New developments in the shipping industry show that with the advancement of technology and artificial intelligence, human trust in information and data remains important. In a specialized panel at the Splash Singapore event, representatives from various companies, including Heidelberg Materials Trading, examined this issue.
Data Quality and Trust in Information
This panel extensively emphasized data quality. Despite the fact that more information is available today than in the past and various platforms are well connected, trust in data remains a fundamental challenge. With technological advancements, information such as ship performance, greenhouse gas emissions, and port arrival time accuracy is reported more transparently than five years ago.
However, amid this discussion, attention to the importance of trust in data and artificial intelligence decisions became a key topic. Trusting a data point is fundamentally different from trusting a recommendation generated by artificial intelligence.
The Evolution of Trust in the Shipping Industry
According to the theories of philosophers and leadership thinkers, trust includes elements such as honesty, consistency, capability, reliability, credibility, and respect. While technology can claim to excel in some of these areas, honesty and transparency, especially when there is a cost to the individual, are elements that machines cannot achieve.
For example, when an experienced charterer shares unpleasant information with their counterpart, this act is a sign of honesty and transparency. This may lead to short-term damage to relationships but helps maintain them in the long run.
While artificial intelligence can process data and model scenarios, it cannot make decisions based on honesty and transparency. In a world where key information, including real-time arrival times and cargo readiness, is still communicated through human relationships, this distinction is very important.
The results of this panel showed that success in the shipping industry depends on individuals' ability to interpret data, not merely on the volume of that data. This is particularly significant as artificial intelligence takes over more analytical work.
Ultimately, trust in artificial intelligence will certainly increase, but honesty and the willingness to be truthful in critical situations will remain a human responsibility. In the shipping industry, where trust is built slowly and lost quickly, this issue is of great importance.
