Congratulations on making it through another week and half way through 2025. This week’s episode is a bit of a throwback. If you don't remember or are new here, in January I laid out my top 10 realistic predictions for where AI, emerging tech, and the world of work were heading in 2025. I committed to circling back mid-year, and despite my shock at how quick it came, we’ve hit the halfway point, so it’s time to revisit where things actually stand.

If you didn't catch the original, I'd highly recommend checking it out.

Now, some predictions have held surprisingly steady. Others have gone in directions I didn’t fully anticipate or have escalated much faster than expected. And, I added a few new trends that weren’t even on my radar in January but are quickly becoming noteworthy.

With that, here’s how this week’s episode is structured:

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Revisiting My 10 Original Predictions

In this first section, I walk through the 10 predictions I made at the start of the year and update where each one stands today. From AI’s emotional mimicry and growing trust risks, to deepfake normalization, to widespread job cuts justified by AI adoption, this section is a gut check. Some of the most popular narratives around AI, including the push for return-to-office policies, the role of AI in redefining skills, and the myth of “flattening” capability growth, are playing out in unexpected ways.

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Pressing Issues I’d Add Now

These next five trends didn’t make the original list, but based on what’s unfolded this year, they should have. I cover the growing militarization of AI and the uncomfortable questions it raises around autonomy and decision-making in defense. I get into the overlooked environmental impact of large-scale AI adoption, from energy and water consumption to data center strain. I talk about how organizational AI use is quietly becoming a liability as more teams build black box dependencies no one can fully track or explain.

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Early Trends to Watch

The last section takes a look at signals I’m keeping an eye on, even if they’re not critical just yet. Think wearable AI, humanoid robotics, and the growing gap between tool access and human capability. Each of these has the potential to reshape our understanding of human-AI interaction, but for now, they remain on the edge of broader adoption. These are the areas where I’m asking questions, paying attention to signals, and anticipating where we might need to be ready to act before the headlines catch up.

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If this episode was helpful, would you share it with someone? Also, leave a rating, drop a comment, and follow for future breakdowns that go beyond the headlines and help you lead with clarity in the AI age.

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Show Notes:

In this mid-year check-in, Christopher revisits his original 2025 predictions and reflects on what’s played out, what’s accelerated, and what’s emerging. From AI dependency and widespread job displacement to growing ethical concerns and overlooked operational risks, this extended update brings a no-spin, executive-level perspective on what leaders need to be watching now.

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Timestamps:

00:00 – Introduction

00:55 - Revisiting 2025 Predictions

02:46 - AI's Emotional Nature: A Double-Edged Sword

06:27 - Deepfakes: Crisis Levels and Public Skepticism

12:01 - AI Dependency and Mental Health Concerns

16:29 - Broader AI Adoption and Capability Growth

23:11 - Automation and Unemployment

29:46 - Polarization of Return to Office

36:00 - Reimagining Job Roles in the Age of AI

39:23 - The Slow Adoption of AI in the Workplace

40:23 - Exponential Complexity in Cybersecurity

42:29 - The Struggle for Personal Data Privacy

47:44 - The Growing Need for Purpose in Work

50:49 - Emerging Issues: Militarization and AI Dependency

56:55 - Environmental Concerns and AI Polarization

01:04:02 - Impact of AI on Children and Future Trends

01:08:43 - Final Thoughts and Upcoming Updates

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#AIPredictions #AI2025 #AIstrategy #AIethics #DigitalLeadership

Happy Friday, everyone! This week I’m back to my usual four updates, and while they may seem disconnected on the surface, you’ll see some bigger threads running through them all.

All seem to indicate we’re outsourcing to AI faster than we can supervise, are layering automation on top of bias without addressing the root issues, and letting convenience override discernment in places that carry life-or-death stakes.

With that, let’s get into it.

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Stanford’s AI Therapy Study Shows We’re Automating Harm

New research from Stanford tested how today’s top LLMs are handling crisis counseling, and the results are disturbing. From stigmatizing mental illness to recommending dangerous actions in crisis scenarios, these AI therapists aren’t just “not ready”… they are making things worse. I walk through what the study got right, where even its limitations point to deeper risk, and why human experience shouldn’t be replaced by synthetic empathy.

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Microsoft Says You’ll Be Training AI Agents Soon, Like It or Not

In Microsoft’s new 2025 Work Trend Index, 41% of leaders say they expect their teams to be training AI agents in the next five years. And 36% believe they’ll be managing them. If you’re hearing “agent boss” and thinking “not my problem,” think again. This isn’t a future trend; it’s already happening. I break down what AI agents really are, how they’ll change daily work, and why organizations can’t just bolt them on without first measuring human readiness.

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Workday’s Bias Lawsuit Could Reshape AI Hiring

Workday is being sued over claims that its hiring algorithms discriminated against candidates based on race, age, and disability status. But here’s the real issue: most companies can’t even explain how their AI hiring tools make decisions. I unpack why this lawsuit could set a critical precedent, how leaders should respond now, and why blindly trusting your recruiting tech could expose you to more than just bad hires. Unchecked, it could lead to lawsuits you never saw coming.

