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We talk a lot about AI reshaping the future.

We talk less about who gets to participate in it.

In this episode of FUTUREPROOF., I sit down with Corbb O’Connor, who leads accessibility advocacy at Level Access. Corbb is blind. He’s spent years consulting enterprise teams — from financial institutions to global brands — helping them design digital experiences that are actually usable by people with disabilities.

This isn’t a compliance conversation.

It’s a systems conversation.

As AI systems increasingly generate interfaces, content, decisions, and workflows at scale, accessibility can no longer be an afterthought. If accessibility isn’t embedded upstream — in product design, in data pipelines, in AI outputs — exclusion compounds just as quickly as innovation.

Corbb argues that inclusion is not a moral add-on. It’s infrastructure. It’s economics. It’s risk management. And increasingly, it’s competitive advantage.

We explore:

• Why accessibility should be treated like cybersecurity — a non-negotiable requirement, not a retroactive fix
• The difference between “AI for accessibility” and “accessible AI”
• Why automated scanning tools can’t replace human testing
• How poor product design quietly excludes users without teams even realizing it
• Why psychological safety and culture matter just as much as tooling
• And whether AI will widen or narrow accessibility gaps over the next five years

If digital products define access to banking, healthcare, employment, and civic life, then accessibility isn’t a feature.

It’s participation.

And as AI becomes core infrastructure, the question becomes sharper:

Are we scaling inclusion — or scaling exclusion?

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We talk constantly about the future of work — AI agents, automation, leaner teams, productivity gains.

But what if the real drag on performance isn’t technology — it’s coordination?

Unproductive and unnecessary meetings cost companies up to $1.4 trillion every year. Seventy-one percent of senior leaders say meetings are inefficient. The average knowledge worker now spends around 11 hours a week in meetings. And nearly half admit to faking excuses to avoid them.

This isn’t a scheduling issue.

It’s a systems issue.

Dr. Rebecca Hinds — founder of the Work Innovation Lab at Asana, the Work AI Institute at Glean, and author of YOUR BEST MEETING EVER: 7 Principles for Designing Meetings That Get Things Done — argues that meetings are organizational “junk drawers.” Instead of asking whether a meeting is necessary, companies simply default to adding another recurring invite.

Her solution is radical in its simplicity: treat meetings like products.

Define the user. Clarify the outcome. Design the experience. Measure performance. Iterate.

In this episode, we zoom out beyond tactics and ask deeper questions:

Why are humans so inefficient at coordinating with one another?
What do broken meetings reveal about incentives, trust, and accountability?
Does AI meaningfully solve meeting dysfunction — or simply automate it?
And in a world pushing toward automation, what is the human role in collaboration?

If coordination is broken, no productivity tool can save us.

And if meetings are the canary in the coal mine, we should probably pay attention.

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We live in a moment where disagreement feels dangerous.

Politics is polarized. Social media amplifies outrage. Inside companies, dissent is often muted — not because people agree, but because they assume speaking up will damage relationships or reputations.

But what if most of that fear is wrong?

Julia Minson, decision scientist at Harvard Kennedy School, studies the psychology of disagreement. Her research on “conversational receptiveness” reveals something counterintuitive: people systematically overestimate how much disagreement will harm a relationship and underestimate how much thoughtful dissent earns respect.

That miscalculation has consequences.

When leaders avoid disagreement, bad ideas survive. When teams confuse persuasion with understanding, trust erodes. When we treat conflict as a character flaw rather than a cognitive process, we weaken our institutions.

In this episode, we explore why humans are wired to assume they’re objectively right, how subtle language shifts can dramatically increase receptiveness, and why polarization may be less about ideology and more about judgment errors.

And in an era where AI systems increasingly summarize, mediate, and even “assist” in conflict, what happens if our tools inherit our biases? And if healthy disagreement is essential to good decision-making, how do we preserve it inside organizations that prize alignment over friction?

This isn’t a conversation about compromise.

It’s about whether we still know how to disagree in ways that make us smarter.