AI and the NDT technician

This is a series of articles put together by the Practitioner Committee to describe the principles of different NDT methods and techniques as an introduction to practitioners...

1. Introduction
As technology continues to advance at a breakneck pace, many industries are facing the challenge of adapting to the changing landscape. One industry that is particularly vulnerable to disruption is non-destructive testing (NDT), which relies heavily on specialised knowledge and expertise to inspect and evaluate the quality of materials and structures.

2. Are humans being replaced?
As artificial intelligence (AI) and automation become more prevalent in the field of NDT, there is a growing concern about job losses and the potential impact on the workforce. However, rather than viewing AI and automation as a threat, we should see them as an opportunity to transform the industry and create new and exciting possibilities for NDT professionals.

3. Retain control
The key to limiting the impact of job losses in NDT is to focus on up-skilling and reskilling. This means investing in programmes that help workers adapt to the changing landscape of their field and acquire new skills that are in demand. By embracing new and innovative technologies and expanding their knowledge base, NDT professionals can position themselves as valuable assets to their employers and the industry as a whole.

But up-skilling and reskilling are just the beginning. We must also focus on collaboration between humans and AI. Rather than seeing AI as a replacement for human workers, we should view it as a tool that can help us work more efficiently and accurately. By integrating AI and automation into the existing NDT workflow, we can free up human workers to focus on more complex tasks that require specialised knowledge and expertise, like knowing when the AI or automation is producing a repetitive error.

4. Augmenting with AI
In fact, the integration of AI and automation may actually create new opportunities for NDT professionals. For example, AI can help us analyse copious amounts of data and detect patterns that may not be visible to the human eye. This can lead to new insights and discoveries that can help us improve the quality and safety of materials and structures.

Furthermore, by diversifying their skills, NDT professionals can become more versatile and adaptable. This can involve learning about different NDT techniques, as well as other related fields such as data analysis or machine learning. By expanding their knowledge base, NDT professionals can position themselves as experts in multiple areas, which can make them more valuable to their employers and increase their job security.

5. Value the NDT technician
Finally, AI has made remarkable progress, but it cannot replace the intuition and experience of an NDT technician. NDT technicians are highly trained professionals who use specialised equipment and techniques to identify defects and irregularities in materials and structures. They rely on their extensive knowledge of materials science, physics and engineering to make informed decisions about the safety and reliability of objects being inspected. Their human skills and expertise, such as adapting testing methods and exercising judgement, make them essential.

NDT technicians are crucial for ensuring safety in many industries and their work cannot be fully replaced by AI technology. It is important for the industry as a whole to invest in education and training programmes that prepare NDT professionals for the changing landscape of their field. This can include courses on AI and automation, as well as other relevant technologies and trends. By providing workers with the tools and resources they need to adapt to the changing landscape, we can ensure that the industry remains strong and vibrant for years to come.

6. Conclusion
In conclusion, while the rise of AI and automation may pose a challenge to the NDT industry, it also presents a unique opportunity for transformation and growth. By embracing innovative technologies, up-skilling and reskilling, collaborating with AI, diversifying skills and investing in education and training, we can create a more dynamic and innovative industry that benefits workers, employers and society as a whole.

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