Applicability and Constraints in Implementing Artificial Intelligence in Biotechnology and Healthcare
Year: 2024
Type: article
Abstract: The present project investigates the feasibility and limitations of implementing Artificial Intelligence (AI) in healthcare and biotechnology through a global analysis of use cases. The study aims to assess the practicality and viability of implementing AI solutions in these fields, examining their real-world impact on diagnostics, treatment, drug discovery, and patient care. Key objectives involve identifying successful use cases demonstrating AI's positive contributions and elucidating potential barriers and ethical considerations. Utilizing a mixed-methods approach, the study employs an extensive survey and interview-based research methodology to gather insights from diverse stakeholders. The survey quantifies current adoption rates, perceived benefits, and challenges associated with AI integration. Most of the population agrees that regulations are necessary to ensure responsible AI use. Interviews with experts further explore perspectives, highlighting AI's potential as a valuable tool for education and social institutions, generating skilled jobs, and enhancing social life. However, challenges such as the destruction of manual labour, the digital divide, and concerns about human attention spans and IQs are also noted. This initiative underscores moral, ethical, and legal concerns while examining the potential of AI and Machine Learning (ML) in genomics, biotechnology, and healthcare. Recommendations include increasing public awareness, establishing organizations, and prioritizing user privacy. The initiative aims to ensure that research is conducted ethically and practically, understanding AI applications, gathering insights, and analysing potential difficulties.
Source: Figshare
Author: Garg, HK
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W6977420044
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