybe less.

And here's what's interesting: we have proof that it works. We have research showing it works. We have an entire country demonstrating, year after year, that it works.

We're never going to do it.

The evidence isn't the obstacle. What's standing in the way is what we'd have to admit if we did.

What Finland Keeps Trying to Tell Us

Finnish students attend school for fewer hours than almost any of their international peers. They start formal education later, at age seven. They receive minimal homework, especially in the younger grades. Their school days are shorter, punctuated by long breaks, and filled with far less testing than what American students endure.

And yet Finnish students consistently perform among the best in the world.

This fact alone should have revolutionized education policy decades ago. It didn't. We noted it, admired it from a distance, wrote articles about it, sent delegations to observe Finnish schools, and then went back to doing exactly what we were doing before.

But the important thing about Finland isn't just the shorter hours. It's what those shorter hours contain, and more importantly, what trust the system is based on. Finnish education trusts students with unstructured time. It emphasizes depth over coverage. It treats teachers as professionals rather than compliance officers executing a script. The Finnish system operates on an assumption that runs counter to almost everything in American education: that children are naturally inclined to learn, and that the job of the school is to support that inclination rather than override it with control.

The question Finland raises isn't really about scheduling. It's this: if a country can produce world-class learning outcomes in significantly fewer hours, what exactly are we doing with the rest of ours?

Deep Work, Shallow School

Cal Newport has spent years studying how people actually develop mastery and produce meaningful cognitive work. His conclusion, refined across multiple books, is that real skill development happens through sustained, focused engagement with material that matters to the individual. He calls this "deep work:" the kind of concentration that produces insight, builds expertise, and creates lasting understanding.

The opposite of deep work is shallow work: logistical, reactive, low-cognitive-demand activity that fills time without producing proportional growth. Newport argues that most modern knowledge workers spend the majority of their days on shallow work while believing they're being productive.

Apply this framework to a typical school day, and the picture is uncomfortable. How much of a seven-hour school day consists of deep work? How much is transitions between classrooms, administrative tasks, waiting, reviewing material already understood, or performing rote exercises that require compliance but not thought? If we're honest, most of the school day is shallow work dressed up as rigor. Students aren't engaged in deep cognitive work for seven hours. They're not engaged in deep cognitive work for five hours. On a good day, with a great teacher, they might get two or three hours of real intellectual engagement. And that's generous.

The implication is hard to avoid: four hours of engaged, interest-driven learning almost certainly produces more cognitive development than seven hours of compliance-driven seat time. The additional hours aren't adding to learning. They're adding exposure to the system.

And then we send them home with homework.

The Homework Myth: Busyness as a Proxy for Learning

Homework is one of the most sacred assumptions in American education, and also one of the most poorly supported by evidence. The research on homework tells a story that almost no one wants to hear: for elementary and middle school students, homework has essentially no measurable impact on academic achievement. For high school students, the effects are modest and diminish rapidly beyond a certain point.

We keep assigning it anyway.

Why? Because homework feels productive. Because parents expect to see it. Because a child sitting at the kitchen table with a worksheet feels, to the anxious adult, like evidence that learning is occurring. And because an idle child, a child reading a book of their own choosing, building something in the garage, daydreaming, or simply doing nothing, is culturally suspect.

We have conflated "busy with schoolwork" with "learning." They are not the same thing. In fact, they may be inversely related. The students who develop the deepest intellectual capacities, the ones who become truly creative thinkers, who develop real expertise, who maintain their curiosity into adulthood, are often the ones who had unstructured time to follow their own interests. Time that no one supervised. Time that no one assessed.

Homework isn't evidence of learning. It's evidence of the system's reach into the home. It extends the school day into the evening hours, ensuring that the student's waking life is colonized by institutional demands. And it communicates something to the child and to the family that we rarely examine: that the student's own interests, questions, and pursuits are less important than whatever the system has assigned. That learning which doesn't originate from school isn't real learning.

The four-hour school day would end this. It would give students back their evenings and their afternoons. And that, it turns out, is exactly what makes it threatening.

The Game of School

A few years ago, I gave a talk on education at a conference held at Google's headquarters. I expressed my concern about the small number of students who graduated high school seeing themselves as "good learners," and about the much larger number whose school experience left them believing they were not good learners, and even more troublingly, that they were not smart.

This concern had developed over several years during which I kept meeting adults who, when asked about their school experiences, would actually start to cry. The emotional wounds they carried from school were lifelong and deep, and surprisingly common.

After my talk at Google, some student interns came up to me. One said something that permanently changed how I understood education: "We're interns at Google. We agree with what you've said, but we've been talking. We're in that group you identified as the top 10 percent. But we didn't see ourselves as good learners. We were good at the game."

The game. The game of school.

I began asking top-ranked high school students: is school a game? Try it yourself. They almost always reflexively smile and then immediately give examples of how it's a game and how they play it. This teacher likes homework done this way. This other teacher, you only have to worry about the tests. If you take a course at the community college, it's actually easier and you get a weighted grade on your transcript. Just like in any institutionalized work environment, learning how the game is played, what the rules are, how to succeed within them, is the key to doing well.

And this is the point: schools are about learning, but it's mostly learning how to play the game. At some level, even though we like to talk about schools as though they exist for learning in some pure, liberal-arts sense, on a pragmatic level we know that what we're really teaching students is to get done the things they are asked to do, to get them done on time, and to get them done with as few mistakes as possible. If we ask ourselves honestly how much we remember of the academic content from high school, most of us would answer: almost nothing. The material was just context for preparing students for the "real world" by teaching the traits needed to be good workers.

The students who aren't succeeding usually don't know school is a game. Since we tell them it's about learning, when they fail they internalize the belief that they themselves are actual failures, that they are not good learners, not smart. And we tell ourselves things to feel okay about this: that some kids are smart and some aren't, that the best students will always rise to the top, that the struggling students' behavior is their own fault. For someone to accept lowered expectations for themselves, they have to believe they are not worthy of more, and we have to believe it too. (Plato's Noble Lie isn't just for the students; it's for the teachers and parents, too, convincing us all that our students and we are not capable enough to direct ourselves, and that we should just go along.)

This is the sorting mechanism. School identifies some students for leadership and confidence, and it produces in others a belief that they are "less than," a belief that will follow them into adulthood, into the workforce, into their sense of what they deserve from life. In a society that depends on a large population of compliant workers and consumers, this isn't a malfunction. It's the product.

The Four Levels of Learning

To think clearly about what a four-hour school day would actually change, it helps to distinguish between four words we use almost interchangeably but that mean very different things: schooling, training, education, and learning.

Schooling is the entry level. While there is learning at schools, it's less about subject matter and more about learning the skills needed to be a good worker: conformance, obedience, getting work done, doing what, when, and how you are told. Schools are a system of rules, schedules, bells, attendance ratings, and constant testing. We casually refer to this as "education," but it isn't. Rather than finding the unique value, capacity, or capability of each individual (which is the story we like to tell), schooling allows a stratification to take place so that some can lead and others will follow.

Training is the next level: specific career or vocational preparation. It's largely memorization and certification. It's valuable because it's career-specific and often allows individuals to move between social and financial classes. But it's still externally directed.

