Making AI Work Podcast #004 – Louise de Beer

“I think we are often guilty as tech people that we fall in love with our solutions. And we forget to still check if they are still relevant, versatile, fit-for-purpose. Where it fits in the bigger picture in our organization.”

Getting real value out of Machine Learning can be difficult. Especially when obstacles like poor data literacy, organisational readiness and lack of investment slow adoption. JVR’s Head of Software Engineering, Louise de Beer gives us insight on psychometrics, data-readiness and reveals what businesses need to make ML work.

Data Readiness & Change Management

“… data literacy across the board is really lacking. That’s always where I start… I have to ask myself before I start: how ready is the organization for this?”

“…not even talking about AI. Just getting data analytics right Is hard. And organizations often don’t know what they’re in for, because analytics and reporting holds up a mirror… Any kind of data project comes with so much change management, not only technologically, but in the organization and the business side. And I think as data leaders, we have to address both sides of that.”.

Extending Models to Impact Employee Behaviour

“I do think psychometrics has a big part to play in behavioral data… We are gathering so much data from all our users. All the time. My outlook sends me a little reminder of what I’m supposed to be doing every day and with that kind of AI, we get so much data.”

And if we start overlaying that with things like your personality data, or your psychometric tests… I think that’s going to revolutionize the relationship an employer has with an employee… It just creates a better well-being experience on our platforms as well.”

More ML and Data Engineers 

“… Technically, the people that work in machine learning engineering and data sciences, that space has changed quite a bit.”

“I see less of a dependency on data scientists and that [the industry] is moving more towards machine learning engineers and data engineering. I think that means our industry can grow quicker. We can open it up. It’s not that prohibitive anymore.”

“I mean, that’s bringing AI back to the people. Where it should be.”

Much more on Psychometrics, data readiness & behavioural change

Give this episode a listen!

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