”It doesn’t matter how perfect the AI solution is if it doesn’t solve a problem!”

”AI is the solution! But to what? For companies and organisations to succeed with their AI transformation, they must start with the basics: understanding the problems. Alice Mohlin, the AFAIR doctoral student who doesn't shy away from the heavy groundwork, puts it plainly: ‘It doesn’t matter how perfect the AI solution is if it doesn’t solve a problem!’”

Problem understanding lies at the heart of Alice Mohlin’s research. For the past four years, she has been part of the AFAIR research group, actively contributing to projects such as PrepAIr and PropAIr. These projects have focused on organisational readiness for AI transformation in manufacturing industries and proactive organisation for AI adoption. In short: how will AI impact businesses, and how can organisations prepare effectively?

Alice delves deep into the problem-understanding phase of new AI projects, exploring how issues can be identified and then addressed using innovative technology. Her work is grounded in a sociotechnical perspective, examining the intersection of humans and machines.

What made you choose to research AI?

”I’ve always found the relationship between humans, organisations, and advanced technology fascinating. I’ve studied information systems, library and information science, media technology, and organisation and leadership at various institutions in Malmö, Uppsala, and Växjö. Even when I wrote my very first essay in Malmö, I knew I wanted to continue in academia – I find it incredibly enjoyable. After completing my master’s in information systems, I was certain I wanted to research the relationship between technology and humans. The research role at AFAIR, along with the PrepAIr project – which focused on assessing businesses’ AI maturity – was simply perfect for me.”

How do you view the relationship between humans and technology?

”I personally want to avoid polarisation. Digital technology is so deeply integrated into our world that it cannot exist without us. To understand one side, you have to understand the other. That’s why I think research has such an important role to play. These are exactly the questions we need to be tackling right now.”

What drives you as a researcher?

”I genuinely enjoy the research process itself. As a researcher, I have access to a whole array of tools and established methods. I can go out into the world, use these tools, and generate new knowledge that could be of benefit to someone – and I think that’s pretty cool.”

Why is problem understanding so important?

”To succeed in AI transformation, you need to dissect the problem from the start and establish a clear vision. What is the challenge, and what do we want to achieve? Many companies are so enthusiastic about AI right now that they easily launch numerous technical initiatives without really considering why. PrepAIr and PropAIr have been about slowing down and starting from scratch. How should organisations operate during this transformation? How can they prepare and become actively involved in the development and implementation of new technology? Otherwise, it just becomes yet another piece of technology to understand and use – one that might not even be designed to solve the right problem – leaving organisations even more stressed. That’s why an initial conceptual phase is crucial, along with creating a team where everyone involved participates in identifying the problems and opportunities before developing the technical solution. Everyone involved in solving the problem must be part of understanding it – from shift workers to middle managers, senior leadership, and the developers of the AI solution.”

What should businesses consider before starting an AI project?

”Make sure the entire organisation is on board. Address basic communication issues and explain what’s being done and why. Include everyone involved in the project. Ask yourselves why you’re undertaking this project. What problems is it meant to solve? And what do those problems look like? Dive deep into both the technical and social aspects of the problem. In the long term, consider how you envision AI being integrated into the process. Could the entire process be automated in 10 years? Only by clarifying this can you truly understand how – and perhaps if – AI should or can be integrated.”

Who wins: humans or machines?

”I don’t see it as a matter of one winning over the other. Instead, I think the boundaries between humans and technology are blurring. On one hand, I’m optimistic. Together with AI, I believe we can develop a society and working life that prioritises human health and well-being, where machines take care of the ‘heavy lifting’. On the other hand, I think it demands a lot from us in terms of adaptability and curiosity to ensure that technology doesn’t make us less capable. A great, albeit humorous, depiction of this dystopia is the film Idiocracy. In it, two people frozen in the past wake up in a world where machines handle essential societal functions and daily tasks, and humanity has become completely dumbed down. What will the symbiosis between humans and technology look like in the future? That’s a question worth pondering. We’re already on that path – just look at how we’ve become inseparable from our smartphones in just a couple of decades.”