Human-Centered AI
Work, Longevity,and Lived Experience
Grounding conversations about AI in how people are actually living and working
Much of the conversation about AI focuses on capability — what the technology can do, how fast it advances, and where it might scale next.
Far less attention is paid to how people are actually experiencing AI at work — making decisions, carrying responsibility, leading others, and navigating careers that now stretch longer than ever before.
As AI reshapes systems across industries, the human implications extend beyond productivity. They influence economic participation, professional identity, leadership accountability, and the dignity of work itself.
The gap in today’s AI conversation
AI is no longer experimental or distant. It is already embedded in everyday work — shaping how decisions are made, how performance is evaluated, how opportunity is distributed, and how people think about their relevance and value.
Yet many strategies, policies, and frameworks guiding AI adoption are still built on assumptions rather than lived experience. They focus on what systems can do, while overlooking how humans adapt, compensate, and carry the consequences of those systems in practice.
When lived experience is missing from the conversation, we risk designing AI-enabled systems that move faster than people can realistically absorb — and that disconnect innovation from trust, dignity, and accountability.
Why longevity changes the stakes
People are living longer, and for many, working longer — whether by choice, necessity, or a mix of both. Careers are no longer linear or single-phase. Instead, they increasingly involve transitions, pauses, reinvention, and portfolio paths that stretch across decades.
AI intersects with this reality in powerful ways.
On one hand, AI can extend capability, lower barriers to access, and enable people to contribute in new ways later in life. On the other, it can accelerate displacement, reinforce age-based bias, or quietly filter people out of opportunity through opaque systems.
The question is no longer simply whether AI will change work. It is how people remain visible, valued, and able to contribute meaningfully across longer working lives — and what support structures make that possible.
Judgment, responsibility, and the human role
As AI becomes part of everyday work, it increasingly informs decisions — not just tasks. People are asked to rely on AI-generated insights, recommendations, and analysis, while remaining accountable for outcomes.
This creates new pressure points:
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When should AI be trusted, and when should human judgment override it?
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Who is responsible when AI-informed decisions go wrong?
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How do leaders explain decisions when systems are involved?
These questions are not abstract governance concerns. They show up daily for managers, advisors, professionals, and leaders making real decisions with real consequences.
Human-centered AI must account for this lived reality — not just formal policy or technical design.
Beyond the organization
The implications are not limited to individual companies or roles. They extend to education pathways, workforce policy, institutional design, and how societies prepare people for longer working lives in rapidly shifting environments.
As AI reshapes economic participation, broader questions emerge:
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Who adapts easily — and who absorbs strain?
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Where does accountability sit in AI-assisted systems?
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What prevents capable professionals from being quietly excluded as technology evolves?
Responsible AI adoption requires more than technical integration. It requires understanding how people adapt, where pressure accumulates, and what enables agency rather than exclusion.
Contribute to the Research
This work centers on lived experience — how people are actually working with AI today, making decisions, and navigating responsibility across longer and evolving careers.
Participation is voluntary, anonymous, and takes approximately 5–7 minutes. No technical expertise is required. The goal is to ensure that conversations about AI are informed not only by what technology can do, but by how people experience working with it every day. Your perspective matters.
Insights from this work may inform:
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public dialogue on human-centered AI
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writing and speaking engagements
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workshops and forums focused on leadership, work, and AI
Individual responses are analyzed in aggregate.