Podcast: How AI is shaping the future of workplace safety and minimizing risks

Natasha Porter is chief customer officer at Benchmark Gensuite. Natasha has over 25 years of experience and leadership as an EHS practitioner and in the digital solution space. In her current position, Natasha leads a cross-functional team in the advancement and adoption of artificial intelligence (AI) / machine learning (ML) technologies in an effort to disrupt the way technology is applied to safety in the workplace. Natasha recently spoke with Nicole Stempak, managing editor of EHS Today, about how AI could impact workplace safety efforts.

Below is an excerpt from the podcast:

EHST: I wanted to get your opinion on what you see as some of the biggest benefits organizations stand to gain by adopting AI in the workplace. And, as a second part to that, what is it going to take to realize those benefits?

NP: What I’ve certainly seen in applying AI solutions in the field of safety and digital solutions is it can be a huge improvement for efficiency, enabling better decision making, and ultimately delivering cost savings. So, as a former EHS professional myself, what would have taken me 2-3 months in compiling data, analyzing it, and creating a report on trends, you can utilize AI today and do that in about 10 seconds. So that's just an example of the computing power and efficiency and fundamentally better decision making that AI enables folks to do. So really thinking about automating routine tasks and analyzing vast amounts of data are really great applications of AI.

Now to your second question. How do you go about achieving these gains? I think companies really need to start with a clear goal and objective in mind. Is there a pain point or a problem that you need to try and solve? And can AI provide some improvements in that area? So that's step one. I think the second piece is having quality data that you can expose that AI solution, whether it's something you develop or something that you purchase that a third-party develops, to be able to process information and get an end result. The third piece is engaging employees throughout the process because that’s important to make sure that any kind of AI adoption is successful. And I know we'll probably talk a little bit more about that, but having that connection with folks that are ultimately going to use the AI solution we're evaluating and having them along for the journey is an important consideration.

EHST: I love that. I kind of mentioned this in the last question, but new and different ideas, it's a change, and that can be really scary for folks. How are you seeing AI integrated or adopted into workplaces that's creating a change? Are there any kind of best practices for helping people navigate that change in their day-to-day lives?

NP: I think a lot of companies are using AI to automate repetitive tasks, and that really frees employees up to do more meaningful work. I'll give you a practical example. We use, at Benchmark Gensuite, the Microsoft Copilot product, and that is actually integrated into Teams. So anytime we have a meeting, internal or customer facing, we record that meeting, and we can leverage Microsoft Copilot to create a summary of what were key points that were discussed and action items that were determined during that call. So, if you think about, you know, before AI, before Microsoft Copilot, how did you manage summaries coming from meetings? How long did it take you to compile your notes if you wrote them down on paper or even if you were typing in the computer? Maybe 30 minutes, 45 minutes, depending on what you want to do. Now it takes 2 seconds to push the button, and you get the summary, and then you apply your additional edits to that.

So to me, it's the 80/20 rule. It can get you 80% of the way there very quickly. And then you have to apply your judgement and your expertise for the final mile on that final 20%. So that's a good example, and repetitive tasks are everywhere. Reporting, data analysis, trying to make decisions faster, and getting better accurate results I think are all great examples of that. And I think it also really comes back to, again, what are your biggest challenges and how can you align an AI solution that's going to deliver the most value? And bringing employees into that evaluation process is critical, not only when you are trial running an AI, but throughout the process and ensuring that employees can provide feedback to make that AI solution better.

EHST: Safety professionals are very familiar with repetitive tasks and motions. That's kind of the basis of some ergonomic best practices too. You're trying to reduce and eliminate repetitive muscle strain and fatigue. I could see AI applications helping to analyze or reduce those as well, coming up with creative solutions. So, what do safety professionals need to communicate, either with management or workers, about AI and safety? Are there any kind of ideas or best practices for those conversations?

NP: I think first and foremost, AI is a tool that can enhance safety. It is not replacing human judgment. That's really, really important. So, you really need to think about it as a tool to augment your capability, not replace the final answer or decision that you're going to make. AI should support a function like safety, and it's not about replacing workers. Again, it goes back to this point of augmentation, making the job safer, making it easier to complete the job or identify where there's a risk and how to make that improvement.

And I think the final piece is transparency. That’s really, really important. I think everyone wants to understand at some level how the AI technology works that they're engaging with, how decisions are being made so that they can build trust and confidence in that solution. So that’s important as you are thinking about building an AI solution or evaluating technology solutions. Understanding the fundamental premise for what the AI is doing and how it is going about making that decision making process is really, really important.

About the Podcast
Great Question: A Manufacturing Podcast offers news and information for the people who make, store and move things and those who manage and maintain the facilities where that work gets done. Manufacturers from chemical producers to automakers to machine shops can listen for critical insights into the technologies, economic conditions and best practices that can influence how to best run facilities to reach operational excellence.