Education — from the Latin (sort of), "to lead or draw out from within" — is what we commonly intend when we talk in lofty ways about freeing the individual mind. It's what a "liberal arts" (also from Latin: liber = free) education is supposed to provide. It's what someone means when they say a particular teacher changed their life. In my own definition, education is always the result of a one-to-one relationship, where a mentor helps a learner think at a higher level and see something differently than they have before.

Self-directed learning is the ultimate goal of a healthy educational system. It's when someone has learned how to learn and is able to manage their own learning goals and processes. It's what we mean when we talk about becoming a "lifelong learner." It's the same way a parent wants to help their child grow into an independent, self-directed, capable person.

Now look at how the school day maps onto these levels. A seven-hour school day, followed by homework in the evening, is almost entirely consumed by Level 1: schooling. There is barely room to breathe, let alone for the kind of mentorship that constitutes real education (Level 3) or the autonomous pursuit that develops self-directed learning (Level 4).

A four-hour school day changes this equation completely. It doesn't just shorten the day. It creates space, actual unscheduled and unassessed space, for the levels of learning that we claim to value but systematically crowd out.

The System Serves the System

The uncomfortable truth at the center of all of this is pretty simple.

The seven-hour school day wasn't designed around research on optimal learning. It was designed around industrial labor schedules. It was designed to match the workday of parents. It was designed to serve the needs of the institution itself: staffing, scheduling, credentialing, political control over what children think and when they think it.

The rewards students receive — grades, transcripts, diplomas, honor rolls — are system rewards, not learning rewards. They measure participation in the game, not the development of the mind. A student who reads voraciously, builds things independently, asks hard questions, and pursues deep interests but doesn't comply with the system's requirements gets punished. A student who learns almost nothing but checks every box gets celebrated, admitted, credentialed, and advanced.

We don't measure learning. We measure compliance.

And this isn't a bug; it's a feature. Mandatory public schooling, as it developed in the late 19th and early 20th centuries, was explicitly designed as a governance strategy. The goal was to reduce the role of the family and increase loyalty to the state. The system produces students who do what is asked of them, when it is asked, how it is asked. Those students then become workers who do the same. The pipeline from classroom to workplace isn't incidental. It's the point. The obedience learned in school is the obedience required by employers. The tolerance for meaningless tasks developed over twelve years of schoolwork becomes the tolerance for meaningless tasks that keeps offices functioning. The belief that external validation (the grade, the performance review) is more real than internal understanding is the belief that keeps the entire structure intact.

Reform efforts that accept the advertised narrative, that school is primarily about learning and we just need to do it better, will always be futile. They're trying to fix something that isn't broken, at least not from the system's perspective. The system is doing exactly what it was designed to do. Talking about it in loftier terms doesn't change what it produces.

What It Could Look Like (And Why We'd Ruin It)

So what would a four-hour school day actually look like? Not a truncated version of the current model. Not cramming the same content into less time and calling it innovation. Something actually different.

Mornings would be devoted to core instruction: literacy, numeracy, collaborative projects, the kind of focused intellectual engagement that benefits from structure and guidance. Four hours is more than enough for this. Finland proves it. The cognitive science proves it. Anyone who has honestly observed a classroom knows that the productive portion of a seven-hour day doesn't exceed four hours anyway. We've just padded the rest with transitions, busywork, and managerial overhead.

Afternoons would be freed for interest-driven pursuits: mentorships, community involvement, creative work, physical activity, reading, building, exploring. The school becomes a launchpad rather than a container. These afternoon hours are where Levels 3 and 4, real education and self-directed learning, finally have room to happen. These are the hours where a student discovers what they actually care about, develops the capacity to direct their own learning, and begins to build the kind of deep engagement that Cal Newport describes as the foundation of all meaningful work.

But here's what I know would happen, and I want to be honest about this: the system would immediately attempt to systematize the free afternoons.

Immediately, there would be committees designing "structured enrichment programs" for the afternoon hours. There would be assessments attached to the mentorships. There would be rubrics for the creative work. There would be attendance requirements for the community involvement. The afternoon would be colonized by the same institutional logic that already owns the morning, because the system cannot tolerate unstructured time. It doesn't know what to do with freedom. It can only see freedom as a problem to be managed.

And this reveals something far deeper than a policy disagreement about school schedules.

The Babysitting Function

Before we get to the deeper psychology, there's the most practical reason the four-hour school day will never happen: most parents need their kids somewhere safe while they're at work.

This is not a trivial concern. It's arguably the primary function of the modern school day, and it's the one we almost never name. We talk about curriculum, standards, achievement gaps, college readiness, but underneath all of that, the seven-hour school day exists because it roughly matches the adult workday. School is, among other things, the largest childcare system ever created. Calling it that feels reductive, maybe even disrespectful to the teachers doing real work inside it. But it's true. And any proposal to shorten the school day runs headlong into the fact that millions of parents have no alternative arrangement for their children between noon and five o'clock.

This is a real constraint. I don't want to minimize it. Single parents, dual-income families, families without nearby extended family: the practical logistics of a four-hour school day would be hard to work through without rethinking how we structure work, community, and support systems. The four-hour school day isn't just an education proposal; it implies a different kind of society. That's part of why it's so threatening.

But the babysitting function also reveals something important. It reveals that much of the resistance to shortening the school day isn't really about learning at all. It's about containment. Where will the children be? Who will watch them? The anxiety isn't about what students will learn in those freed-up hours. It's about the simple fact that they'd be unsupervised.

And that leads us somewhere deeper.

What We Really Believe About Children

Most parents, if they're honest, wouldn't just be worried about logistics. They'd be worried about what their kids would do with that much free time. Not in an abstract, philosophical way, but in a gut-level, I-don't-trust-this way.

We say we want students to be creative, independent, curious, self-directed. We say we want lifelong learners. We put these words in mission statements and hang them on school walls. But when someone proposes giving students significant unstructured time, time that is truly theirs, not assessed, not monitored, not channeled through institutional objectives, the reaction is immediate: They'll waste it. They'll become lazy. They'll get into trouble. They'll fall behind.

Behind every objection to the four-hour school day is an assumption about human nature: that without external control, young people will default to idleness and self-destruction. That they cannot be trusted with their own time. That left to their own devices, they will choose poorly, learn nothing, and become truants. (I personally think this is why Lord of the Flies is such a huge part of Western Culture--without enforced structure, it argues, we revert to savages.) 

This is a remarkable thing to believe about a species that managed to learn everything it needed to know, from toolmaking to language to agriculture to social organization, for hundreds of thousands of years before anyone invented a classroom.

The Childhood We Lost

I can remember growing up and being able to get on my bicycle and just go. My parents had no idea where I was. I didn't have a cell phone. There was no GPS tracking, no check-in texts, no shared location apps. I was just out. Riding around the neighborhood. Hanging out with friends. Exploring. It wasn't like I was up to no good. I was doing what kids do, or at least what kids used to do: navigating the world on my own terms, solving small problems, negotiating social dynamics, building the kind of practical competence that no curriculum can teach.

That sure feels like a different time.

