As part of this year’s Tomorrow Show, our program will include four roundtable outlook sessions focusing on the following topics: Industry, Global, Finance, and Technology. Bringing together top-tier industry leaders and experts, the sessions promise to spark dynamic discussions and insightful debates.
In a recent interview, our EVP and Chief Commercial Officer Haavard Oestensen shared what he expects to gain from the Industry Outlook session that will explore how AI affects the way industries and business operate.
Looking at the big picture, we’ve talked about energy transition for many years. Many agencies continue to put out different projections focusing on fossil fuels, renewables and when these will meet. In this session, I hope to hear how companies are translating this to value creation over the next five years, ten years and beyond that in the long term. Where do they see the industry going?
And more importantly, what will work look like in 2025? In 2060? How can people prepare, and what will jobs look like? People are curious about this, and the impacts on companies are far-reaching as well in terms of re-education, upskilling and talent attraction.
At Kongsberg Digital, we work in the world’s most important industries: energy and maritime. These questions are on everyone’s minds, and as technology providers, we have an important role to play as well. Together with our customers and partners, we need to start having discussions on what work in the industry means now and how it differs from what lies ahead. This outlook session is the perfect place to start.
We can’t get away from large language models and the topic of generative AI – especially when it comes to embedding these into industries in a safe and meaningful way.We would love to hear some shared learnings from industry leaders like Shell, Chevron and LNG Canada who are experimenting with AI.
Another topic that warrants our focus is trust and veracity in AI; how to best build in parameters and metrics to follow providence and lineage. We need to know where data comes from, how it changes along its journey, and why we can be certain it’s correct, complete and trustworthy.
If I plug something into ChatGPT today, I don’t know how it came up with the answer. We want to see the sources, the data manipulation on the way and how the data has been interpreted.
Lastly, and most importantly, I want to hear how the human role is being perceived as we continue to welcome AI into our lives and businesses. Will people continue to do lab work, focus more on analysis, or manage by exception? When should they be involved—for qualitative decisions or quantitative ones? How will this be decided?
As I mentioned, trust is a major challenge. When accuracy is extremely important, trust needs to be there. If the trust is not there, people simply won’t rely on AI for critical things. Engineers don’t want to work with systems that have a black box, and that’s how it should be – how can we expect engineers to trust a system that obfuscates layers of data? And if the engineers don’t trust it, why would their supervisors, or asset managers, or anyone else?
The European Parliament’s GDPR has a policy: the right to an explanation. What this means in practice is that people have the right to understand how machine-learning models are used in automatic decision-making for, say, a bank loan. If you are denied a loan, you have the right to know why the system made this decision and how your credit score was compiled. In industries as complex as energy and maritime, ones with such an important mandate to operate safely and sustainably, we expect the same level of transparency and traceability.
Different approaches will be taken in every country because laws, employment structures, safety limitations and geopolitical influences differ. One example: how do you balance AI as a co-pilot to leverage remote workers versus operating in countries where you have requirements to be there in person? This is another challenge we need to consider as we embed AI into systems and processes.
We know there are lucrative opportunities for AI to improve energy efficiency, enable autonomous operations and make work not just easier but also more engaging and interesting for people. Industry gatherings like The Tomorrow Show give us an arena to discuss how we can ensure that the coming AIvolution will contribute to true value creation.
Haavard, thanks for taking the time to share your thoughts with us. We look forward to this roundtable session!
