1
Future of AI
Student
Institution
Professor
Course
Due
2
Future of AI
Wolff, J., Pauling, J., Keck, A., & Baumbach, J. (2020). The economic impact of artificial
intelligence in health care: systematic review.,Journal of medical Internet
research,,22(2), e16866. https://doi.org/10.2196/16866/
Wolff et al. (2020) perform a systematic review to assess the impact of AI costs in the
healthcare industry. They determine if prior research fulfils objective standards for economic
effectiveness. The review identifies substantial methodological weaknesses in the present
assessments and notes that only six of 66 satisfied the minimum inclusion criteria. This is an
important area requiring improvement to take into account initial investment and cost of
operation as well as comparing solutions. This article is helpful in revealing that future research
should provide more robust and more comprehensive economic assessments of AI in healthcare
systems. The authors are experts in the field of healthcare economics as well as artificial
intelligence.
Braganza, A., Chen, W., Canhoto, A., & Sap, S. (2021). Productive employment and decent
work: The impact of AI adoption on psychological contracts, job engagement and team
member trust. Journal of Business Research,,131, 485-494.
https://doi.org/10.1016/j.jbusres.2020.08.018.
This research explores the impact of AI integration on the psychological contract,
engagement, and trust of employees under the framework of the United Nations Sustainable
Development Goal 8 (SDG 8). By examining 232 survey responses, the authors identify that AI
diminishes the previously beneficial relationship between psychological contracts and job
engagement and trust, formally defining a new Alienational contract type(Braganza et al., 2021).
It suggests growing job vulnerability but also enhanced freedom and efficiency among workers.
3
The authors, who are involved in business and technology, share helpful information on how the
use of artificial intelligence redesigns employee relations. Therefore, this source is relevant for
unravelling the multifaceted effects of AI on employees and organizational productivity.
Ashok, M., Madan, R., Joha, A., & Sivarajah, U. (2022). Ethical framework for Artificial
Intelligence and Digital technologies.,International Journal of Information
Management,,62, 102433. https://doi.org/10.1016/j.ijinfomgt.2021.102433
The authors of this paper aim to explain the application of AI in digital technologies as
well as its relationship to the 14 domains of digital ethics across seven archetypes and the four-
dimensional ontological structure(Ashok et al., 2022). The authors, therefore, propose a
conceptual model to explain the societal and organizational consequences borne by these ethical
implications. Regarding a synthesis of key findings, intelligibility, accountability, fairness,
autonomy, and privacy are outlined. As such, the ethical framework and propositions presented
in this paper hold significant potential for elucidating the ethical considerations tied to AI
implementation. This source is essential for assessing the influence of ethical aspects of AI in the
workplace because it offers a step-by-step procedure for dealing with ethical issues. These
authors effectively define and expand on a clear and comprehensive ethical model, which makes
this source very helpful for the study.
Rayhan, A., Rayhan, R., & Rayhan, S. (2023). The Role Of AI In Healthcare: Revolutionizing
Patient Care And Well-Being.,DOI: 10.13140/RG. 2.2,,22601.
This article aimed to describe how the recent innovations in technology, specifically in
artificial intelligence, are revolutionizing health care in improving diagnostic precision, tailoring
treatment plans, increasing efficiencies, and enabling patient-centred self-management(Rayhan et
al., 2023). In their view, AI has the most impactful applications in medical imaging, precision
4
medicine, and process automation, all of which contribute to enhancing patients' lives and
enhancing healthcare organizations' performance. They also tackle issues of an ethical nature,
like data privacy, algorithm bias, and job replacement in the healthcare sector. This paper
explores various practical uses of AI in the healthcare sector, as identified in the following cases.
The authors themselves give quite a rich overview of the topic, which makes this source helpful
in describing the positive consequences and ethical issues of AI use in healthcare for the project.
Choudhury, A., & Asan, O. (2020). Role of artificial intelligence in patient safety outcomes:
systematic literature review.,JMIR medical informatics,,8(7), e18599.
https://doi.org/10.2196/18599.
