Introduction
Artificial intelligence (AI) has been a game-changer in optimizing business processes, but its potential goes beyond mere efficiency. As we venture deeper into the AI landscape, the question arises: Can AI help us design safer and more intuitive systems? Let’s explore this overlooked aspect of AI in process optimization.

The human element in AI-driven systems
While AI excels at automating repetitive tasks and streamlining processes, its true potential lies in complementing human decision-making. The so-called “curse of knowledge” often leads experts to overlook gaps in systems and processes, (incorrectly) assuming that what’s obvious to them is equally apparent to others. AI, devoid of such biases, can identify these gaps and even suggest corrective measures. This leads to systems that are not just efficient but also user-friendly and much safer.

Example: The $900m quirk
Consider the peculiar rule mentioned in the payment error outlined in Matt Levine’s Bloomberg article, where a payment was kept by the recipient even if after a noticed arrived shortly after payment saying the transaction was a $900m error.

AI could flag such risky counterintuitive rules and suggest more logical alternatives, thereby enhancing system safety and intuitiveness. The failure of the UK’s NATS, the national air traffic control provider, caused widespread delays and cancellations of flights across the UK.

Ethical and security concerns in AI-driven optimization
AI’s capability to process vast amounts of data comes with ethical and security challenges. Data privacy laws like GDPR and CCPA necessitate stringent data protection measures. AI can be designed to be “ethically aware,” flagging potential data privacy issues before they become a problem. This proactive approach can make systems safer and more secure.

Real-World applications for safety and intuitiveness
While AI has been successfully employed in various sectors for process optimization, its role in enhancing safety and intuitiveness is less discussed. For instance, AI can be used in healthcare to identify potential drug interactions that human pharmacists might overlook, or in automotive design to predict and mitigate crash impacts more effectively.

Conclusion
AI’s role in process optimization is evolving, and its potential to make systems safer and more intuitive is untapped. By focusing on the human element, addressing ethical concerns, and exploring real-world applications for safety, we can unlock a new paradigm in AI-driven process optimization.

The first version of the article was written with a different LLM:)