As the name suggests, Artificial Intelligence (AI) is assimilating human intelligence into machines by applying computer science knowledge. Fortunately, AI has simplified decision-making, including huge and complex data analysis, storage, and information retrieval. Mondal, B. (2020) asserts that AI has influenced personal, social, and business outlooks by developing products capable of playing music, creating social networks, and deriving data for use in e-commerce. However, despite AI’s benefits for humanity, the critics of AI are often concerned about the loss of human-to-human relations since AI is a machine.
Critics often argue that AI lacks human attributes such as compassion and empathy to bond with humans and release the same experience as communicating or interacting with fellow humans. Therefore, ethical concerns have been raised with the use of AI in fields like medicine, business, and education. The purpose of this research is to look into the fields which have had the most profound application and impact of AI by answering the research questions below;
Research Question 1: What is the level of AI application and adoption worldwide?
Research Question 2: How is AI affecting society and normal practices of human existence?
Research Question 3: What regulatory and ethical measures are being implemented to protect human activities and AI applications?
Key terms include artificial intelligence, use of artificial intelligence, AI Models, and automation.
AI is applicable in a wide range of fields today, including but not limited to; healthcare, education, the justice system, and financial services. According to Lee, H. S., & Lee, J. (2021), AI is used in academic research. However, it is still in its early stages. Moreover, AI is being applied in education in Physical Education (PE) by offering customized PE classes with learners’ evaluation and knowledge provision. Lee and Lee suggest that AI’s self-learning algorithm can offer a personal PE experience depending on the student’s psychology, abilities, and other characteristics. On the other hand, AI models such as Electronic Health Record (EHR) has improved patient outcome since it is used to analyze clinical data in ophthalmology. Moreover, EHR data has been useful in ocular disease diagnosis, such as diabetic retinopathy, through supervised machine learning that enhances risk assessment for early detection and predicting progression (Lin et al., 2020).
Since it is meant to be intelligent by artificial neural networks, one characteristic of AI is that it learns, and because it analyses clinical data in the case of EHR, it can solve problems. Moreover, according to Johri et al. (2021), AI has Natural Language Processing (NLP) subfield that uses machine learning to understand and manipulate human language to perform tasks such as spell check and translation. Additionally, AI is a machine that uses the knowledge of robotics, meaning it is more efficient, faster, and more accurate than humans. Furthermore, AI imitates human cognition, meaning it can perceive; for instance, it can recognize images. Therefore, the versatile nature of AI makes it more appealing to be adopted by humans across the globe.
The medical field is realizing the most real-world application of AI in their daily performance. According to Haleem et al. (2019), AI is set to change almost all areas of medicine. Haleem Javaid and Khan affirm that AI is used to digitally store medical records, perform check-ups, conduct personal therapy, offer targeted treatments, and discover new drugs. Moreover, AI assists surgeons in operations through imaging and offers better decision-making by performing risk analysis to control infections. Since AI reduces documentation time, understands human language, can analyze medical data, enables precise surgeries, and offers imaging tools, the use of AI in hospitals is so profound that almost every sector of medical institutions has AI models in use.
However, with increasing automation, there have to be frameworks that regulate AI applications in different fields. For instance, since AI is used in EHR, data protection policies regarding AI must be implemented to ensure patients’ data is safe. According to Rana et al. (2022), employee-related contingency regarding the application of AI includes a lack of data governance, inadequate training, and poor data quality. As we are bound to experience more technological innovations from AI, proper training and knowledge management should be prioritized to regulate AI as a tool, not to loosen the distinction between human and machine, thus upholding ethical practices.
AI is a powerful tool for this generation, and if properly applied, it will improve and sustain the quality of life. AI has revolutionized different fields of our society, more profoundly, the medical sector, where doctors and surgeons apply AI models in medical procedures and data storage. However, we must foster ethical practices while we adopt AI use. Therefore, data protection policies and accountability must be established where institutions use AI models to perform specific tasks. One thing to note is that AI has a brighter and darker side. Therefore, we should maximize the benefits and minimize the risks of using AI.
Mondal, B. (2020). Artificial intelligence: state of the art. Recent Trends and Advances in Artificial Intelligence and Internet of Things, pp. 389–425.
Lee, H. S., & Lee, J. (2021). Applying artificial intelligence in physical education and future perspectives. Sustainability, 13(1), 351.
Lin, W. C., Chen, J. S., Chiang, M. F., & Hribar, M. R. (2020). Applications of artificial intelligence to electronic health record data in ophthalmology. Translational vision science & technology, 9(2), 13–13.
Johri, P., Khatri, S. K., Al-Taani, A. T., Sabharwal, M., Suvanov, S., & Kumar, A. (2021). Natural language processing: History, evolution, application, and future work. In Proceedings of 3rd International Conference on Computing Informatics and Networks: ICCIN 2020 (pp. 365–375). Springer Singapore.
Haleem, A., Javaid, M., & Khan, I. H. (2019). Current status and applications of artificial intelligence (AI) in the medical field: An overview. Current Medicine Research and Practice, 9(6), 231–237.
Rana, N. P., Chatterjee, S., Dwivedi, Y. K., & Akter, S. (2022). Understanding the dark side of artificial intelligence (AI) integrated business analytics: assessing firm’s operational inefficiency and competitiveness. European Journal of Information Systems, 31(3), 364–387.