The impact of <scp>AI</scp> on the post‐pandemic generation of early career researchers: What we know or can predict from the published literature
Abstract This extensive literature review is not a stand‐alone paper, as it was conducted to help set the scene for the third and current stage of the Harbinger of Change project (H‐3), which is focusing on the impact of artificial intelligence (AI) on early career researchers (ECRs). Its purpose is to inform the design, scope and question‐forming of the ongoing interview project (2024–). The overarching aim of the review is to establish what we know of the already extant and/or predicted opportunities and challenges that AI‐driven technologies present to researchers, in general, and the cohort of junior researchers among them, in particular. It was found that very little empirical evidence exists of what is happening to ECRs on the ground, and that tends to be drowned in a sea of forecasts and prognostications. However, down the road there are clear benefits accruing to ECRs and, arguably, the most appealing for novice researchers must be the benefits of enhancing their productivity, the key to all scholarly rewards, inclusive of career advancement.
Authors
- Jorge Manuel Rias Revez (ORCID: https://orcid.org/0000-0002-3058-943X)
- Marzena Świgoń (ORCID: https://orcid.org/0000-0003-3600-8349)
- Abdullah Abrizah (ORCID: https://orcid.org/0000-0002-8224-5268)
- Anthony Watkinson (ORCID: https://orcid.org/0000-0002-2317-6557)
- David M. Nicholas (ORCID: https://orcid.org/0000-0001-8046-2835)
- Eti Herman (ORCID: https://orcid.org/0000-0001-8526-9081)
- David Clark
- Blanca Rodríguez Bravo (ORCID: https://orcid.org/0000-0002-9476-7602)
- Jie Xu (ORCID: https://orcid.org/0000-0002-9820-8066)
Institutions
- University of Lisbon (PT)
- University of Malaya (MY)
- Wuhan University (CN)
- Uniwersytecki Szpital Kliniczny w Olsztynie (PL)
- Organic Research Centre (GB)
- Universidad de León (ES)
Publication Details
- Journal
- Learned Publishing
- Published
- 2024-09-04
- DOI
- https://doi.org/10.1002/leap.1623
- Citations
- 10
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 1.20