22–26 October |Houston, Texas ASNT… CREATING A SAFER WORLD!® JOIN US! Visit asnt.org/events 15–17 August 2023 |Dübendorf (Zurich), Switzerland International Symposium on Nondestructive Characterization of Materials John Register KEYNOTE |23 OCTOBER 2023 |4PM Amputate Fear and Embrace Your New Normal Mindset Bader Busbait FEATURED TALK |24 OCTOBER 2023 |3:30 PM Inspection Technologies Evolution Fueled by the Industrial Revolution 4.0 2307 ME July dup.indd 27 6/19/23 3:41 PM

BENEFITS AND CONCERNS of Using Emerging Artificial Intelligence Chatbots With Work in NDT BY JOHN C. ALDRIN While most of the papers in this special issue explore the use of artificial intelligence and machine learning (AI/ML) to support the evaluation of nondestructive testing (NDT) data and assist with the classification of NDT indications, there are other important ways that emerging AI tools may impact how we work in NDT. The article discusses the recent emergence of AI chatbots, also referred to as generative artificial intelligence agents or large language models (LLMs), and highlights the potential benefits and risks as part of work in the NDT field. Introduction ChatGPT, launched in late 2022, has been getting a lot of attention due to its ability to generate human-like text responses to various tasks such as answering questions or gen- erating summaries of content (Molla 2023). For many of us who have been working with computer algorithms since the 1990s, the idea of developing computer-assisted tools, like expert systems, has been around for a long time. What makes these systems different today? Recent breakthroughs in the AI field are enabling such tools to be much more useful than past generations (Wolfram 2023). To start, these models are very large. The GPT-3 architecture is from OpenAI, and the language model ChatGPT has been reportedly trained on around 45 terabytes of text data, FEATURE |AI/ML 28 M A T E R I A L S E V A L U A T I O N • J U L Y 2 0 2 3 2307 ME July dup.indd 28 6/19/23 3:41 PM