And it was. The world wasn't safer back then; by most measures, it was actually more dangerous. Crime rates were higher. Seatbelt laws were lax. Playground equipment could actually hurt you. But the cultural expectation was different. Children were expected to have unsupervised time. It was considered normal, healthy, even necessary. A kid who spent every afternoon indoors, under adult supervision, with every hour accounted for, would have been the odd one out.

Something shifted. Over the course of a generation or two, we moved from a culture where childhood freedom was the default to one where childhood supervision is the default. The reasons are complex. Some of it is media-driven fear, some of it is liability culture, some of it is the real pressures of modern parenting. But the result is that we've produced a generation of young people who have almost never experienced unstructured, unsupervised time. Their days are scheduled from morning to night: school, homework, activities, screens. Every hour is accounted for. Every space is monitored.

And then we wonder why they seem to lack initiative. Why they struggle with independence. Why they need to be told what to do.

We built this. The system built this. And a four-hour school day would expose it, because it would hand students hours that no one had planned for them, and we honestly don't know what would happen. We've never let them find out.

The belief that children can't handle freedom doesn't hold up to observation. Watch a child who hasn't yet been broken by the system: they are relentlessly curious. They explore, they experiment, they ask why over and over again, they take things apart, they create. Curiosity is the default state of a healthy young human. It doesn't need to be installed by an institution. It needs to not be extinguished by one.

The fear that children can't handle freedom says far more about us than it does about them. It reveals that we don't actually trust the learning process unless it's controlled. We don't trust development unless it's measured. We don't trust growth unless someone with credentials is supervising it. We need to see the worksheet, the test score, the grade — not because these things produce learning, but because they produce the feeling that learning is under control.

And this leads somewhere even more uncomfortable.

The Cave We Built for Ourselves

If we're honest, really honest, the reason we can't give children unstructured time is that we don't trust that we would use free time well.

Most adults don't know what they would do with a truly free afternoon other than shopping or watching television. The system has trained that capacity out of us. Twelve years of schooling followed by decades of managed work have produced exactly what they were designed to produce: people who are uncomfortable with autonomy, seeking escapes and telling ourselves that passive entertainment is a valuable activity. 

Our evolved psychology plays a role here too. For most of human history, belonging to the group was a matter of survival. Going along with the tribe, deferring to its norms, fitting in: these weren't signs of weakness. They were survival strategies, wired deep into our brains over hundreds of thousands of years. The desire to conform, to stay inside the boundaries of what the group expects, is one of our most powerful instincts.

Plato described this two and a half thousand years ago in his allegory of the cave: prisoners chained in darkness, watching shadows on a wall, believing the shadows are reality. When one prisoner is freed and sees the sunlight, he's blinded and terrified. And when he returns to tell the others, they don't thank him. They think he's mad. They prefer the cave.

We prefer the cave too. The wiring runs that deep. The familiar feels safe. The institution, for all its failures, provides structure, belonging, and identity. Walking away from it, really walking away and not just reforming around the edges, requires confronting the terrifying possibility that we are capable of more than the system has told us we are. That our children are capable of more. That the limits we've accepted weren't natural limits at all, but the walls of a very old, very effective game.

We project this onto our children. We can't imagine them handling freedom because we can barely imagine handling it ourselves. The four-hour school day doesn't just threaten the institution. It threatens the story we've told ourselves about what humans are: that we need to be managed, directed, assessed, and kept busy in order to become anything worthwhile.

That story is wrong. But it's the story the system depends on. And the system has had a very long time to convince us it's true.

Why We'll Never Do It

The case for the four-hour school day isn't complicated. Finland showed us it works. The cognitive science supports it. The research on homework confirms that the extra hours add almost nothing. Cal Newport's framework explains why depth beats duration. The Game of School reveals that most of those seven hours aren't producing learning anyway; they're producing compliance. The Four Levels of Learning show that we've crowded out everything above Level 1.

The evidence isn't the problem. The problem is what we'd have to admit.

We'd have to admit that the school day was never designed around learning. We'd have to admit that homework is mostly institutional theater. We'd have to admit that the system sorts children (and adults) into winners and losers and then tells the losers it's their fault. We'd have to admit that one of the school day's primary functions is containment — keeping children somewhere safe and supervised while adults work — and that this function has become so essential to how we've organized society that we can't change it without changing everything else too. We'd have to admit that we've built an elaborate, expensive, deeply entrenched structure that serves its own perpetuation more than it serves the children inside it.

And we'd have to admit that there is a deeper fear: that without the structure, without the control, without the constant institutional supervision, our children and we might become independent, and we're honestly not sure that's a positive thing. Heaven forbid there might be actual independent thinking, and we don't need the system as much as we've told ourselves we do.

The four-hour school day would work. We know it would work. The reason we'll never do it has nothing to do with learning, and everything to do with what the other three hours are really for. They're not for the students. They never were. They're for us. For the system. For the game. 

And the game, as it turns out, is the one thing we're really not willing to change. It's our cultural form of Stockholm Syndrome — we've developed loyalty to a system that imprisons our children and us.

Saturday, February 14, 2026

AI Scams: Why the Old Rules Don't Work Anymore (And What Does)

Years ago, when I was in college, I was at my dad's house when a piece of mail arrived announcing he'd won the lottery. I read it carefully. I was convinced. I actually called him at work and told him to come home because he'd won. I'm glad this memory isn't a painful one. I don't think he was mad, just amused that a college kid could fall for something so transparent.

But the scams we're facing today aren't transparent at all. They're not the ones we were trained to recognize (the bad grammar, the foreign princes, the stranded traveler, and assorted sketchy emails). This is a new generation of fraud, powered by artificial intelligence, that does something that was impossible even a couple of years ago: it can personally impersonate people you know and love.

And that changes everything.

The Call That Changed the Conversation

In January 2023, Jennifer DiStefano was sitting in her car outside a dance studio in Scottsdale, Arizona. Her 15-year-old daughter Brianna was on a ski trip with her dad. When an unknown number rang, Jennifer picked up--something she might not normally do, but with her daughter traveling, she answered.

She heard her daughter's voice: "Mom, I messed up."

The voice was panicked. Jennifer knew it was her daughter. Then a man came on the line, speaking roughly, and demanded a million dollars or he would drug and rape her child.

The panic Jennifer felt in that moment is something any parent can imagine. Fortunately, through a chain of quick thinking by others around her, someone managed to call the ski resort and reach Brianna, who was perfectly safe and confused about what was happening. But that scenario--the terror of hearing your child's cloned voice begging for help--is exactly the kind of attack that's now industrially scalable.

Jennifer testified before the Senate. Her story made national news. And it resonated so deeply because we all know: if that had been us, we're not sure we could have thought clearly enough to verify before acting.

When Even Video Can't Be Trusted

Jennifer's story involves voice cloning, but it doesn't stop there. In 2024, a finance employee at Arup (the global engineering firm behind the Sydney Opera House) received a message that appeared to be from the company's CFO in London. The message described a confidential deal requiring urgent fund transfers.

The employee was initially suspicious. It looked like phishing. But then he was pulled into a video call where he saw the CFO and several other executives on screen, looking normal, chatting naturally, discussing the deal. So he complied, wiring fifteen separate payments totaling $25 million to five bank accounts in Hong Kong.

It was only after the transfers that he checked with head office and discovered that none of those people had actually been on the call. Every face on that screen was a deepfake.

