Ananya Singh

Purpose This study aims to test whether artists and technologists evaluate artificial intelligence (AI)-generated art differently with respect to authorship, ownership, ethics, public perception and market impact, thereby clarifying how creative and technical stakeholders view emerging copyright and pricing debates. Design/methodology/approach A closed-ended questionnaire using five-point Likert items was administered to 119 master-level artists and 119 AI developers in India. Paired-sample t-tests compared the two groups across six constructs derived from the recent literature. Findings Authorship and market-impact scores did not differ significantly (p = 0.229; p = 0.168). However, large gaps emerged for ownership (Δ = 1.02; t = 15.31; p < 0.001) and public perception (Δ = 1.24; t = 11.25; p < 0.001). Artists favored limited copyright and lower prices for AI art, whereas technologists endorsed full protection and price parity under defined conditions. Both groups supported minimal yet dedicated regulation. Research limitations/implications Findings are based on self-reported perceptions from a single country; cross-cultural replication is needed. Practical implications Results inform policymakers drafting adaptive copyright frameworks and gallery curators setting valuation benchmarks for AI-generated art. Social implications Balanced regulation and weighted authorship could preserve human creativity while legitimizing algorithmic contributions. Originality/value This is the first paired statistical investigation that juxtaposes creative practitioners and AI developers, quantifies their attitudinal distance and links the results to the legal triad of fixation, originality and creativity. The Global South sample broadens a debate dominated by Western case studies.

Expeditious increase in population and industrialization has led to alarming rates of air pollution in all countries. However, developing economies have had to face a more adverse and severe impact. This had led to many changes in the day to day living of citizens. In this paper we have focused on the psychological process and predictors of migration intention of the people living in Hanoi, Vietnam. Two stratified random datasets of 475 people were used, and Bayesian analysis was performed on this dataset. We found out that the intent to move was negatively associated to the individual’s satisfaction with air quality. We also found that people who have family members that have fallen victim to a disease caused by air pollution are more likely to migrate. This paper discusses an important topic: immigration of the younger demographic, i.e. the Hanoi workforce, which may cause restrictions and hurdles in the city's urbanisation and development. The findings suggest that, if measures against air pollution are not taken, economic forces may be disrupted, posing a threat to urban growth. As a result, collaborative activities and steps need to be taken by the government to curb this unfortunate consequence.