Proceedings of the 2020 5th International Conference on Humanities Science and Society Development (ICHSSD 2020)

Employment Guidance for College Students Under the Background of Artificial Intelligence

Authors
Fang Wang, Fenghai Zhang
Corresponding Author
Fang Wang
Available Online 27 July 2020.
DOI
10.2991/assehr.k.200727.067How to use a DOI?
Keywords
Artificial intelligence, college students, employment guidance
Abstract

The employment rate of college students has always been a key issue of concern for society and universities. With the development of artificial intelligence technology, the combination of industrial selection and artificial intelligence in many fields to achieve intelligence is both an opportunity and a challenge for college students’ employment. This research surveys college students on issues related to individual employment in the age of artificial intelligence by means of questionnaire surveys, and makes relevant suggestions on employment guidance.

Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2020 5th International Conference on Humanities Science and Society Development (ICHSSD 2020)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
27 July 2020
ISBN
978-94-6252-991-5
ISSN
2352-5398
DOI
10.2991/assehr.k.200727.067How to use a DOI?
Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Fang Wang
AU  - Fenghai Zhang
PY  - 2020
DA  - 2020/07/27
TI  - Employment Guidance for College Students Under the Background of Artificial Intelligence
BT  - Proceedings of the 2020 5th International Conference on Humanities Science and Society Development (ICHSSD 2020)
PB  - Atlantis Press
SP  - 84
EP  - 87
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.200727.067
DO  - 10.2991/assehr.k.200727.067
ID  - Wang2020
ER  -