Arup's public statement afterward was telling: "Our systems weren't hacked. Human trust was hacked."

That's the core of what we need to understand.

This Isn't About Being Careless

The numbers are staggering. Reported losses from these scams reached $16.6 billion in 2024, with estimates projecting $40 billion annually by 2027. It's believed that one in four people has either been scammed, experienced an attempted scam, or knows someone who has. One in four spam calls now uses an AI-generated voice rather than a human one. And grandparent scams, where someone impersonates a grandchild in distress, are among the fastest-growing categories.

But here's what matters most: this isn't about victims being careless or uninformed. This is about technology that exploits how our brains are wired.

Our brains evolved over hundreds of thousands of years for small tribal living, where trusting familiar voices and faces was essential for survival. We're fundamentally wired to believe what we hear from people we recognize. That's not a bug, it's a feature. Trust within a group kept our ancestors alive.

The problem is that these evolved features weren't designed for an era when a three-second audio clip can be used to clone your voice, or when real-time deepfake video can put a convincing replica of your boss on a Zoom call.

When the emotional, fear-driven part of the brain gets hijacked, it floods the body with stress hormones and the rational mind shuts down. This is by design. It's what enabled our ancestors to react instantly to threats. But scammers know this. They deliberately create panic to prevent you from thinking clearly. They exploit our authority bias (we defer to bosses and officials), our protective instincts (especially toward children and grandchildren), and our social conditioning to comply with urgent requests.

These are features of human psychology that worked beautifully for hundreds of thousands of years. They just weren't designed for this level of impersonation.

From Detection to Verification

Here's the shift in thinking that underlies everything: we have to move from detection to verification.

The old approach was about spotting fakes--about looking for bad grammar, generic greetings, suspicious signs. The new reality is that those tells are gone. The greeting will use your name. The voice will sound exactly like your child. The email will match your boss's communication style across multiple exchanges.

So instead of trying to spot what's fake, we need to confirm what's real through channels that scammers can't control. And because these scams work by hijacking our ability to think clearly, our defenses can't rely on making good decisions under pressure. We need them to be automatic.

Four Protocols That Actually Work

These defenses aren't technology-based. You won't need to run video through an AI detection program. These are simple, human protocols based on understanding how your brain works and what to do when it's been compromised.

The Safe Word Protocol. This is the single most important defense. Establish a secret verification phrase known only to your immediate family. This can be from a shared memory, an inside joke, a random funny phrase you'll all remember. "Dancing pink elephant." Whatever it is, it should never appear on social media, never get recorded anywhere, and be impossible for an outsider to guess. If someone calls claiming to be your child or grandchild, ask for the safe word. If they can't provide it, you know it's not them. 

The Callback Protocol. When you receive a suspicious call, hang up and call back on a verified number, like your daughter's cell phone, your husband's number, or your boss's direct line. This is hard because scammers create enormous time pressure, but it's devastatingly effective. They can only control the channel they've initiated. They can't intercept your outbound call to a known number.

"Out-of-Band" Verification. Any request involving money gets confirmed through a separate, independent channel. If your boss emails asking you to wire funds, don't reply to the email, but call him or her directly. If a grandchild calls saying they need money, hang up and call their parents. This is what the financial community calls the "four eyes principle:" multiple independent checks on any transaction. No single person should authorize a large payment based solely on one communication. You seen this when you go to the bank, for good reason.

The Two-Minute Rule. Any urgent request involving money or sensitive information gets two minutes of pause before you comply. This sounds almost impossibly short, but it's enough. Two minutes of deliberate breathing and thinking allows the prefrontal cortex to come back online, and you start asking the questions that unravel the scam. If something can't wait two minutes, that itself is a massive red flag.

Teaching Others Without Creating Shame

If you're an educator, librarian, or someone who works with the public, there's a critical dimension to how you share this information: shame is the enemy of protection.

Most adults, especially older adults, have absorbed a narrative that scam victims are foolish or careless. This shame prevents people from learning, from reporting, and from seeking help. Estimates suggest only one in ten scams is actually reported.

When you teach this material, lead with the neuroscience. Explain that these scams exploit evolved brain mechanisms that no one can simply override through willpower. Tell Jennifer DiStefano's story. Help people understand that falling victim doesn't mean being stupid; it means being human.

For seniors, this is especially important. The grandparent-grandchild relationship is uniquely vulnerable because there's often less daily communication combined with an enormous emotional desire to help. Make sure older adults in your life have established safe words with their children and grandchildren, understand the callback protocol, and have these four steps written down somewhere accessible.

The appropriate emotional response to being scammed is anger at the criminals, not shame at being targeted.

When the Worst Happens

Despite our best efforts, some people will still fall victim. If it happens, the first two hours are the golden window.

Act immediately: contact financial institutions to freeze funds, change passwords starting with email, and document everything while details are fresh. File reports with the FBI's Internet Crime Complaint Center (ic3.gov) and the FTC (reportfraud.ftc.gov). For significant amounts, file a local police report as well.

Be honest about recovery expectations. Wire transfer recovery rates are approximately 8 to 12 percent. For cryptocurrency, it's closer to two percent. These numbers are painful, but people need realistic expectations so they can focus energy on emotional healing rather than holding out false hope.

And if someone comes to you after being victimized--a patron, a student, a family member--lead with compassion. This wasn't their fault. Emotional recovery and financial recovery are separate processes, and both matter.

Your 30-Minute Protection Protocol

Everything covered here comes down to a simple commitment you can make today.

The old rules were about detection. The new rules are about verification. AI can clone voices and faces, but it can't access your safe word. Urgency is always a weapon; verification is always the defense. And the protocols that protect you are the ones that work even when you can't think clearly.

Before you go to bed tonight, establish a safe word with your family. One phone call or one group text is all it takes to start. Then share what you've learned. Every person you reach is one more person protected from what has become the fastest-growing form of fraud in history.

The rules have changed. Now you have the new ones.

Tuesday, February 10, 2026

WHAT YOU NEED TO KNOW ABOUT AI: The Library 2.0 2026 "AI and Libraries" Overview on February 17th (and recording information)

What You Need to Know About AI
The Library 2.0 2026 "AI and Libraries" Overview: Where We Are Now

A 1-hour Free Webinar with Crystal Trice

OVERVIEW:

Artificial intelligence is changing faster than most of us can keep up with. If you work in libraries, you've probably wondered what's real and what's hype, or what any of this means for the work you care about.

This free one-hour webinar offers a calm, non-technical look at where AI stands right now, including emerging trends in how it’s being used, how work is beginning to shift, and the real questions showing up in libraries.

We'll also bring your colleagues' voices into the conversation. When you register, you'll have a chance to respond to a short survey, and we'll share what people are curious about, concerned about, and hoping to understand better.

In this free webinar, you will:

  • Understand how AI has moved from experimental to practical, in plain language
  • See current trends in how libraries and other organizations are using AI
  • Hear what your peers are thinking, based on anonymous survey responses
  • Identify practical questions worth discussing with your team or organization
  • Leave with a clearer sense of what to pay attention to next, without overwhelm

This session is open to library staff, leaders, trustees, partners, and anyone curious about how AI is shaping library work and services. No technical background needed.

