Sustainable value creation and responsible AI are inextricably linked. It is a broad theme that Conclusion has divided into six pillars. In order to monitor whether these six pillars are being met correctly, Conclusion developed the Responsible AI Framework. Not only does this framework assess code or mathematics, but also at the human components that are a core part of what makes technology deliver sustainable value. "After all, technology is more than code and mathematics, it also involves things like policy, governance and organizing human involvement," Valentin explains.Â
The fact that the field of AI is still relatively young compared to a field such as traditional software development only increases the challenges, Valentin believes. "It's missing about 20 years of trial and error when it comes to figuring out how to build things right. Just think of automated testing, continuous integration and deployment, etc. AI uses many lessons learned from traditional software development, but it remains a different field with its own challenges, requiring its own solutions. While the field is developing rapidly, norms and standards are lagging behind."
He cites the example of monitoring energy consumption by AI. "If you're not careful, you'll be developing energy-guzzling applications. It would be great if a plug & play monitoring tool was available that you could use right off the shelf; a tool that uses a standard that everyone embraces. Now we still have to develop our own monitoring system and implement and manage it." Something that takes a lot of time but also adds value, because monitoring the ecological impact of AI models allows you to come up with more creative solutions, as Conclusion has already experienced with several customers.