In this systematic literature review, Choudhury and Asan include 53 studies that
investigate the impact of AI on patient safety by analyzing machine-learning algorithms and
natural language processing(Choudhury & Asan, 2020). The review establishes clinical findings
within alarms, reports and a drug safety perspective and shows how AI applied within decision
support can improve error identification, patient segmentation and drug utilization. The authors
indicated a need for reference standards and heterogeneity in the reporting of AI, saying
validation in real-world clinical settings deserves further research. This source is valuable when
presenting the ideas and challenges of applying AI in healthcare systems through the
perspectives of safety and effectiveness of the operation.
Ahmed, Z., Mohamed, K., Zeeshan, S., & Dong, X. (2020). Artificial intelligence with multi-
functional machine learning platform development for better healthcare and precision
medicine.,Database,,2020, baaa010. https://doi.org/10.1093/database/baaa010
In this article, Ahmed et al. (2020) highlight how AI and machine learning contribute to
precision medicine by improving the accuracy of diagnosis as well as treatment plans. The
5
authors consider the use of EHR with other data sources in order to gain more insights into
disease trajectory and biological markers. They emphasize the requirement of solid analytics that
can support the integration and linking of clinical and public health networks. The study serves
as a valuable reminder of how AI could help clinicians with subject stratification and decision-
making for health care to be more effective, efficient, less costly, and individualized. This source
is helpful for the project because it contains valuable information about the utilization of AI to
transform the healthcare industry.
Yin, J., Ngiam, K. Y., & Teo, H. H. (2021). Role of artificial intelligence applications in real-life
clinical practice: systematic review.,Journal of medical Internet research,,23(4), e25759.
https://doi.org/10.2196/25759
Yin et al. 's (2021) systematic review explored the use of AI in practice and implicated 51
papers from 2010 to 2020. The diseases, including sepsis, breast cancer, diabetic retinopathy and
polyp and adenoma, were included in the review. These are the efficiency of AI algorithms in a
clinical environment, their impact on clinicians and patients, and the economic benefits of the
solution. As much as the authors acknowledge the potential of AI in enhancing clinical practices,
they also note that the field is still in its infant stage, which requires more robust research. This
source is beneficial for the project as it discusses the current development of AI and its
application in clinical practice, as well as the advantages and limitations of the technology.
6
References
Ahmed, Z., Mohamed, K., Zeeshan, S., & Dong, X. (2020). Artificial intelligence with multi-
functional machine learning platform development for better healthcare and precision
medicine.,Database,,2020, baaa010. https://doi.org/10.1093/database/baaa010
Ashok, M., Madan, R., Joha, A., & Sivarajah, U. (2022). Ethical framework for Artificial
Intelligence and Digital technologies.,International Journal of Information
Management,,62, 102433. https://doi.org/10.1016/j.ijinfomgt.2021.102433
Braganza, A., Chen, W., Canhoto, A., & Sap, S. (2021). Productive employment and decent
work: The impact of AI adoption on psychological contracts, job engagement and
employee trust.,Journal of Business Research,,131, 485-494.
https://doi.org/10.1016/j.jbusres.2020.08.018.
Choudhury, A., & Asan, O. (2020). Role of artificial intelligence in patient safety outcomes:
systematic literature review.,JMIR medical informatics,,8(7), e18599.
https://doi.org/10.2196/18599.
Rayhan, A., Rayhan, R., & Rayhan, S. (2023). The Role Of AI In Healthcare: Revolutionizing
Patient Care And Well-Being.,DOI: 10.13140/RG. 2.2,,22601.
Wolff, J., Pauling, J., Keck, A., & Baumbach, J. (2020). The economic impact of artificial
intelligence in health care: systematic review.,Journal of medical Internet
research,,22(2), e16866. https://doi.org/10.2196/16866/
Yin, J., Ngiam, K. Y., & Teo, H. H. (2021). Role of artificial intelligence applications in real-life
clinical practice: systematic review.,Journal of medical Internet research,,23(4), e25759.
https://doi.org/10.2196/25759