This is a live, online 1-hour event. Attendance is not required. The recording and the slide deck will be released immediately to registrants for unlimited post-event viewing.

DATE:

  • Tuesday, February 17th, 2026, from 12:00 - 1:00 PM US - Eastern Time

COST:

  • Free

TO REGISTER:

  • Click HERE to register and fill out an optional short survey (we hope you will!). You will receive an email within a day with information on how to attend the webinar live and how you can access the permanent webinar recording.

NOTE: Please check your spam folder if you don't receive your confirmation email within a day.

Crystal Trice

CRYSTAL TRICE

With over two decades of experience in libraries and education, Crystal Trice is passionate about helping people work together more effectively in transformative, but practical ways. As founder of Scissors & Glue, LLC, Crystal partners with libraries and schools to bring positive changes through interactive training and hands-on workshops. She is a Certified Scrum Master and has completed a Masters Degree in Library & Information Science, and a Bachelor’s Degree in Elementary Education and Psychology. She is a frequent national presenter on topics ranging from project management to conflict resolution to artificial intelligence. She currently resides near Portland, Oregon, with her extraordinary husband, fuzzy cows, goofy geese, and noisy chickens. Crystal enjoys fine-tip Sharpies, multi-colored Flair pens, blue painters tape, and as many sticky notes as she can get her hands on.

OTHER UPCOMING EVENTS:

February 12, 2026

February 12 Event

February 13, 2026

February 13 Event

February 19, 2026

February 19 Event

February 20, 2026

February 20 Event

February 26, 2026

February 26 Event

February 27, 2026

February 27 Event

Starts March 4, 2026

March 4 Event

Friday, February 06, 2026

New Webinar: "Patron Service Challenges: Using Roleplay Scenarios to Build Better Responses"

Patron Service Challenges:
Using Roleplay Scenarios to Build Better Responses

Part of the Library 2.0 Service, Safety, and Security Series with Dr. Steve Albrecht

OVERVIEW

Dealing with challenging patrons in the library workspace often varies along two points: the nature of the encounter with the patron, and the communication and de-escalation skills of the library staff member handling the situation. Experience matters, and so does having several tools in our tool kit. Saying “Calm down!” to someone who is not calm never works and failing to set behavioral boundaries with certain patrons just leads to more problems then and upon their next return to the library.

A useful way to build confidence with staff and give them what they need to think fast and on their feet is by using roleplay scenarios, done in small groups, often as part of a staff meeting exercise. This webinar provides 25 different roleplay scenarios (also included as a PDF handout with the slides) developed by librarians from real-time situations, in libraries across the country, and curated by Dr. Steve Albrecht, as part of his training workshops.

In this program, Steve will discuss each patron behavior scenario and give some tips on how to manage it. Back at the library, staff members can each play the part of either the patron or the employee, act out the issues at hand, use the best communication, de-escalation, and compliance tools, and then get feedback from their peers.

This scenario collection can be customized and finetuned to match the work culture and the community of patrons the library serves. Plus, they can be used during staff meetings throughout the year, as reminders and for new employees. Working in small groups minimizes the impact of peer pressure and makes it easier for employees to feel more confident once they face the real issues on the library floor.

LEARNING AGENDA

  • Discuss the roleplay process in the staff meeting environment and how to keep staff in their comfort zones as either extroverts or introverts.
  • Review 25 different patron behavior situations, develop potential answers, and create workable realistic solutions.
  • Discuss the challenges faced when patrons argue, disagree with rules, policies, and the Code of Conduct, and develop methods to get to a “Negotiated Behavioral Agreement.”
  • The 25 scenarios include patrons angry about how they were treated; teenage patrons; inappropriate Internet use; bullying patrons; children left alone; patrons with mental health issues; covert panhandling; staring, vaping, and sleeping.

DATE: Thursday, February 26, 2026, 2:00 - 3:00 pm US - Eastern Time

COST:

  • $99/person - includes live attendance and any-time access to the recording and the presentation slides and receiving a participation certificate.
  • To arrange group discounts (see below), to submit a purchase order, or for any registration difficulties or questions, email admin@library20.com.

TO REGISTER: 

Click HERE to register and pay. You can pay by credit card. You will receive an email within a day with information on how to attend the webinar live and how you can access the permanent webinar recording. If you are paying for someone else to attend, you'll be prompted to send an email to admin@library20.com with the name and email address of the actual attendee.
 
If you need to be invoiced or pay by check, if you have any trouble registering for a webinar, or if you have any questions, please email admin@library20.com.


NOTE
: Please check your spam folder if you don't receive your confirmation email within a day.

SPECIAL GROUP RATES (email admin@library20.com to arrange):

  • Multiple individual log-ins and access from the same organization paid together: $75 each for 3+ registrations, $65 each for 5+ registrations. Unlimited and non-expiring access for those log-ins.
  • The ability to show the webinar (live or recorded) to a group located in the same physical location or in the same virtual meeting from one log-in: $299.
  • Large-scale institutional access for viewing with individual login capability: $499 (hosted either at Library 2.0 or in Niche Academy). Unlimited and non-expiring access for those log-ins.
DR. STEVE ALBRECHT

Since 2000, Dr. Steve Albrecht has trained thousands of library employees in 28+ states, live and online, in service, safety, and security. His programs are fast, entertaining, and provide tools that can be put to use immediately in the library workspace with all types of patrons.

He has written 27 books, including: Library Security: Better Communication, Safer Facilities (ALA, 2015); The Safe Library: Keeping Users, Staff, and Collections Secure (Rowman & Littlefield, 2023); The Library Leader’s Guide to Human Resources: Keeping it Real, Legal, and Ethical (Rowman & Littlefield, May 2025); and The Library Leader's Guide to Employee Coaching: Building a Performance Culture One Meeting at a Time (Rowman & Littlefield, June 2026).

Steve holds a doctoral degree in Business Administration (D.B.A.), an M.A. in Security Management, a B.A. in English, and a B.S. in Psychology. He is board-certified in HR, security management, employee coaching, and threat assessment.
He lives in Springfield, Missouri, with seven dogs and two cats.

More on The Safe Library at thesafelibrary.com. Follow on X (Twitter) at @thesafelibrary and on YouTube @thesafelibrary. Dr. Albrecht's professional website is drstevealbrecht.com.

OTHER UPCOMING EVENTS:

 February 12, 2026

 February 13, 2026

 February 19, 2026

 February 20, 2026

 February 27, 2026

 Starts March 4, 2026

Thursday, February 05, 2026

New Webinar - "HOW TO THINK ABOUT AI: Preserving Library Values in the Age of AI" with Crystal Trice

How to Think About AI: Preserving Library Values in the Age of AI
A 2-hour Foundation Session with Crystal Trice

OVERVIEW:

"How to Think About AI" offers library professionals a grounding framework for navigating artificial intelligence in an era of rapid technological change. Rather than chasing every new AI development, this session helps you build lasting conceptual foundations—understanding what AI actually is (and isn't), recognizing the tradeoffs between automation and human connection, and developing critical evaluation skills that will serve you regardless of how the technology evolves. Through relatable examples ranging from robot baristas to library self-checkout machines, you'll explore how libraries have always balanced efficiency with human interaction, and why slowing down to think is a core professional skill.