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Military AI Is Here, and We’re Not Ready for the Moral Tradeoffs

From autonomous fighter jet simulations to OpenAI defense contracts, military AI is no longer theoretical; it’s operational. The U.S. Army is staffing up with Silicon Valley execs. AI drones are already shaping modern warfare. But what happens when decisions of life and death get reduced to “green bars” on output reports? I reflect on why we need more than technical and military experts in the room and what history teaches us about what’s lost when we separate force from humanity.

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If this episode was helpful, would you share it with someone? Also, leave a rating, drop a comment, and follow for future breakdowns that go beyond the headlines and help you lead with clarity in the AI age.

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Show Notes:

In this Weekly Update, Christopher Lind unpacks four critical developments in AI this week. First, he starts by breaking down Stanford’s research on AI therapists and the alarming shortcomings in how large language models handle mental health crises. Then, he explores Microsoft’s new workplace forecast, which predicts a sharp rise in agent-based AI tools and the hidden demands this shift will place on employees. Next, he analyzes the legal storm brewing around Workday’s recruiting AI and what this could mean for hiring practices industry-wide. Finally, he closes with a timely look at the growing militarization of AI and why ethical oversight is being outpaced by technological ambition.

Timestamps:

00:00 – Introduction

01:05 – Episode Overview

02:15 – Stanford’s Study on AI Therapists

18:23 – Microsoft’s Agent Boss Predictions

30:55 – Workday’s AI Bias Lawsuit

43:38 – Military AI and Moral Consequences

52:59 – Final Thoughts and Wrap-Up

#StanfordAI #AItherapy #AgentBosses #MicrosoftWorkTrend #WorkdayLawsuit #AIbias #MilitaryAI #AIethics #FutureOfWork #AIstrategy #DigitalLeadership

Happy Friday, everyone! This week’s update is one of those episodes where the pieces don’t immediately look connected until you zoom out. A CEO warning of mass white collar unemployment. A Lego research study shows that kids are already immersed in generative AI. And, Apple is shaking things up by dismantling the myth of “AI thinking.” Three different angles, but they all speak to a deeper tension:

We’re moving too fast without understanding the cost.

We’re putting trust in tools we don’t fully grasp.

And, we’re forgetting the humans we’re building for.

With that, let’s get into it.

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Anthropic Predicts a “White Collar Bloodbath”—But Who’s Responsible for the Fallout?

In an interview that’s made headlines for its stark predictions, Anthropic’s CEO warned that 10–20% of entry-level white collar jobs could disappear in the next five years. But here’s the real tension: the people building the future are the same ones warning us about it while doing very little to help people prepare. I unpack what's hype and what's legit, why awareness isn’t enough, what leaders are failing to do, and why we can’t afford to cut junior talent just because AI can the work we're assigning to them today.

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25% of Kids Are Already Using AI—and They Might Understand It Better Than We Do

New research from the LEGO Group and the Alan Turing Institute reveals something few adults want to admit: kids aren’t just using generative AI; they’re often using it more thoughtfully than grown-ups. But with that comes risk. These tools weren’t built with kids in mind. And when parents, teachers, and tech companies all assume someone else will handle it, we end up in a dangerous game of hot potato. I share why we need to shift from fear and finger-pointing to modeling, mentoring, and inclusion.

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Apple’s Report on “The Illusion of Thinking” Just Changed the AI Narrative

Buried amidst all the noise this week was a paper from Apple that’s already starting to make some big waves. In it, they highlight that LLMs and even advanced “reasoning” models (LRMs) may look smarter. However, they collapse under the weight of complexity. Apple found that the more complex the task, the worse these systems performed. I explain what this means for decision-makers, why overconfidence in AI’s thinking will backfire, and how this information forces us to rethink what AI is actually good at and acknowledge what it’s not.

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If this episode reframed the way you’re thinking about AI, or gave you language for the tension you’re feeling around it, share it with someone who needs it. Leave a rating, drop a comment, and follow for future breakdowns delivered with clarity, not chaos.

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Show Notes:

In this Weekly Update, Christopher Lind dives into three stories exposing uncomfortable truths about where AI is headed. First, he explores the Anthropic CEO’s bold prediction that AI could eliminate up to 20% of white collar entry-level jobs—and why leaders aren’t doing enough to prepare their people. Then, he unpacks new research from LEGO and the Alan Turing Institute showing how 8–12-year-olds are using generative AI and the concerning lack of oversight. Finally, he breaks down Apple’s new report that calls into question AI’s supposed “reasoning” abilities, revealing the gap between appearance and reality in today’s most advanced systems.

00:00 – Introduction

01:04 – Overview of Topics

02:28 – Anthropic’s White Collar Job Loss Predictions

16:37 – AI and Children: What the LEGO/Turing Report Reveals

38:33 – Apple’s Research on AI Reasoning and the “Illusion of Thinking”

57:09 – Final Thoughts and Takeaways

#Anthropic #AppleAI #GenerativeAI #AIandEducation #FutureOfWork #AIethics #AlanTuringInstitute #LEGO #AIstrategy #DigitalLeadership