Although AI is gradually dominating news headlines around the world, humans still play an important role in ensuring that the content and solutions generated by AI are accurate, reliable, and aligned with reality.

How can this be achieved? Without a doubt, it comes down to data quality. The classic saying "garbage in, garbage out" applies here as well—if we don't train AI with high-quality data, the accuracy of the content it generates will be poor. If the data is not diverse and broad enough, the results will be flawed, as they will reflect biases and lack value.

Furthermore, the development of AI also needs to consider sustainability issues. For example, GPT-3, the first publicly released model of the popular AI chatbot ChatGPT, is estimated to have consumed 936 megawatt-hours during its training—enough energy for an electric vehicle to travel to the moon and back more than six times. Clearly, this level of energy intensity is not sustainable.

Accurate data helps identify and mitigate biases, promotes fairness, and ensures that AI is used ethically. Without accurate data, users cannot build trust in AI systems, which is essential for the broader acceptance and adoption of AI-based applications.

"Calibration is crucial for ensuring data accuracy," says Mona-Lisa Grannas, Marketing Director at Beamex. "Using properly calibrated instruments, measurement results can be proven to be accurate, reliable, and repeatable. For over 40 years, Beamex has been a world-leading provider of calibration solutions, committed to building a world with more safety and less uncertainty, helping businesses improve their efficiency."