How to Improve the Employment Competitiveness of College Students Under the Environment of Artificial Intelligence
- DOI
- 10.2991/978-94-6463-230-9_40How to use a DOI?
- Keywords
- Artificial intelligence; College students; Employment competitiveness
- Abstract
With the rapid development of artificial intelligence technology, college students are facing new opportunities and challenges in employment. In the future, there will be disruptive changes in what people work, how they work and the skills they need. The job market will definitely have substitution and creation effects. Employment guidance in colleges and universities should teach students to give play to human’s strengths in abstract concept, logical thinking, innovation ability, emotional perception ability, interpersonal communication ability, cultivate students’ scientific and technological literacy and humanistic literacy, help them form critical thinking, innovative thinking and systematic thinking, and improve their professional ability, learning ability, communication ability and practical ability. In order to meet the challenges of man-machine competition and cooperation in the future.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Lin Wang AU - Xuehui Tao PY - 2023 DA - 2023/09/04 TI - How to Improve the Employment Competitiveness of College Students Under the Environment of Artificial Intelligence BT - Proceedings of the 3rd International Conference on Internet, Education and Information Technology (IEIT 2023) PB - Atlantis Press SP - 336 EP - 341 SN - 2667-128X UR - https://doi.org/10.2991/978-94-6463-230-9_40 DO - 10.2991/978-94-6463-230-9_40 ID - Wang2023 ER -