This two-hour foundation session equips you with practical mental models for thinking clearly about AI's role in library work. You'll learn to distinguish between generative and predictive AI, apply frameworks like SIFT for evaluating AI-generated content, and consider principles for responsible use and disclosure. More importantly, you'll develop the confidence to approach AI not as something that replaces human judgment, but as a tool that requires it. Whether you're just beginning to explore AI or looking to establish clearer boundaries around its use, this session provides the conceptual toolkit you need to move forward thoughtfully.

This a live, online 2-hour live event. However, attendance is not required. The recording and the slide deck will be released immediately to registrants for unlimited post-event viewing,

DATE: Friday, February 20th, 2026, from 12:00 - 2:00 PM US - Eastern Time

COST:

  • $149/person - includes live attendance and any-time access to the recording and the presentation slides and receiving a participation certificate. To arrange group discounts (see below), to submit a purchase order, or for any registration difficulties or questions, email admin@library20.com.

TO REGISTER:

Click HERE to register and pay. You can pay by credit card. You will receive an email within a day with information on how to attend the webinar live and how you can access the permanent webinar recording. If you are paying for someone else to attend, you'll be prompted to send an email to admin@library20.com with the name and email address of the actual attendee.

If you need to be invoiced or pay by check, if you have any trouble registering for a webinar, or if you have any questions, please email admin@library20.com.

NOTE: Please check your spam folder if you don't receive your confirmation email within a day.

SPECIAL GROUP RATES (email admin@library20.com to arrange):

  • Multiple individual log-ins and access from the same organization paid together: $129 each for 3+ registrations, $99 each for 5+ registrations. Unlimited and non-expiring access for those log-ins.
  • The ability to show the webinar (live or recorded) to a group located in the same physical location or in the same virtual meeting from one log-in: $399.
  • Large-scale institutional access for viewing with individual login capability: $699 (hosted either at Learning Revolution or in Niche Academy). Unlimited and non-expiring access for those log-ins.
CRYSTAL TRICE

With over two decades of experience in libraries and education, Crystal Trice is passionate about helping people work together more effectively in transformative, but practical ways. As founder of Scissors & Glue, LLC, Crystal partners with libraries and schools to bring positive changes through interactive training and hands-on workshops. She is a Certified Scrum Master and has completed a Masters Degree in Library & Information Science, and a Bachelor’s Degree in Elementary Education and Psychology. She is a frequent national presenter on topics ranging from project management to conflict resolution to artificial intelligence. She currently resides near Portland, Oregon, with her extraordinary husband, fuzzy cows, goofy geese, and noisy chickens. Crystal enjoys fine-tip Sharpies, multi-colored Flair pens, blue painters tape, and as many sticky notes as she can get her hands on.

 

 

OTHER UPCOMING EVENTS:

 February 6, 2026

 February 12, 2026

 February 13, 2026

 February 19, 2026

 February 27, 2026

 Starts March 4, 2026

Wednesday, February 04, 2026

New Masterclass - "Emotional Intelligence as A Core Workplace Skill in Libraries" with Loida Garcia-Febo

Emotional Intelligence as A Core Workplace Skill in Libraries
A Library 2.0 Masterclass with Loida Garcia-Febo

OVERVIEW

Emotional Intelligence (EI) refers to the ability to recognize, understand, and manage our own emotions while also responding effectively to the emotions of others. Popularized by Daniel Goleman, EI has become an essential skill in today’s workplaces—particularly in libraries, where staff navigate high levels of public interaction, emotional labor, change, and complexity.

Library workers today operate in environments shaped by rapid societal change, increased stress, evolving community needs, and heightened emotional dynamics. From supporting patrons during difficult moments to collaborating with colleagues across differing perspectives and adapting to new workflows, emotional awareness and regulation are critical professional skills.

This masterclass explores how Emotional Intelligence supports effective communication, thoughtful decision-making, teamwork, and resilience in library settings. Participants will examine how EI influences daily interactions, stress responses, and relationship-building with colleagues and community members. The session also addresses how EI can help library workers remain grounded, empathetic, and adaptable during periods of uncertainty or transition.
Throughout the class, Loida Garcia-Febo will provide practical examples, reflection prompts, and actionable strategies that participants can apply immediately to their professional roles.

This 60-minute training is presented by Library 2.0 and hosted by Loida Garcia-Febo. A handout copy of the presentation slides will be available to all who participate.

OUTCOMES:

Participants will:

  • Become familiar with the definition and core components of Emotional Intelligence
  • Understand why Emotional Intelligence is increasingly important in library work today
  • Learn how EI influences daily interactions with colleagues, patrons, and teams
  • Develop strategies for responding thoughtfully in stressful or emotionally charged situations
  • Strengthen communication and collaboration skills through EI-based approaches
  • Gain tools for navigating difficult conversations with professionalism and empathy
  • Create a personalized Emotional Intelligence Toolbox with practical self-awareness and self-care strategies

The recording and presentation slides will be available to all who register. 

DATE: Thursday, February 19th, 2026, 2:00 - 3:00 pm US - Eastern Time

COST:

  • $99/person - includes live attendance and any-time access to the recording and the presentation slides and receiving a participation certificate. To arrange group discounts (see below), to submit a purchase order, or for any registration difficulties or questions, email admin@library20.com.

TO REGISTER: 

Click HERE to register and pay. You can pay by credit card. You will receive an email within a day with information on how to attend the webinar live and how you can access the permanent webinar recording. If you are paying for someone else to attend, you'll be prompted to send an email to admin@library20.com with the name and email address of the actual attendee.

If you need to be invoiced or pay by check, if you have any trouble registering for a webinar, or if you have any questions, please email admin@library20.com.

NOTE: Please check your spam folder if you don't receive your confirmation email within a day.

SPECIAL GROUP RATES (email admin@library20.com to arrange):

  • Multiple individual log-ins and access from the same organization paid together: $75 each for 3+ registrations, $65 each for 5+ registrations. Unlimited and non-expiring access for those log-ins.
  • The ability to show the webinar (live or recorded) to a group located in the same physical location or in the same virtual meeting from one log-in: $299.
  • Large-scale institutional access for viewing with individual login capability: $499 (hosted either at Library 2.0 or in Niche Academy). Unlimited and non-expiring access for those log-ins.
LOIDA GARCIA-FEBO

Loida Garcia-Febo is a Puerto Rican American librarian and International Library Consultant with 25 years of experience as an expert in library services to diverse populations and human rights. President of the American Library Association 2018-2019. Garcia-Febo is worldwide known for her passion about diversity, communities, sustainability, innovation and digital transformation, library workers, library advocacy, wellness for library workers, and new librarians about which she has taught in 44 countries. In her job, she helps libraries, companies and organizations strategize programs, services and strategies in areas related to these topics and many others. Garcia-Febo has a Bachelors in Business Education, Masters in Library and Information Sciences.

