Introduction
The article being reviewed is based on the use of artificial intelligence in the healthcare sector especially in interacting with the patients. It mentions the application of this sector in examining the patients seamlessly such that it appears to be a human interaction to the patients. The results of AI and its applications have been vivid and the development of robots to aid human with different activities has made its application in the healthcare sector very eminent. Thus, how the concept can be applied to the medical sector to interact and examine the patients is discussed in the journal. In this review, the journal is first summarized and then critically evaluated from personal perspective to understand if its outcome is achieved or not.
Summary of the article
The use of technology in all aspects of the life is very prominent and so its influence on the medical sector needs to be studied. The applicability of the artificial intelligence (AI) in the healthcare sector is quite needed and it is in fact growing from the passive mode of using the technology to actually interacting actively with the patients. Robot-assistance implies the participation of the machines in assisting the medical practitioners with some procedures, etc. Their use is limited in enhancing the reports and thereby the analysis of the patients. However, this paper further takes it ahead to discuss the issues in the healthcare that can be resolved by using the AI by customizing the application of the reference concept of Turing Test that forms the rock bottom of AI. However, in these interactive machines, it is pertinent that they do not have faults and have the real power of decision-making as here it is an active interaction with the human beings. Thus, based on this fact, the paper further studies the implementation by modifying the Turing Test philosophy. This will provide precision about the computable investigation that will enhance the medical equipments with the eventual objective of ensuring great quality and validation before making any decision. In the basic test, a machine is successful and passes the test if the human or responder is unable to determine the difference between the machine-human interaction and human-human interaction. In this paper, the focus of the machines is not to pass the Turing test but actually understand their usability in the sector by and large (Ashrafian, Darzi & Athanasiou, 2015).
Besides, per the cases developed in the study, there are chances of having a machine or human with the probability of at least one time to be the machine interaction. For testing purpose, this is efficient as the human should not be able to differentiate between the two. It confirms the quantitative diagnostics, its precision and robustness in the assessment of the humans using the technologies in the healthcare unit (Ashrafian, Darzi & Athanasiou, 2015).
Critical Evaluation
The purpose of the article to modify the Turing Test to apply it in the healthcare sector is the centric point that has been a motivation for me to choose this very article for review. It interested me to understand how the AI's base of Turing Test can be used in active interaction with the humans and ensure seamlessness (Warwick & Shah, 2015).
While perusing this article twice, I was able to understand the implications of this study in real healthcare sector. I also took aid of extra readings to understand further what is the purpose of the Turing Test to understand why and what modifications are required to this test from the healthcare sector perspective. The concept of this test was explicitly mentioned in the paper but without actually delineating the details of the modifications. Besides, the basic purpose of the Test is to test or assess the performance of a machine that uses AI to see if a lay can differentiate between its use and human interaction (Warwick & Shah, 2015). However, this was not achieved and not planned as rigorously as possible. The study conducted in the research paper was more superficial.
The applications of Turing test are beyond the computer segment and they are very vivid. It is a long journey and the application in medical sector are also quite many. But the study's restrictive approach did not check the applicability of the machine. The testing samples and the quantitative research done were not very clear or directly pointing to the obvious (Hernandez-Orallo, 2000). There is mostly secondary data being used for the study which is not realistic. Besides, the application of data in the medical sector is very wide. There are so many symptoms that are common for multiple diseases but there are some distinctive features that set the diagnosis of each one apart. In this case, these tests were not conducted by the study (Hernandez-Orallo, 2000).
It did not meet my expectations that I had prior to the reading of this article. It more tried to assess the concept of the Turing Test rather than its application from the AI perspective. The application is not very intensive and there are prior studies that already have indicated of the similar applications in the medical sector. The study did not extend it to the new areas of medicine. The illustrations were weaker than expected and so were their evidences. The future course of action to be taken by the research is immense. The precision of the machines is assessed but their application and testing from the AI perspective was not per the mark (Hernandez-Orallo, 2000).
Conclusion
The paper sufficiently details about the concept of the Turing Test but could not take it very far to assess its real-time application in the medical sector. It lacks substance and overall the results achieved do not meet the primary objectives set for the study of this topic.
References
Ashrafian, H, Darzi, A & Athanasiou, T (2015). 'A novel modification of the Turing test for artificial intelligence and robotics in healthcare', Int J Med Robot, vol 11, no. 1, pp. 38-43.
Hernandez-Orallo, J (2000). 'Beyond the Turing Test', Journal of Logic, Language and Information, vol 9, no. 4, pp. 447–466.
Warwick, K & Shah, H (2015). 'Can Machines Think? A Report on Turing Test Experiments at the Royal Society', Journal of Experimental and Theoretical Artificial Intelligence, vol 10.