Learn from artificial intelligence: the pursuit of objectivity
1
Issued Date
2025-03-03
Resource Type
eISSN
1472765X
Scopus ID
2-s2.0-86000671190
Pubmed ID
39933596
Journal Title
Letters in applied microbiology
Volume
78
Issue
3
Rights Holder(s)
SCOPUS
Bibliographic Citation
Letters in applied microbiology Vol.78 No.3 (2025)
Suggested Citation
Wang F., Marouli A., Charoenwongwatthana P., Chang C.Y. Learn from artificial intelligence: the pursuit of objectivity. Letters in applied microbiology Vol.78 No.3 (2025). doi:10.1093/lambio/ovaf021 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/106809
Title
Learn from artificial intelligence: the pursuit of objectivity
Author(s)
Corresponding Author(s)
Other Contributor(s)
Abstract
Humans continuously face threats from emerging novel pathogens and antimicrobial resistant bacteria or fungi, which requires urgently and efficient solutions. Alternatively, microbes also produce compounds or chemicals highly valuable to humans of which require continuous refinement and improvement of yields. Artificial intelligence (AI) is a promising tool to search for solutions combatting against diseases and facilitating productivity underpinned by robust research providing accurate information. However, the extent of AI credibility is yet to be fully understood. In terms of human bias, AI could arguably act as a means of ensuring scientific objectivity to increase accuracy and precision, however, whether this is possible or not has not been fully discussed. Human bias and error can be introduced at any step of the research process, including conducting experiments and data processing, through to influencing clinical applications. Despite AI's contribution to advancing knowledge, the question remains, is AI able to achieve objectivity in microbiological research? Here, the benefits, drawbacks, and responsibilities of AI utilization in microbiological research and clinical applications were discussed.