About this Research Topic
It has become essential to understand the potential downsides of AI. Privacy violations, the spread of fake news, algorithmic bias caused by bad data, and socioeconomic inequality have been mentioned as some of the biggest drawbacks. Clear policies are needed in order to identify harmful health misinformation on online platforms, as well as consistent approaches in dealing with it.
AI-focused research and development offers opportunities to avoid serious and potentially existential harms. Furthermore, relevant regulation of the development and use of artificial intelligence is essential in order to avoid harm.
The purpose of this Research Topic is to take a closer look at the possible well-being related risks of artificial intelligence in everyday life on people of all ages and explore how to manage these risks. Given that AI is becoming more prevalent every day among families and educators who know neither the scope nor the extent of this challenge, we hope that this Research Topic will shed light on the current situation.
We welcome contributions that focus on the mechanisms by which AI has an impact on everyday life and well-being, and the implications for individuals.
Specific themes include, but are not limited to, the following:
1. The etiology of well-being related problems/downsides concerning the different AI activities among people of all ages.
2. The well-being related consequences connected to AI use/activity.
3. Prevention, harm-reduction strategies, and intervention connected to potential AI related downsides.
4. The assessment of AI involvement and its related impacts.
Keywords: artificial intelligence, developmental and psychosocial effects studies, qualitative studies, cross-sectional studies, cross-cultural studies, longitudinal studies
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.