  ChatGPT has changed the AI community and an active research line is the
performance evaluation of ChatGPT. A key challenge for the evaluation is that
ChatGPT is still closed-source and traditional benchmark datasets may have been
used by ChatGPT as the training data. In this paper, (i) we survey recent
studies which uncover the real performance levels of ChatGPT in seven
categories of NLP tasks, (ii) review the social implications and safety issues
of ChatGPT, and (iii) emphasize key challenges and opportunities for its
evaluation. We hope our survey can shed some light on its blackbox manner, so
that researchers are not misleaded by its surface generation.
