AI Chatbots in Digital Mental Health

Abstract

Artificial intelligence (AI) chatbots have gained prominence since 2022. Powered by big data, natural language processing (NLP) and machine learning (ML) algorithms, they offer the potential to expand capabilities, improve productivity and provide guidance and support in various domains. Human–Artificial Intelligence (HAI) is proposed to help with the integration of human values, empathy and ethical considerations into AI in order to address the limitations of AI chatbots and enhance their effectiveness. Mental health is a critical global concern, with a substantial impact on individuals, communities and economies. Digital mental health solutions, leveraging AI and ML, have emerged to address the challenges of access, stigma and cost in mental health care. Despite their potential, ethical and legal implications surrounding these technologies remain uncertain. This narrative literature review explores the potential of AI chatbots to revolutionize digital mental health while emphasizing the need for ethical, responsible and trustworthy AI algorithms. The review is guided by three key research questions: the impact of AI chatbots on technology integration, the balance between benefits and harms, and the mitigation of bias and prejudice in AI applications. Methodologically, the review involves extensive database and search engine searches, utilizing keywords related to AI chatbots and digital mental health. Peer-reviewed journal articles and media sources were purposively selected to address the research questions, resulting in a comprehensive analysis of the current state of knowledge on this evolving topic. In conclusion, AI chatbots hold promise in transforming digital mental health but must navigate complex ethical and practical challenges. The integration of HAI principles, responsible regulation and scoping reviews are crucial to maximizing their benefits while minimizing potential risks. Collaborative approaches and modern educational solutions may enhance responsible use and mitigate biases in AI applications, ensuring a more inclusive and effective digital mental health landscape.

Analysing the Impact of Generative AI in Arts Education: A Cross-Disciplinary Perspective of Educators and Students in Higher Education

“…Professors do point out that in the near future this may change with the development of more sophisticated generative AI applications. As Balcombe [8] points out, the human factors of human-computer interaction require more attention through empirical research. Although AI chatbots are increasingly accessible, they should be seen as complementary tools and not as human substitutes.…”

“…In other words, they are phrases that we use to ask, propose or order the AI what we want to stimulate a response. In this regard, it is necessary to recognise the limitations of AI chatbots, such as poor semantics, biases and the need for qualitative studies to improve the user experience [8].…”

“…In this sense, several authors recommend legal regulation of the process of content creation and distribution of products made with generative AI [8,34].…”

“…AI chatbots (intelligent conversational computer systems that think, learn and complete tasks in combination with humans or independently), considered as generative AI, have become popular since the launch of ChatGPT in November 2022 [8].…”

AI-Enabled Clinical Decision Support Tools for Mental Healthcare: A Product Review

“…While some studies found conversational agents to reliably predict mental disorders (Vaidyam et al, 2020), others caution that they are not yet accurate enough to provide formal diagnoses (Bhattacharyya et al, 2023;Farhat, 2023;Jungmann et al, 2019). In discussions with tool providers, we learned that their tools can support decision-making, but the final diagnosis must come from a qualified mental health professional, further emphasizing the role of conversational agents as complementary tools rather than replacements for human professionals (Balcombe, 2023).…”