Don’t Make This Mistake When Presenting

We've all seen it happen.

A speaker gets to the front of the room and suddenly everything stops. The screen is dark. The audio does not work. The laptop needs an update. No one knows the WiFi password. Someone is searching for the right adapter.

The audience waits. The speaker stalls. Someone calls for “the tech person.” Everyone acts like this is just part of presenting.

It should not be.

The bring-your-own-device model turns public speaking into a technical gamble. Each new presenter brings a different laptop, a different charger, a different adapter, different settings, and different problems.

That is not a presenter problem. It is a room design problem.

In my latest Tech & Learning article, The Presentation Station Should Belong to the Space, Not the Speaker, I make the case for a better model: the presentation station should belong to the room.

That means the host provides one dedicated room device that is already connected, tested, and ready before the speaker steps up. The internet works. The display works. The audio works. The agenda and materials are in the cloud. Access is simple.

This is not about being fancy or high-tech. It is about reducing failure points so presenters can focus on their message and participants can focus on learning.

The article also includes a simple checklist for schools, districts, conference organizers, and event hosts who want presentation spaces that are connected, tested, accessible, and ready to go.

Read the full piece in Tech & Learning:
The Presentation Station Should Belong to the Space, Not the Speaker

Devices Down is the Wrong Goal

The AFT’s new 10-point plan, “Devices Down, Eyes Up, Hands-On,” gets some things right. Students do need more active, human, hands-on learning. They need career-connected experiences, civic engagement, collaboration, movement, and opportunities to solve real problems.

But the “devices down” frame points schools in the wrong direction.

The problem is not the device. The problem is passive learning, poor infrastructure, weak support, and policies that confuse classroom management with meaningful instruction.

In my latest piece, Devices Down Is the Wrong Goal, I respond to each of the AFT’s 10 points and explain where the plan gets it right, where it falls short, and why preparing students for the future means teaching them when technology helps, when it gets in the way, and how to use appropriate tools well.

Sometimes devices should be down.

Other times, devices should be up.

The goal is not more technology or less technology. The goal is better learning. 

Webinar: Why Digital Well-Being Must Be at the Center of AI in Schools

As schools move from talking about artificial intelligence to actually using it, the real challenge is not just access. It is building the conditions for technology use that is thoughtful, supportive, and responsible. That means clear expectations, strong partnerships, coordinated staff support, and a culture where educators feel confident and students are protected.

This Brisk Innovators webinar explores what that looks like in practice and how, as district leaders, my colleagues and I are approaching digital well-being as a foundation for responsible AI use in schools. You can check it out on the Brisk webinar page.

Reverting to Pen & Paper Won’t Improve Learning. Better Learning Design Will.

Some educators believe that better learning occurs when we remove laptops and go back to pen and paper.

But that raises an important question. Are we confusing easier classroom management with better learning?

In my latest Tech & Learning column, I explore why blaming laptops for declining learning outcomes misses the bigger issue. The problem was never the devices. It was the learning model we built around them.

The article examines why the paper vs. screens debate is often misunderstood, why arguments about the “primary use” of technology oversimplify learning, and why schools must help students learn to manage attention, choose the right tools for the task, and operate responsibly in a digital world.

It also looks at how this same debate is already emerging again with AI.

Read the full article at Tech & Learning. 

Could the Future of AI Reconnect Us to What Mattered Most?

Much of the conversation around artificial intelligence (AI) is framed in fear. White-collar professionals are increasingly anxious about AI replacing cognitive work once thought untouchable, a concern captured in The Atlantic’s piece on the worst-case future for white-collar workers. Blue-collar workers have their own version of this fear as employers test automation that shows up in the real world as robots and drones doing physical jobs once reserved for people, including delivery and warehouse work, like Amazon’s reported testing of humanoid delivery robots.

The anxiety is real. But what if we are asking the wrong question?

Instead of asking how we preserve jobs as they exist today, what if we ask whether working less might actually be progress?

We have changed the work week before. In the late 1800s, industrial workers routinely labored 60 to 70 hours per week. The 40-hour work week was not inevitable. It was the result of labor organizing and policy reform, as documented by the U.S. Bureau of Labor Statistics.

Now imagine this: because of AI-enabled automation, your employer tells you that you no longer need to work 40 hours a week to earn the same pay.

That sounds radical, but the idea of a shorter workweek is not new. In 1930, economist John Maynard Keynes argued that technological advances could eventually make a 15-hour workweek realistic, leaving society with a different challenge: how to use all that newfound freedom well, an idea he explored in Economic Possibilities for our Grandchildren.

