The Advantages and Disadvantages of Using Artificial Intelligence in Mental Health Services

被引:0
作者
Gultekin, Mucahit [1 ]
机构
[1] Afyon Kocatepe Univ, Afyon, Turkey
来源
INSAN & TOPLUM-THE JOURNAL OF HUMANITY & SOCIETY | 2022年 / 12卷 / 03期
关键词
Mental health; mental health services; psychological assesment; artificial intelligence; machine learning; DISORDER; ROBOTS; DEPRESSION; FUTURE; PROGRAM; COACH;
D O I
10.12658/M0664
中图分类号
C [社会科学总论];
学科分类号
03 ; 0303 ;
摘要
Today, interdisciplinary development, which is called the fourth technological revolution, continues to be an important topic of discussion. Three previous revolutions in which the steam engine, electricity, and the computer were at the center respectively brought about social changes along with them. Artificial intelligence and machine learning characterize the fourth technology revolution that started in the 21st century. Many experts discuss the possibility that artificial intelligence could directly replace human beings. In this respect, the period we are in is considered to differ from the previous ones. The new technologies emerging with the integration of biology, the Internet, and artificial intelligence are expected to lead to significant changes in the field of mental health as in almost every discipline. The number of studies utilizing artificial intelligence and machine learning in training, diagnosis, prediction, treatment, and evaluation stages of mental health services are gradually increasing. These studies bring along discussions about how artificial intelligence will affect mental health services. Despite the stronger emphasis on the advantages of using artificial intelligence in mental health services, attention is also drawn to its disadvantages and limitations. The aim of this article is to examine the research findings on the use of artificial intelligence and machine learning in mental health services and to discuss the opportunities and problems that artificial intelligence would bring to the field of mental health, and to make suggestions for future research.
引用
收藏
页码:121 / 158
页数:38
相关论文
共 154 条
[1]   Multi-modular AI Approach to Streamline Autism Diagnosis in Young Children [J].
Abbas, Halim ;
Garberson, Ford ;
Liu-Mayo, Stuart ;
Glover, Eric ;
Wall, Dennis P. .
SCIENTIFIC REPORTS, 2020, 10 (01)
[2]  
Ahmed A., 2021, Comput Methods Programs Biomed Update, V1, DOI [DOI 10.1016/J.CMPBUP.2021.100012, 10.1016/j.cmpbup.2021.100012, 10.1016/j.cmpbup.2021]
[3]   The Cognitive Bases of Anthropomorphism: From Relatedness to Empathy [J].
Airenti, Gabriella .
INTERNATIONAL JOURNAL OF SOCIAL ROBOTICS, 2015, 7 (01) :117-127
[4]   Artificial Intelligence and the Future of Psychiatry [J].
Allen, Summer .
IEEE PULSE, 2020, 11 (03) :2-6
[5]  
Altinbasak G., 2019, THESIS USKUDAR U
[6]   Deep learning reveals Alzheimer's disease onset in MCI subjects: Results from an international challenge [J].
Amoroso, Nicola ;
Diacono, Domenico ;
Fanizzi, Annarita ;
La Rocca, Marianna ;
Monaco, Alfonso ;
Lombardi, Angela ;
Guaragnella, Cataldo ;
Bellotti, Roberto ;
Tangaro, Sabina .
JOURNAL OF NEUROSCIENCE METHODS, 2018, 302 :3-9
[7]  
[Anonymous], 2002, P 4 C DES INT SYST P, DOI [DOI 10.1145/778712.778756, DOI 10.1037/0096-1523.30.2.319]
[8]   Predicting Limit-Setting Behavior of Gamblers Using Machine Learning Algorithms: A Real-World Study of Norwegian Gamblers Using Account Data [J].
Auer, Michael ;
Griffiths, Mark D. .
INTERNATIONAL JOURNAL OF MENTAL HEALTH AND ADDICTION, 2022, 20 (02) :771-788
[9]  
Avrupa Komisyonu Yapay Zeka Ust Duzey Uzman Grubu, 2019, EUROPEAN COMMISSION
[10]   Use of a Novel Artificial Intelligence Platform on Mobile Devices to Assess Dosing Compliance in a Phase 2 Clinical Trial in Subjects With Schizophrenia [J].
Bain, Earle E. ;
Shafner, Laura ;
Walling, David P. ;
Othman, Ahmed A. ;
Chuang-Stein, Christy ;
Hinkle, John ;
Hanina, Adam .
JMIR MHEALTH AND UHEALTH, 2017, 5 (02)