Stuart Hubbard, Senior Director of Artificial Intelligence and Advanced Development at Zebra, and Tess Valbuena, Interim CEO, Humans In the Loop
By Stuart Hubbard | May 16, 2024

Plan to Put AI to Work for Your Business? Just Make Sure There’s Always a Human in the Loop.

Though AI can work more quickly than people can in some cases, it still takes its cues from us. But that’s not the only reason why you shouldn’t let an AI work completely independently.  

Artificial intelligence (AI) has shown us both the limitations and strengths of humans, the latter being most evident in our critical thinking capabilities. Though some AI systems can be trained to become independent thinkers, they lack the emotional intelligence, common sense, and accountability of people. So, when we ask any AI to work on our behalf – or make decisions that directly impact humans’ health, safety, well-being, productivity, and so on – we must ensure it’s doing exactly what it’s supposed to do. Even a well-trained AI that passes every test could hallucinate, impart bias, or make another mistake at some point because conditions and context change in the real world, and training is never perfect. Think about it: did you know how to deal with every situation in life after completing school? Probably not. You learned as you went along – as you made mistakes and recognized that you need to adjust. 

Plus, if you are using AI systems in the European Union (EU), you’re now going to have to comply with the EU AI Act guidance for “human oversight,” and similar requirements are expected to follow soon in other regions. That’s why it is imperative that, no matter how you use AI to support your business, a person is always managing the AI.  

But what does “managing” mean? 

Well, how much you need to manage the AI system and exactly how you should manage it depends on the criticality of the decisions and actions you’re empowering the AI to make. It also depends on how much you trust the AI to “do the right thing.” 

Of course, if you don’t have time (or a team) to keep tabs on the AI 24/7, you may say that you just have to trust the AI was properly trained. But that mindset is what introduces tangible risk into your business. So, I reached out to Tess Valbuena, interim CEO of the award-winning social enterprise Humans In the Loop, for a quick chat about how her team effectively manages AI systems (since this is what they do full time). 

My team leans on Tess's team on occasion to help keep an eye on the AI systems we use for research and development (R&D). Even though we are AI engineers and have the know-how to manage our AI systems, we know how important it is to have a human in the loop around the clock. We just don’t have the bandwidth to be that “human in the loop,” so Tess’s team steps in to help us out. Her team has also helped several Zebra customers (and thousands of organizations around the world) that don’t have AI engineers or data scientists on staff but want, or maybe need, AI to assist with certain business functions. 

So, when we spoke, I asked Tess to share...

  • what types of AI systems require constant oversight and management by a human 

  • which AI systems might only need “standby” support or occasional performance checks

  • the best way to “trust but verify” that an AI is doing what it’s supposed to be doing, regardless of which type of AI you’re using or what you’re asking it to do. 

Hear what she said:

Tess and her team also wrote a short and sweet blog post highlighting some of the key takeaways from our discussion if you want to share it or bookmark it for later:

The Role of Human-in-the-Loop: Navigating the Landscape of AI Systems

You may also be interested in this discussion: 

The Truth About AI: What Mainstream Media Coverage is Missing

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Stuart Hubbard
Stuart Hubbard

Stuart Hubbard is a respected leader in the field of AI and advanced development, known for his practical approach, technical innovation, and ability to drive success in the development of cutting-edge technologies. 

He currently serves as Senior Director of Artificial Intelligence and Advanced Development at Zebra Technologies and boasts a wealth of technical experience garnered from various industries worldwide. His specialization lies in AI, machine learning, deep learning, computer vision, as well as IoT and cloud-based solutions (SaaS and PaaS). Notably, Stuart excels in building high-performing research and development teams that are capable of developing innovative and integrated solutions.

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