The Machines are Coming!

I’m too familiar with SkyNet, M3GAN and – what’s that robot’s name from iRobot? – to know that encoding a human element into the machines we use and design is critical to our survival.

Fine, maybe there’s a little hyperbole here, but for all humans to thrive, all human experiences need to be considered when creating and improving technology, AI tools in particular.

This was the premise of the talk I had the privilege of giving on the WORKTECH Chicago stage, joining some of the sharpest minds exploring the future of work, technology, and workplace experience design. My talk, “Encoding Humanity: Rethinking AI for a Multicultural Workforce,” was one of those moments where my research, lived experience, and conviction collided, sparking a conversation that was necessary, overdue, and deeply human.

Why Should We Care?

You mean other than SkyNet, M3GAN and Sonny (I found his name!)? AI is already transforming the way we recruit, assess, and manage talent; and it is also shaping how we define leadership, innovation, and success. And if we’re honest, the systems we’re building often carry a dangerous blind spot: they’re designed through Western, Eurocentric frameworks that fail to reflect the lived experiences of the remaining 85% of the global population.

This is a human problem as it is a tech problem. When leaders don’t intentionally encode multicultural perspectives into their business and digital strategies, exclusion starts becoming real than hypothetical.

The data backs this up:

2 out of 3 job seekers say they’re less likely to apply for jobs where AI screens candidates.
Multicultural consumers report low levels of trust in AI systems, citing fears of bias and harm.

It is not hard to see why this is the case. If AI had been in charge of choosing the best candidate for my own Fortune 100 leadership role without a bachelor’s degree but with real expertise and grit, I would have never even have had the chance to be considered. And there many plenty similar stories such as mine out there.

Designing for Humans

In a space full of workplace futurists, experience designers, and forward-thinking leaders, I challenged us to consider:

Who are we designing for, and who are we leaving out of the process?
How can we build AI with cultural intelligence baked in from the start?
What does it mean to embed human accountability in every system we deploy?
How do we scale trust, not just technology, in the future of work?

The conversation was vulnerable, provocative, a little contrarian, but necessary. Because if we don’t start asking better, bolder, and braver questions now, we risk building a future of work that leaves out a global majority.

The Future of Work is Multicultural

And the feedback that poured in afterwards confirms this. Attendees shared that my session added “fuel to their fire,” that it was research-driven yet deeply human, that it challenged them to rethink risk mitigation, talent assessments, and the ethics of the tools we’re rapidly adopting.

The algorithms we often talk about in tech design and utilization has real people, real stories and opportunities, and real systemic barriers that technology can either dismantle or deepen.

And that’s why I do this work of designing human-centered strategies. To help create a critical mass of leaders willing to think and build differently, designing technology and workplaces where human experiences are prioritized.

Encoding Humanity: Building a Multicultural Future of Work

I’m too familiar with SkyNet, M3GAN and – what’s that robot’s name from iRobot? – to know that encoding a human element into the machines we use and design is critical to our survival.

Fine, maybe there’s a little hyperbole here, but for all humans to thrive, all human experiences need to be considered when creating and improving technology, AI tools in particular.

Why Should We Care?

This is a human problem as it is a tech problem. When leaders don’t intentionally encode multicultural perspectives into their business and digital strategies, exclusion starts becoming real than hypothetical.

The data backs this up:

2 out of 3 job seekers say they’re less likely to apply for jobs where AI screens candidates.

Multicultural consumers report low levels of trust in AI systems, citing fears of bias and harm.

Designing for Humans

In a space full of workplace futurists, experience designers, and forward-thinking leaders, I challenged us to consider:

Who are we designing for, and who are we leaving out of the process?

How can we build AI with cultural intelligence baked in from the start?

What does it mean to embed human accountability in every system we deploy?

How do we scale trust, not just technology, in the future of work?

The conversation was vulnerable, provocative, a little contrarian, but necessary. Because if we don’t start asking better, bolder, and braver questions now, we risk building a future of work that leaves out a global majority.

The Future of Work is Multicultural

And the feedback that poured in afterwards confirms this. Attendees shared that my session added “fuel to their fire,” that it was research-driven yet deeply human, that it challenged them to rethink risk mitigation, talent assessments, and the ethics of the tools we’re rapidly adopting.

The algorithms we often talk about in tech design and utilization has real people, real stories and opportunities, and real systemic barriers that technology can either dismantle or deepen.

And that’s why I do this work of designing human-centered strategies. To help create a critical mass of leaders willing to think and build differently, designing technology and workplaces where human experiences are prioritized.

Because the future of work is multicultural, and it’s time our systems reflected that reality.

Encoding Humanity: Building a Multicultural Future of Work

I’m too familiar with SkyNet, M3GAN and – what’s that robot’s name from iRobot? – to know that encoding a human element into the machines we use and design is critical to our survival.

Fine, maybe there’s a little hyperbole here, but for all humans to thrive, all human experiences need to be considered when creating and improving technology, AI tools in particular.

Why Should We Care?

This is a human problem as it is a tech problem. When leaders don’t intentionally encode multicultural perspectives into their business and digital strategies, exclusion starts becoming real than hypothetical.

The data backs this up:

2 out of 3 job seekers say they’re less likely to apply for jobs where AI screens candidates.

Multicultural consumers report low levels of trust in AI systems, citing fears of bias and harm.

Designing for Humans

In a space full of workplace futurists, experience designers, and forward-thinking leaders, I challenged us to consider:

Who are we designing for, and who are we leaving out of the process?

How can we build AI with cultural intelligence baked in from the start?

What does it mean to embed human accountability in every system we deploy?

How do we scale trust, not just technology, in the future of work?

The conversation was vulnerable, provocative, a little contrarian, but necessary. Because if we don’t start asking better, bolder, and braver questions now, we risk building a future of work that leaves out a global majority.

The Future of Work is Multicultural

And the feedback that poured in afterwards confirms this. Attendees shared that my session added “fuel to their fire,” that it was research-driven yet deeply human, that it challenged them to rethink risk mitigation, talent assessments, and the ethics of the tools we’re rapidly adopting.

The algorithms we often talk about in tech design and utilization has real people, real stories and opportunities, and real systemic barriers that technology can either dismantle or deepen.

And that’s why I do this work of designing human-centered strategies. To help create a critical mass of leaders willing to think and build differently, designing technology and workplaces where human experiences are prioritized.

Because the future of work is multicultural, and it’s time our systems reflected that reality.

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