Happy Tuesday, everyone. I'm Frank Richardson, an organisational psychologist observing the workplace with curiosity and care. Each week, I share insights to help HR leaders better understand the people behind the processes and build cultures where both individuals and organisations can thrive.
This Week in Workplace Whiplash 🌀
A quick snapshot of work right now, where expectations are shifting faster than anyone’s quite keeping up with:
⛪ The Pope Weighs In on AI and Jobs
Pope Leo XIV has entered the AI debate, warning that without clear limits, the
technology could displace large numbers of workers. His message puts responsibility squarely on employers and policymakers to manage how AI is
introduced, not just how fast it scales.
👉HR Grapevine😬 6 in 10 Workers Say Their Boss Is Toxic
A new report finds most workers are dealing with toxic leadership, but they’re not blaming personality, they’re blaming the system. Nearly half say their companies are investing more in AI than in training managers, and many are working harder just to cope.
👉HR Dive📁Employees Asked to Report DEI Activity
The U.S. Department of Labor has told employees they can report colleagues for “DEI-related discrimination,” including activities going back three years. With whistleblower protections in place, critics warn the policy could create a culture of surveillance and fear.
👉HR Brew
And it raises a broader question about what happens when the systems around work start to matter as much as the work itself…
🤝 This edition is kindly brought to you by Metaview
Metaview surveyed 505 recruiting and hiring leaders, and the numbers are hard to ignore. 90% described their partnerships as "good." 58% admitted they actively wish they could work around their counterpart. That disconnect is showing up in real business damage, especially speed-to-hire and candidate loss.
🤐 The hiring tension is more serious than most leaders realize: 58% of recruiting and hiring leaders wish they could bypass their counterpart entirely
⚡ Misalignment is directly costing teams talent: Teams with excellent recruiter-manager partnerships are 60% less likely to lose candidates to faster-moving competitors
🤖 AI becomes valuable when it improves collaboration: Teams that say AI is core to hiring are 3.8x more likely to report excellent working relationships
📈 The strongest hiring teams treat AI as shared infrastructure: 85% of companies exceeding business goals are actively using AI in hiring workflows
Yesterday I came across this LinkedIn post from The Decision Lab about how gamification is shaping motivation, and it immediately reminded me of something I did a few years ago.
I built a dashboard for my team. It tracked outputs, showcased impact, and made it much easier to explain what we were doing to senior leadership. Exec loved it. It gave us visibility, clarity, and a much stronger narrative around our work.
Objectively? Huge success.
But it also did something I wasn’t expecting. Over time, I started to notice the team subtly shifting how they worked. The things that showed up clearly on the dashboard got prioritised. The more ambiguous, exploratory thinking, the kind that doesn’t translate neatly into a metric, started to fall away.
Now I feel like I spot the same pattern everywhere. Not just in obvious places like fitness apps or Duolingo streaks, but in work itself. Dashboards, performance trackers, weekly metrics, productivity apps, time-on-task data. Even “visibility” is starting to feel a bit like a score.
Ten years ago, work was something you did. Now, increasingly, it’s something you track. Which sounds efficient, but it does make you wonder what that’s slowly doing to how the work actually gets done.
🎮 What do you find yourself optimising for most at work?
🧠 The behavioural science lens
What looks like better measurement often ends up reshaping behaviour in ways we don’t fully intend:
Metrics don’t just measure performance, they start to define it: Once people know what’s being tracked, they naturally begin to optimise for it. That’s the core idea behind Goodhart's Law: when a measure becomes a target, it stops working as a measure. Over time, the dashboard stops reflecting performance and starts directing it.
Gamification narrows attention, even when it increases effort: Points, streaks, and progress bars are effective because they simplify what success looks like. The trade- off is that people start focusing on what moves the metric rather than what actually matters. As research on gamification and motivation shows, these systems don’t just increase engagement, they shape where attention goes, often pulling it toward the reward structure itself rather than the underlying task.
Visible progress can crowd out meaningful work: When work is broken into trackable units, it creates a constant sense of movement. That feeling is compelling, but it doesn’t always map to impact. As this Harvard Business Review piece on productivity points out, the kinds of work that are easiest to measure aren’t always the ones that matter most, which makes it very easy to prioritise what’s visible over what’s valuable.
Tracking systems can quietly replace judgement: The more work is instrumented, the easier it becomes to rely on metrics as a proxy for quality. Instead of asking whether something is good or complete, people look for confirmation in the numbers. Studies on intrinsic vs extrinsic motivation show that heavy reliance on external metrics can weaken internal judgement over time.
🚀 What this means for leaders
Most of these systems are designed to improve performance, they just don’t always improve the right things:
Be very clear on what your metrics are actually incentivising: Every dashboard sends a signal about what matters, whether you intend it to or not. People respond to that signal quickly, especially when performance is visible. If the easiest way to succeed is to move numbers rather than create value, that pattern will take hold faster than you expect.
Don’t confuse visibility with impact: The work that shows up most clearly in systems isn’t always the work that matters most. Thinking, problem-solving, and long-term decisions are harder to track, which makes them easier to deprioritise. Over time, teams can become very good at looking productive without necessarily moving things forward.
Make space for work that doesn’t translate neatly into metrics: If everything has to be measurable, people will naturally avoid the kinds of work that aren’t. That includes reflection, experimentation, and collaboration, all of which tend to sit outside what can easily be tracked. Without space for that, performance becomes narrower, even if activity increases.
💬 Final thoughts
None of this happens all at once. It builds slowly, through small decisions about what gets tracked, what gets surfaced, and what gets rewarded.
Before long, people aren’t just doing their jobs, they’re also working out how to look good in the system. It’s a bit like Duolingo, you start out trying to learn Spanish and end up just trying not to lose your streak.
Once that mindset creeps in, it becomes much harder to separate actual performance from whatever the dashboard happens to favour.
How's the depth of today's edition?
If any of these land differently read together, I'd genuinely love to hear it. Hit reply.
Frank
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