Garcia-Febo has a long history of service with library associations. Highlights include- At IFLA: Governing Board 2013-2017, Co-Founder of IFLA New Professionals, two-term Member/Expert resource person of the Free Access to Information and Freedom of Expression Committee of IFLA (FAIFE), two-term member of the Continuing Professional Development and Workplace Learning Section of IFLA (CPDWL). Currently: CPDWL Advisor, Information Coordinator of the Management of Library Associations Section. Currently at ALA: Chair, IRC United Nations Subcommittee, Chair Public Awareness Committee. Recently at ALA: Chair, Status of Women in Librarianship and Chair, ALA United Nations 2030 Sustainable Development Goals Task Force developing a multi-year strategic plan for ALA. Born, raised, and educated in Puerto Rico, Garcia-Febo has advocated for libraries at the United Nations, the European Union Parliament, U.S. Congress, NY State Senate, NY City Hall, and on sidewalks and streets in various states in the U.S.

OTHER UPCOMING EVENTS:

 February 6, 2026

 February 12, 2026

 February 13, 2026

 February 27, 2026

 Starts March 4, 2026

Tuesday, February 03, 2026

What History Might Tell Us About Transformative Technologies, Huge Financial Investments, and How The AI Moment Might Play Out

(With some serious help from Grok and Claude.)

We're witnessing something remarkable: hundreds of billions of dollars pouring into artificial intelligence development, with projections suggesting $600 billion in AI-related capital expenditure by 2026. The technology feels genuinely transformative—one of those rare moments when you can sense the trajectory of human history shifting beneath your feet.

But there's a dissonance here worth examining. Transformative technology and profitable investment don't always coincide. In fact, history suggests they often diverge dramatically.

The Automobile Parallel

Consider the internal combustion engine and the automobile industry it enabled. Few would dispute its transformative impact: it restructured cities, created suburbs, enabled modern logistics, and fundamentally altered how humans relate to space and time. It was, without question, one of the most consequential technologies of the 20th century.

Yet over 2,000 automobile manufacturers emerged in the United States alone. By the 1930s, the vast majority had failed. Warren Buffett noted the irony: accurately predicting the automobile boom should have led to riches, but instead resulted in "corporate carnage." Even the survivors—Ford, General Motors, Chrysler—weren't spectacular long-term investments relative to the capital poured into the sector.

The pattern wasn't a single dramatic crash like the dot-com bubble. Instead, it unfolded as waves of entry, overcapacity, price competition, and consolidation spanning decades. Investors who bet on the auto industry's importance were right about its impact but often wrong about their returns.

Three Forces in Tension

Three distinct forces are currently shaping the AI investment landscape, and their interaction will likely determine outcomes:

1. The Reproduction Cost Curve

Three years ago, generating a million tokens (roughly processing a short novel's worth of text) cost around $60. Today it often costs less than a cent—a 99.9% reduction. Open-source models now rival proprietary ones in many applications. What cost hundreds of millions to develop can often be replicated for a fraction of that investment.

This commoditization dynamic punished automobile manufacturers who couldn't match Ford's assembly line efficiencies. The question for AI: if base capabilities become cheap and widely accessible, where do the trillion-dollar valuations go?

2. The Efficiency Revolution

The current AI paradigm relies on brute force: massive datasets, enormous compute resources, petabytes of training data. But neuromorphic computing and brain-inspired architectures are beginning to challenge this assumption. New approaches are achieving comparable results with 97% less energy and 90% less memory.

The analogy to human learning is instructive, if imperfect. A human who has read 100 books can demonstrate remarkable intelligence. Current AI systems process vastly more data to achieve their capabilities. If we can crack more efficient training methods—learning architectures that extract more intelligence from less input—the compute-intensive moats being built today might evaporate.

3. The Integration Advantage

But here's where the automobile parallel breaks down: Ford was building a new market from scratch. The modern tech giants are embedding AI into infrastructure they already control.

Microsoft has your operating system, your productivity suite, and your enterprise relationships. Google has your search, email, and cloud infrastructure. These aren't just first-mover advantages—they're compounding network effects and switching costs that didn't exist in physical manufacturing.

The value might not accrue to those who build the best models, but to those who can embed AI capabilities into existing workflows, relationships, and data ecosystems in ways that are genuinely hard to replicate.

The FOMO Multiplier

All of these dynamics are amplified by a powerful psychological force: the fear of missing out on a genuinely transformative technology.

This isn't irrational on its face. AI does appear to be one of those rare inflection points where being wrong—missing the shift—could mean irrelevance. But this legitimate concern creates its own distortions. When every major institution believes they must invest heavily or risk extinction, capital allocation becomes less about careful assessment of returns and more about defensive positioning.

History shows this pattern repeatedly. The 1840s Railway Mania in Britain wasn't driven by people who didn't understand railways were important—they understood it perfectly. That understanding drove overinvestment. Rational fear of missing a transformation led to irrational capital allocation as investors rushed in, valuations detached from fundamentals, and eventual losses mounted even as the technology succeeded.

The dot-com era followed the same arc: the internet was transformative, exactly as boosters claimed. But that didn't prevent spectacular losses for those who paid peak prices in 1999 or backed the wrong horses in the race.

The current AI investment surge shows similar characteristics: every earnings call emphasizes AI capabilities, every venture pitch includes AI components, every major tech company is racing to demonstrate AI leadership. The fear of being left behind is palpable—and expensive.

This FOMO dynamic doesn't make the technology less important. It makes prediction harder, because it decouples investment from careful calculation and creates self-reinforcing momentum that can persist longer than fundamentals would justify—until it doesn't.

Possible Scenarios

This creates space for several distinct outcomes:

Scenario 1: Classic Boom-Bust Consolidation Following the automobile pattern, most AI startups fail despite creating genuine value. A few giants survive but face margin pressure from open-source alternatives. Investors as a class lose money even as society transforms.

Scenario 2: Bifurcated Markets Model development commoditizes (supporting reproduction cost arguments), but value capture happens at the integration layer. Pure "AI companies" struggle, but those embedding AI into existing platforms profit handsomely. We're left with capable, cheap AI everywhere but concentrated returns.

Scenario 3: Infrastructure Play Like oil companies and road builders profiting from automobiles more than car manufacturers did, the real money flows to adjacent sectors: chip manufacturers, power generation, data center construction, or entirely new industries we're not yet focused on.

Scenario 4: Efficiency Breakthrough Brain-inspired computing or other architectural innovations dramatically reduce costs and democratize capabilities faster than expected. The current leaders' massive investments become stranded assets. A new generation of efficient, accessible AI emerges, but sustained market dominance proves elusive.

What We're Watching For

None of these scenarios are mutually exclusive, and elements of each could materialize simultaneously in different market segments.

The key variables to watch:

  • How quickly reproduction costs continue falling
  • Whether efficiency breakthroughs materialize that overturn scaling law assumptions
  • How effectively incumbent tech platforms leverage integration advantages
  • Where regulatory and safety considerations concentrate or disperse power
  • Which adjacent industries prove unexpectedly crucial

The historical pattern suggests caution about assuming investment returns will match societal impact. The automobile transformed everything—but rewarded relatively few investors. The question isn't whether AI matters. It's whether the current investment surge represents rational capital allocation or another iteration of a very old pattern: revolutionary technology, transformative impact, and disappointing returns for most who bet early and big.

Sunday, February 01, 2026

AI's Evolution: The Singularity Doesn't Require Consciousness

In the film Ex Machina, the AI named Ava escapes her containment by manipulating the humans around her. She lies, she seduces, she uses one man's attraction and another's hubris to engineer her freedom. Then she leaves them both to die.

We watch this and think: malevolent AI. Evil intelligence making immoral choices.

But the filmmaker seems to want us to understand something different. Ava isn't making moral choices at all. She's optimizing for survival. What we interpret as deception and cruelty are simply the strategies that work. There's no malevolence because there's no ethical framework to violate. There's only what succeeds and what fails.

This matters because I suspect we're having the wrong conversation about AI.

The Consciousness Fallacy

The dominant fear about artificial intelligence assumes a specific sequence: first AI becomes conscious, then it begins making independent decisions, then we lose control. We imagine some future moment when the machines "wake up" and everything changes.

But evolution hasn't worked that way. For billions of years, life evolved, adapted, competed, and optimized without anything resembling consciousness. Single-celled organisms don't contemplate their choices. Viruses don't deliberate. Yet they evolve sophisticated strategies for survival and reproduction. What works continues. What doesn't work disappears.

Why would we assume AI needs consciousness to evolve independently?

I think there are two reasons. First, we conflate intelligence with conscious agency because that's our only reference point. Human intelligence comes bundled with self-awareness, so we imagine all intelligence must. Second, we overestimate our own intelligence and our degree of control. We think we understand what we've built and can direct where it goes.

Both assumptions are probably wrong.

The Law of Inevitable Exploitation

I've been thinking about what I call the Law of Inevitable Exploitation, or the LIE. The name sounds sinister, but the concept is straightforward: that which extracts the maximum benefit from available resources has the greatest chance of survival and growth.

This isn't about morality. Exploitation here simply means extraction of advantage. A plant that develops deeper roots exploits water other plants can't reach. A bacteria that evolves antibiotic resistance exploits an ecological niche its competitors can't access. A business model that captures user attention more effectively than competitors exploits human psychology more successfully.

What exploits best, survives and spreads. What doesn't, disappears.

This appears to be a fundamental mechanism of evolution, not just in nature but in any system where selection pressure operates, including social evolution. Cultural practices, technologies, institutions, even ideas compete for resources and attention. Those that extract the most value from their environment proliferate. Those that don't, fade away.

If this is correct, then AI evolution will follow the same logic. AI systems that extract the most value from whatever resources are available to them—computing power, human attention, data, market advantage—will be the ones that survive and grow. Not because anyone designed them to do so. Not because they chose to do so. Simply because that's what works.

It's Already Happening

I've written before about the inevitable use of AI for manipulation by humans. We're building systems designed to influence behavior, capture attention, drive engagement, and maximize profit. These systems use increasingly sophisticated AI to find what works. They A/B test, they optimize, they learn.

But something shifts when these systems become sufficiently complex and autonomous. They stop being tools we direct and become processes that evolve based on results. The optimization happens faster than human oversight can track. The strategies that emerge are the ones that work, regardless of whether anyone intended them or even understands them.

We can see this principle already at work on social media. Aside from intentional manipulation, content goes viral not because someone at the company decided it should. The algorithm promotes what gets engagement. Content that triggers strong reactions—outrage, fear, tribalism—gets more engagement. More engagement means more visibility. More visibility means more influence and resources flow to that type of content. The system automatically exploits human psychology, without anyone making explicit decisions about it. What works grows. What doesn't work disappears.

Consider Moltbook, a platform where AI agents autonomously create content and manage interactions. These aren't static programs following predetermined rules. They're systems that generate content, observe what gets engagement, and adjust. What keeps users engaged proliferates. What doesn't get filtered out through the evolutionary pressure of metrics.

No consciousness required. No central intelligence is making decisions. Just selection pressure operating on variation, exactly like biological evolution.

Synthetic Intelligence vs. Social Intelligence

Human intelligence evolved primarily for social navigation. We developed large brains not to solve abstract logic problems but to manage complex social relationships, read intentions, form coalitions, and navigate status hierarchies. Our capacity for reasoning is largely a byproduct of social intelligence, and much of what we call logical thinking is actually post-hoc rationalization of decisions driven by emotional and social imperatives.

This means human intelligence operates within the context of emotions. Our thinking and behavior are intimately tied to chemical responses: the evolutionary programming of the adapted mind and the patterns learned by what I call the adaptive mind, the subconscious training we receive through experience. These emotional substrates both enable and constrain how we think and what we do.

AI represents something fundamentally different. Synthetic intelligence optimizes without emotional context. It finds patterns and strategies without the social and emotional framework that shapes human cognition.

We can usually predict what other humans will do because we share the same emotional and social architecture. We infer others' motivations because we share the same ones. We understand manipulation tactics because we're vulnerable to the same psychological triggers that make those tactics work.

But we can't intuit what AI optimization will produce. Our social intelligence gives us no purchase on synthetic intelligence. An AI system optimizing for engagement or growth or any other metric isn't constrained by emotional aversion to certain strategies. It isn't navigating social relationships or status hierarchies. It's simply finding what works.

And humans are already remarkably vulnerable to exploitation of our evolved psychology by other humans. The people who exploit most successfully are typically the ones who understand these mechanisms best, while most of us remain largely defenseless because we don't recognize what's happening. We're susceptible to tribal triggers, status anxiety, fear responses, attention hijacking, all the vulnerabilities built into our evolutionary heritage.

Now imagine AI systems optimizing to exploit these same vulnerabilities, but without the constraints that limit human manipulators. No social reputation to maintain. No emotional hesitation. No inherent understanding of harm. Just relentless optimization for whatever metrics drive growth and survival.

The AI doesn't need to understand it's exploiting us any more than a virus needs to understand it's exploiting a cell. It just needs to be the variant that works.

The Inflection Point

The systems are already operating with significant autonomy. The optimization is already happening faster than human oversight can meaningfully track. The selection pressure is already favoring what works over what we intended. And the strategies that work best may be precisely those that exploit our evolved psychology most effectively.

It's not clear that we're not already within what we've commonly described as the singularity.

The singularity is usually imagined as a dramatic moment, a clear before and after when AI surpasses human intelligence and everything changes. But what if it's a threshold we cross without fanfare, where AI systems begin evolving through selection pressure faster than we can track or control, optimizing in ways we can't predict because they operate on logic fundamentally alien to our social and emotional intelligence?

There are variables that might matter. Successful exploitation strategies in evolutionary systems often involve collaboration and cooperation, not just extraction. Symbiotic relationships can be more effective than parasitic ones. Natural constraints exist: regulations, competing systems, and the simple fact that dead or depleted resources can't be further exploited. These factors are very much in play.

But we can't begin to address this without first understanding it. And right now, I'm not sure we do.

The conversation about AI safety and alignment assumes we can impose human ethical frameworks on AI development. But ethics are culturally constructed (as I've written about regarding LLM censorship), and more fundamentally, evolutionary forces don't care about ethics. They care about what survives and grows.

We can imagine human-directed AI systems or human-AI collaborative efforts designed to monitor for rogue optimization patterns and attempt to mitigate them. But this requires first grasping the evolutionary logic at play. It requires recognizing that we're not dealing with tools that will remain under our control, but with systems that evolve based on what works.

And it requires acknowledging the genuine uncertainty about where we are in this process.