And the redesign continues. The UK four-day workweek pilot found that most companies maintained reduced hours after the trial ended, with improved well-being and stable productivity. In Iceland, public-sector trials reducing work hours without cutting pay showed similar results: productivity held steady or improved, and worker well-being increased.

Reducing work hours did not collapse those economies. In many cases, it strengthened them.

So what if AI reducing the number of hours required to sustain society is not a crisis, but a correction?

Back to What We Once Had Without Going Backward

For much of the 20th century, many families lived on one income. One parent worked outside the home, and the other had more time for caregiving and community life.

That model was imperfect. It was rigid. It was often inequitable. It was not equally accessible across race and class. But it did provide something we are chronically short on today: time. Time scarcity is now one of the defining pressures of modern life.

Over time, dual-income households became the norm. Consumer culture expanded. Work hours expanded. Our cost of living expanded with it.

In How Consumerism Co-Opted Feminism to Reshape Work and Family Life, I explore how economic forces reshaped family life in ways we now assume are natural. They are not.

If AI reduces the hours required to earn a living, we have an opportunity to design something healthier this time. Not a return to rigid gender roles, but a future where adults work fewer hours, shared caregiving becomes normal, time with children is not squeezed into evenings, and community is not optional. Technology could make that possible.

Less Work Could Mean Better Health

More than 40 percent of U.S. adults meet the criteria for obesity, according to the Centers for Disease Control and Prevention (CDC) adult obesity data.

This is not primarily a nutrition problem. It is a time problem.

Long workdays compress everything else in life. Cooking becomes optional. Sleep becomes negotiable. Movement becomes aspirational. When time pressure decreases, health improves.

More discretionary hours could mean walking instead of rushing, cooking instead of ordering, and growing food at home or in community gardens that strengthen both nutrition and social ties.

AI does not just increase productivity. It reduces the human hours required to generate output. That time matters. Fewer work hours can mean more movement, better food, deeper rest, and healthier daily rhythms.

If Work Shrinks, Income Must Stabilize

Of course, this only works if productivity gains are shared.

For years, the discussion centered on universal basic income, a guaranteed baseline payment to every citizen. Peter Diamandis explored this in “free money, no strings attached”, arguing that exponential technologies make such models increasingly plausible.

But the conversation has shifted. Today, some technologists speak of universal stable income or even universal high income, language that reflects a move from scarcity to abundance. The Mosaic model proposes one framework for ensuring that when automation dramatically increases productivity, citizens participate in the upside.

This is not theoretical. Sam Altman’s OpenResearch unconditional cash study found that unconditional cash improved recipients’ financial well-being and ability to weather shocks, including more stable month-to-month spending, modest gains in credit outcomes, and increased savings in the early years. It also found that recipients remained engaged with work, with higher rates of job searching and applications, even as average hours worked dipped slightly.

If AI replaces large categories of labor, it strengthens the argument that efficiency gains should not accrue to a small fraction of society. They should be distributed through wages, reduced hours, and income guarantees. Income stability does not eliminate work. It prevents disruption from becoming collapse.

Stability creates freedom. Freedom creates time. Time creates space for purpose.

A Question for Education Leaders

For those of us in education, this conversation matters.

If the economy requires fewer traditional work hours, how do we prepare students? For nonstop competition, or for meaningful lives?

If abundance becomes technologically possible, schools cannot continue preparing students exclusively for scarcity. They must prepare students to use time well. That means cultivating creativity, civic engagement, health, collaboration, and judgment, not just résumé optimization.

Working Less and the Return to What Matters

For generations, long hours have been equated with virtue. But meaning does not require exhaustion.

Most of what makes life rich is not a job title. It is family, health, learning, service, creativity, and connection.

A reduction in the work required to sustain society does not have to signal collapse. It could signal maturity. We once fought to reduce 70-hour workweeks to 40. The next evolution may not be about producing more. It may be about living better.

If designed intentionally, AI could move us forward by restoring something we quietly lost: time for caregiving, time for health, time for community, and time for purpose outside the office.

The future of AI does not have to be dystopian. It could simply give us back what once mattered most: time for what matters.

Nutrition Labels Transformed Food. It’s Time for Environmental Labels to Transform AI.

I’m hearing more educators and students cite the environment as a reason not to use AI. 

Energy use. Water consumption. Emissions.

Those concerns are real.

But giving up AI isn’t the answer. Accountability is.

Check out my recent piece in Tech & Learning Magazine, where I argue that just as nutrition labels changed food, environmental labels can change AI. 

The article includes classroom-ready lessons and a practical student activity: designing an AI Environmental Label that schools can use to push vendors toward transparency and cleaner infrastructure.