Analysis of the Obstacles to Ethical Use of Artificial Intelligence
Given the expansion of numerous applications of artificial intelligence in the daily activities of human societies and the ethical obstacles that may arise in this direction, the need for a detailed and comprehensive examination of these issues is felt more than ever. Therefore, this study was developed with the aim of examining the challenges of ethical use of artificial intelligence technology.
This study is applied in terms of purpose and descriptive-survey in terms of data collection. Library methods, searching through electronic sources, and field study were used to collect data. In the field method, a questionnaire was used. The research community is experts and specialists in the field of artificial intelligence, 15 of whom were selected through purposive sampling (snowball sampling). By reviewing the literature, 6 obstacles related to the ethical use of artificial intelligence were identified; the DEMATEL method and Excel and MATLAB software were used to analyze the data and evaluate the cause-and-effect relationships between the obstacles.
The results show that among the 6 identified barriers (lack of accountability, lack of transparency, lack of legal regulations, possibility of bias and discrimination, violation of data privacy, and violation of social justice and livelihood of individuals), the barrier of lack of transparency, followed by the lack of legal regulations, are considered to be the most important and influential barriers to the ethical use of AI. Also, the barriers of data privacy violation and violation of social justice and livelihood of individuals were identified as the most influential barriers among the aforementioned barriers.
The findings of this study indicate the importance and causal relationships governing the existing barriers to the ethical use of AI and can help experts and managers in this field in designing AI systems and making decisions in order to comply with ethical principles.
-
Determining the efficiency of decision-making units using the technique of data envelopment analysis in the presence of dual-role performance factors
Esmaeil Keshavarz *, , Ali Fallah Tafti
Journal of Industrial Management Studies, -
Designing a causal model of the antecedents of disruptive innovation in the field of medical services
Atefeh Khayatzadeh, *, Salim Karimi Taklu
Journal of Technology Development Management,