A Categorical Archive of ChatGPT Failures
- URL: http://arxiv.org/abs/2302.03494v8
- Date: Mon, 3 Apr 2023 20:02:26 GMT
- Title: A Categorical Archive of ChatGPT Failures
- Authors: Ali Borji
- Abstract summary: ChatGPT, developed by OpenAI, has been trained using massive amounts of data and simulates human conversation.
It has garnered significant attention due to its ability to effectively answer a broad range of human inquiries.
However, a comprehensive analysis of ChatGPT's failures is lacking, which is the focus of this study.
- Score: 47.64219291655723
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Large language models have been demonstrated to be valuable in different
fields. ChatGPT, developed by OpenAI, has been trained using massive amounts of
data and simulates human conversation by comprehending context and generating
appropriate responses. It has garnered significant attention due to its ability
to effectively answer a broad range of human inquiries, with fluent and
comprehensive answers surpassing prior public chatbots in both security and
usefulness. However, a comprehensive analysis of ChatGPT's failures is lacking,
which is the focus of this study. Eleven categories of failures, including
reasoning, factual errors, math, coding, and bias, are presented and discussed.
The risks, limitations, and societal implications of ChatGPT are also
highlighted. The goal of this study is to assist researchers and developers in
enhancing future language models and chatbots.
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