Overview
Annotated Reference Assignment
The references (and related journal articles) will be due the day before the third class session (June 17, 2024). They can be sent to the instructor via Canvas.
This assignment will to familiarize students with issues related to ethical dilemmas in society. Student will locate, review, and evaluate 2 scholarly peer-reviewed journal articles in this area of interest. The articles must have been published in the past (5) five years, and must be from peer-reviewed journals. You should use these articles as a part of your references for your final Ethical Analysis Review Paper. You should include:
- a summary - a brief description of the essential points made, the scope of the discussion, and the point of view of the author.
- a critique - your reflections on the significance, strengths, and weaknesses of the article.
List your sources using standard APA bibliographic form, with the annotation immediately following each citation. You are expected to provide the instructor copies of the two articles- this should be submitted through Canvas.
Annotation Example (permission obtained to share this example from a former student):
Article: Graham, S., Depp, C., Lee, E. E., Nebeker, C., Tu, X., Kim, H.-C., & Jeste, D. V. (2019). Artificial Intelligence for Mental Health and Mental illnesses: An overview. Current Psychiatry In The Digital Age Reports, 21(11). https://doi.org/10.1007/s11920-019-1094-0链接到外部网站。
Summary: The article focuses on the benefits and potential pitfalls of applying artificial intelligence (AI) in mental health care. By reviewing 28 studies, the authors discovered that utilizing machine learning algorithms to classify mental illnesses could be applicable in the near future. The authors eventually hope that AI technology will be able to assist practitioners to define mental illnesses more objectively than they are written in the DSM-5, tailor treatments towards each individual, and identify mental illnesses at an earlier stage than usual. Specifically, they assert that AI algorithms can be used to enable a better understanding of population-level patterns of mental illnesses as well as provide more intelligent assessments to examine the severity of mental illness. However, they also note that there may be ethical challenges associated with the implementation of AI, such as biased data and the linking of mental illnesses to specific ethnicities. The authors encourage the integration of ethical principles to guide AI research, such as autonomy, beneficence, and justice. Finally, the authors conclude that the future of artificial intelligence in mental health care is promising, and collaboration with stakeholders such as data scientists and other experts is key to integrating such innovation into improved care for patients.
Critique: The article strongly notes the potential benefits of applying artificial intelligence technology to mental health care, while also acknowledging the potential ethical dilemmas that can occur. However, the authors could do more to expand the myriad of potential ethical issues that can develop. For instance, the article briefly cites how AI technologies can link mental illnesses to certain ethnicities but doesn’t investigate further the implications of a hypothetical outcome on both patients and clinicians alike. The authors could have done more to expand upon other different populations and socioeconomic backgrounds that could be adversely affected by AI. Further, the authors do not explore the issues of informed consent among patients to have their data used, as well as any potential data privacy implications in the use of AI technology in mental health care. Providing additional context on the potential pitfalls of data privacy with AI and the unintended potential uses of personal information could be helpful in providing a broader view of the ethical conundrums surrounding AI in mental health.