AILGMay 7, 2023

Professional Certification Benchmark Dataset: The First 500 Jobs For Large Language Models

arXiv:2305.05377v14 citationsHas Code
Originality Synthesis-oriented
AI Analysis

This work addresses the need to assess AI employable skills for professional certification, though it is incremental as it builds on existing models with a new dataset.

The research tackled the problem of evaluating large language models' vocational readiness by testing GPT-3 and Turbo-GPT3.5 on a benchmark of 1149 professional certifications, finding that GPT-3 passed 39% of certifications without fine-tuning and Turbo-GPT3.5 achieved 100% on the OSCP exam.

The research creates a professional certification survey to test large language models and evaluate their employable skills. It compares the performance of two AI models, GPT-3 and Turbo-GPT3.5, on a benchmark dataset of 1149 professional certifications, emphasizing vocational readiness rather than academic performance. GPT-3 achieved a passing score (>70% correct) in 39% of the professional certifications without fine-tuning or exam preparation. The models demonstrated qualifications in various computer-related fields, such as cloud and virtualization, business analytics, cybersecurity, network setup and repair, and data analytics. Turbo-GPT3.5 scored 100% on the valuable Offensive Security Certified Professional (OSCP) exam. The models also displayed competence in other professional domains, including nursing, licensed counseling, pharmacy, and teaching. Turbo-GPT3.5 passed the Financial Industry Regulatory Authority (FINRA) Series 6 exam with a 70% grade without preparation. Interestingly, Turbo-GPT3.5 performed well on customer service tasks, suggesting potential applications in human augmentation for chatbots in call centers and routine advice services. The models also score well on sensory and experience-based tests such as wine sommelier, beer taster, emotional quotient, and body language reader. The OpenAI model improvement from Babbage to Turbo resulted in a median 60% better-graded performance in less than a few years. This progress suggests that focusing on the latest model's shortcomings could lead to a highly performant AI capable of mastering the most demanding professional certifications. We open-source the benchmark to expand the range of testable professional skills as the models improve or gain emergent capabilities.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes