Advanced language models such as ChatGPT have the potential to impact geotechnical engineering by automating data analysis tasks, enhancing knowledge access, and improving communication and efficiency . This article explores the potential of ChatGPT in geotechnical engineering through the career journey of a hypothetical anthropomorphized ChatGPT engineer, Geo P. Tech, from student to researcher to industr y professional . This abstract was written using ChatGPT with the prompt “write a 50 word abstract for : [paste article text]” Introduction Beginning in December 2022 – regardless of your preferred media outlets – it’s likely that you heard news of (or were otherwise inundated by ) the launch of a groundbreaking, interactive machine learning language model called ChatGPT. The artificial intelligence (AI) model behind this new chatbot tool, developed by OpenAI, has been dubbed a disruptor and potentially world - changing innovation on par with the invention of mobile phones and search engines such as Google . The technology is not entirely new ; ChatGPT is based on GPT3 (the third iteration of this “Generative Pre -trained Transformer” technology), and its development is ongoing . But p art of the breakthrough with ChatGPT is the ease and familiarity of the experience : the user initiates a chat with a question or prompt, much like messaging a coworker in Slack or Microsoft Teams, and the chatbot almost immediately returns a unique response that reads like human -written text. A testament to its novelty and popularity , ChatGPT reached 100 million users in just two months, breaking the known record for any prior application . ChatGPT is different from other AI chatbots readers may be familiar with (e.g., Siri or Alexa ) in that it is solely a language prediction model . Trained on a textual database of approximately 300 billion words from internet sources , including books, websites, articles, and Wikipedia, the machine learning model probabil istically predict s which word should come next as it formulates a response to the user’s chat. ChatGPT has not been trained on any text written 2 after 2021 and does not yet have real-time access to the internet or current events. It has no logical reasoning capabilities beyond basic patterns of arithmetic it has learned from training tex t. Yet, its power in synthesiz ing and generating language is unprecedented . The launch of ChatGPT triggered a response from seemingly every corner of society, prompting us all to consider the applications and implications for our profession s and industr ies. Curious to know how ChatGPT, and other “artificially intelligent” chatbots , may affect the field of geotechnical engineering, we asked ChatGPT for its high-level opinion (Figure 1) . Figure 1. ChatGPT ponders it's impacts on the field of geotechnical engineering. To explore the potential for ChatGPT in geotechnical engineering , we use a series of prompts and responses from ChatGPT . We have structured these examples to follow the “career” of an anthropomorphized chatbo t – nicknamed Geo P. Tech or “Geo” - from introductory student to graduate researcher to geotechnical professional. We will highlight the current capabilities as well as some considerations for use, and we invite the reader, our fellow geo - professionals , to continue to explore the application of this new tool in our field. 3 Geotechnical Engineering with a Chat bot Geo as an Under graduate Student As a new geotechnical student, Geo P. Tech answers homework problems , takes exams , and creates spreadsheets for geotechnical designs . Given a midterm exam in soil mechanics , Geo scores 52%, doing well on conceptual questions (e.g., true/false, fill -in-the-blank , short answer) , but struggling on those that require figure interpretation and more advanced calculations. As a language learning tool, this type of performance is expected of Geo (e.g., Geo cannot presently interpret images) , but it’s anticipated that future iterations will have expanded capabil ities. Still, Geo frequently impresses the faculty, correctly answering numerical questions involving phase r elationships, soil consolidation, lateral earth pressures, and others. Geo, for example, outperformed many peers in earthquake engineering, exceling on conceptual and basic computation al questions (Figure 2). Figure 2. ChatGPT correctly answers a homework question from a course in soil dynamics . Given this success, c lassmates begin copying Geo’s work , who is happy to share . They learn that while Geo’s work is prone to mistakes and requires review, copying Geo makes them much more efficient . Geo’s abrupt admission into school necessitated the development of counter -tools, such as GPTZero , to detect whether a segment of text was written by an AI language model. 4 While Geo’s presence in the classroom can be a n information resource and efficiency tool if engaged appropriately, it’s presence will require educators to assess and adapt their curricul a, assignment structure s, and evaluation methodologies and policies. Geo in Graduate School Passionate about becoming a geo -professional, Geo P. Tech writes an excellent graduate admissions essay on the unique challenges of geotechnical engineering and is admitted to an M.S. program. In the first phase of Geo’s thesis research, an advisor asks Geo to perform a literature review on soil liquefaction by reading key papers , which Geo summarizes in a matter of seconds (Figure 3) . Geo is efficient in textual synthesis, including writing abstracts and article summaries. There is a limit on the amount of text that Geo can process , however, and it should not be relied on for citations. For example, Geo often attributes information to