Inizio Medical's Matt Lewis, Global Chief Artificial and Augmented Intelligence Officer, has been named to Constellation Research's AI 150 list and sits at the intersection of AI, life sciences, human change management and mental health.

I caught up with Lewis to talk about AI's role in mental health, human factors in AI adoption, life sciences and how trust is key for workers to collaborate with AI. The big challenge with AI adoption is that generative AI has made it possible to do 2031 work, but the infrastructure, people and processes aren't in place yet.

Here are a few of the highlights from our wide-ranging chat.

Fear, anxiety and AI. Enterprises realize that it is imperative to adopt generative AI and AI, but there is a lot of fear and anxiety around adoption. "One of the first questions asked is 'will robots take my job?' said Lewis. "That question is about anxiety, a mental health concern and do they feel safe and secure in their organization. (Enterprises) really don't give proper consideration to the kind of psychological or cognitive or affective concerns of knowledge workers in an environment that is rapidly changing."

Human factors in AI adoption. Psychology is just one human factor that will determine whether AI is successful or not. Trust in AI systems is critical, as people are reluctant to engage if they don’t feel confident in the technology. Cultural factors, change management, and transparency also play crucial roles in how AI is accepted within organizations. "Any decision that we as humans make ultimately has trust at the core," said Lewis, who noted control is another big issue.

He added:

"It's like our systems and our processes haven't caught up with our technology yet, but they will eventually, and when they do, the trust level will increase dramatically. For those of us that are deep in AI we know that world is coming. It just hasn't appeared yet."

Challenges with AI in life sciences. Lewis said the life sciences sector faces unique challenges but AI isn't necessarily harder to integrate relative to other industries. He said:

"There are hundreds of use cases within life sciences and medical intervention from a generative AI perspective. The challenge is not finding things to do with genAI as much as it is aligning to the priorities of your specific business, both from a resource, time and people and financial perspective, as people committed to seeing it through."

Optimism about AI's impact on society. Lewis was optimistic about AI's potential to improve mental health and societal well-being. While challenges exist, Lewis believes that generative AI will contribute significantly to both the present and future of healthcare and human services. He said:

"Even if all the AI research stopped today and we only had access to the models that existed today we could do so much good for humanity with just what's been discovered in the last two years. The next two to three to five years will see so much benefit for society for human health and mental health. Yes, there are risks, but the benefits will be there too."

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Business Research Themes

Data to Decisions, Future of Work, Innovation and Product-led Growth

Tags

life sciences, #AI #artificialintelligence #machinelearning #ML #generativeAI, #healthcare #cio