mlsanityData to 14 Oct 2026

Evaluating AI Vocational Skills Through Professional Testing

arXiv 2312.10603 ↗First posted 17 Dec 2023cs.LG cs.AIcited by 0

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Abstract (arXiv)

Using a novel professional certification survey, the study focuses on assessing the vocational skills of two highly cited AI models, GPT-3 and Turbo-GPT3.5. The approach emphasizes the importance of practical readiness over academic performance by examining the models' performances on a benchmark dataset consisting of 1149 professional certifications. This study also includes a comparison with human test scores, providing perspective on the potential of AI models to match or even surpass human performance in professional certifications. GPT-3, even without any fine-tuning or exam preparation, managed to achieve a passing score (over 70% correct) on 39% of the professional certifications. It showcased proficiency in computer-related fields, including cloud and virtualization, business analytics, cybersecurity, network setup and repair, and data analytics. Turbo-GPT3.5, on the other hand, scored a perfect 100% on the highly regarded Offensive Security Certified Professional (OSCP) exam. This model also demonstrated competency in diverse professional fields, such as nursing, licensed counseling, pharmacy, and aviation. Turbo-GPT3.5 exhibited strong performance on customer service tasks, indicating potential use cases in enhancing chatbots for call centers and routine advice services. Both models also scored well on sensory and experience-based tests outside a machine's traditional roles, including wine sommelier, beer tasting, emotional quotient, and body language reading. The study found that OpenAI's model improvement from Babbage to Turbo led to a 60% better performance on the grading scale within a few years. This progress indicates that addressing the current model's limitations could yield an AI capable of passing even the most rigorous professional certifications.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 25 of its 50 references that are in the map. First posted on arXiv 17 Dec 2023.

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25 of 50 references.

References · 25

  1. 2023Sparks of Artificial General Intelligence: Early experiments with GPT-4cited by 2,592
  2. 2023A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivitycited by 894
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  11. 2023Towards Making the Most of ChatGPT for Machine Translationcited by 138
  12. 2023How well do Large Language Models perform in Arithmetic tasks?cited by 130
13 more
  1. 2023Speak, Memory: An Archaeology of Books Known to ChatGPT/GPT-4cited by 125
  2. 2021PsyQA: A Chinese Dataset for Generating Long Counseling Text for Mental Health Supportcited by 92
  3. 2023A Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5 All You Need?cited by 84
  4. 2022GPT Takes the Bar Examcited by 65
  5. 2023Evaluating Large Language Models on a Highly-specialized Topic, Radiation Oncology Physicscited by 49
  6. 2023ParroT: Translating during Chat using Large Language Models tuned with Human Translation and Feedbackcited by 34
  7. 2023Mind meets machine: Unravelling GPT-4's cognitive psychologycited by 31
  8. 2023Evaluating GPT-3.5 and GPT-4 Models on Brazilian University Admission Examscited by 25
  9. 2023Performance of ChatGPT on the US Fundamentals of Engineering Exam: Comprehensive Assessment of Proficiency and Potential Implications for Professional Environmental Engineering Practicecited by 15
  10. 2022The Turing Deceptioncited by 5
  11. 2022Towards Zero-Shot and Few-Shot Table Question Answering using GPT-3cited by 4
  12. 2021Local Translation Services for Neglected Languagescited by 2
  13. 2023Creating Large Language Model Resistant Exams: Guidelines and Strategiescited by 2

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