What happens when the systems that decide who matters stop reflecting real contribution?

In this episode of Toronto Talks, we examine what we call the Scoreboard Crisis — the growing disconnect between effort, usefulness, and reward in an economy shaped by AI, automation, and abstraction.

As machines filter work faster than institutions can adapt, many people are discovering something unsettling: the scoreboard is still running — but fewer people can see themselves on it.

This isn’t a conversation about job loss alone.
It’s about legitimacy, meaning, and who still counts when value is captured without employment, recognition, or participation.

We explore:

• Why automation doesn’t destroy value — it filters it

• How abstraction erodes meaning even when productivity rises

• Why contribution is becoming harder to prove, not harder to make

• What replaces wages when employment is no longer the primary signal of worth

• How societies may need to redefine what “useful” actually means

This episode isn’t alarmist.
It’s diagnostic.

Because when the scoreboard breaks, the question isn’t just economic —
it’s moral.

⏱️ Episode Chapters

SEGMENT 1: The Scoreboard Break
When metrics, credentials, and wages stop reflecting contribution — and why trust collapses quietly before it collapses publicly.

SEGMENT 2: Automation Isn’t a Monster, It’s a Filter
Why AI doesn’t replace humans wholesale — it sorts them. And what happens when the filter moves faster than social adaptation.

SEGMENT 3: Meaning Under Abstraction
How distance from outcomes erodes dignity, even when productivity rises. Why people feel less useful in systems that “work.”

SEGMENT 4: Value Capture Without Employment
When upside concentrates without jobs attached — and why this breaks the wage-for-worth bargain societies rely on.

SEGMENT 5: A New Definition of Useful
If the old scoreboard no longer works, what replaces it? Contribution beyond employment — and the hard questions that follow.

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