Creating human-machine partnerships with AI and automation

The economy of the future hinges on successful human-machine partnerships. Here’s how you build them.

By Professor Sally Eaves, author and global strategic advisor in emergent technologies and founder of Aspirational Futures

As a chief technology officer and professor in emergent technologies, I’ve made it my life’s work to understand how humans work with technology to create meaningful progress. But the last few years have brought about rapid change that the general workforce is struggling to keep up with. As an advisor on Dell Technologies’ recent Breakthrough study, I was among other voices in the tech community calling for a reformation in organizational relations that are inhibiting innovation. Dell’s Breakthrough study polled 10,500 respondents worldwide across industries and business functions, investigating workers’ openness to digital transformation. Their findings concluded that employees are experiencing burnout at unprecedented levels, while still being tasked with the expectation to excel and scale alongside rapid technological advancement.

On my podcast, Tomorrow’s Tech Today, I sat down with Dell CTO John Roese to ask his advice and perspective on what can be done to address the skills gap and fears surrounding automation. Here’s what he had to say.

Sally Eaves: We know that the data burden is real. What are the roadblocks we need to overcome to enable human-machine partnerships?

John Roese: Let’s just take autonomous vehicles as an example. For autonomous driving to even happen, we will have to improve the ratio of people to petabytes 3-4  the next decade or we will run out of people. The only answer is automation: sharing the burden without exhausting and overwhelming human beings. This conclusion is what led to a lot of the foundational work that the study is based on. Given the need for automation, this is not a trivial task. But the resistance to change exists for three reasons:

  1. The fear of automation (job replacement anxiety)
  2. Technology is clunky in some cases
  3. People want to hold onto certain tasks (do things how they’ve always been done)

The need to evolve and change has emerged as the fundamental gate between us getting to that future of automation and scale. Data told us that people understand they need to scale but don’t know how to do it, and they’re somewhat afraid of automation.

Your point around fear is an interesting one. The narrative around automation may be scaring people off. We know the benefits, how can we overcome the nervousness?

I think we need to be sympathetic to the fact that people are nervous. There’s a lot of negativity around AI in the world at large. The fact is that as the ratio changes, it disrupts the human ecosystem. But if you look at patterns over the last 200 years, every time we introduce automation, the net result is almost always an expansion of the economy and jobs. Another key point is that automation is unlikely to be independent. It will require partnership with humans. There’s so much demand for skilled workers to be the human in the loop with machine partnership.

 What are the big skills needed for the future?

Empathy is so important. Yes, we care about STEM skills but you don’t necessarily have to be a computer science person. We care about people who can think understand and conceptualize how to change things at a macro level. You might not need to write code; you might need to understand habits and humanity. We’re finding that the best developers are highly empathetic. You need to diversify to find people who want to collaborate and work well with a team. The composition of your team now won’t look like it looked five years ago. Today, it’s a combination of the right skills AND the right people who can work collaboratively.

That’s a great point. Great teams are based on this diversity of thought and perspective. Skills like empathy, curiosity, creativity and emotional intelligence are highly valuable. What can leaders do to bring out the best in everyone?

Learning by osmosis (meaning being in the room) is a great way to learn but has been made difficult though in the pandemic years. It’s important for people to seek out mentors and seek formalized training. Get involved if you’re invited. Be present. Take advantage and learn how people work through formal and informal mentoring and programmatic opportunities.

 Different perspectives make the invisible visible. How do we bring more diversity of thought and identity into STEAM to facilitate great teams?

There are three main ways we can address this.

  1. Understand that representation in leadership is important. Different viewpoints and perspectives strengthen a team, and the top sets the tone.
  2. Question whether the structural behaviors of your organization exclude people. Then address those issues from within.
  3. Foster inclusion in the development stage. Inclusive language, design, and user experience make an impact and create a sense of belonging.

These are important issues to address from an organizational standpoint because diverse teams outperform homogenous teams (in my opinion).

 Is there anything else you’d like to add?

It’s an important time to look at the technology stack and the ecosystem. You’ll recognize that automation is already here. The danger with resisting it is potentially running out of people and limiting progress. Automation will make your life better, allow you to scale, and serve as a critical partner for you. Change in culture, skills and talent will all benefit your organization.

Listen below to listen to the full episode or click here to play on your favorite podcast platform

Lead photo by ThisisEngineering RAEng on Unsplash