AI-Based and Digital Mental Health Apps: Balancing Need and Risk

Hamdoun, Salah; Monteleone, Rebecca; Bookman, Terri; Michael, Katina

doi:10.1109/mts.2023.3241309

Cited by 25 publications

(20 citation statements)

References 35 publications

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“…Through this study, we seek to contribute insights into the potential of AI technology to enhance mental health support services and promote well-being in our society (Hamdoun, S., 2023).…”

Section: Experimentationmentioning

confidence: 99%

RETRACTED: Integration of GPT3 and Dialog GPT Framework in Mental Health Chatbot - A Systematic Literature Research

Nandurkar,

Yuhaniz,

Sahu

2024

Preprint

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While dealing with ongoing health scenarios, researchers take the leap of creativity in AI by engaging Human-AI interaction on the next level. The virtual friend or chatbot, that induced the medical practices not only to diagnose but also, to provide emotional support via., text or voice messages. The research we’ve focused includes this problem statement to analyze and integrate multi-module solutions that’ll be able to outgrow professional as well as amiable (i.e., friendly) behavior concerns and real time database issues. The Dialog Gpt operates with the basic framework of the model, whereas the Da-vinci GPT3 model includes the basic data for medical purposes. The integration of GPT3 and Dialog Gpt results with efficient performance and promising interaction accuracy. The thorough literature review has been carried out on existing solutions for analyzing and avoiding the cons. The concluded model is fused as the backend of a prototype web interface.

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“…Through this study, we seek to contribute insights into the potential of AI technology to enhance mental health support services and promote well-being in our society (Hamdoun, S., 2023).…”

Section: Experimentationmentioning

confidence: 99%

RETRACTED: Integration of GPT3 and Dialog GPT Framework in Mental Health Chatbot - A Systematic Literature Research

Nandurkar,

Yuhaniz,

Sahu

2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Among these search inquiries, mental health issues have been growing (WHO 2022). To counter this expanding need, digital mental health solutions, including AI chatbots, are on the rise (Hamdoun et al 2023) and consequently the emotional comprehension capabilities of GAI are gaining attention (Uludag 2023). Assuming users' data privacy is safeguarded, encrypted GAI chatbots can serve as confidants, allowing individuals to share their emotions, or psychological symptoms, and feel heard (Eshghi 2023).…”

Section: Case Study #2 | Healthcare (Ai-powered Therapies)mentioning

confidence: 99%

The GenAI is out of the bottle: generative artificial intelligence from a business model innovation perspective

Kanbach,

Heiduk,

Blueher

et al. 2023

Rev Manag Sci

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The introduction of ChatGPT in November 2022 by OpenAI has stimulated substantial discourse on the implementation of artificial intelligence (AI) in various domains such as academia, business, and society at large. Although AI has been utilized in numerous areas for several years, the emergence of generative AI (GAI) applications such as ChatGPT, Jasper, or DALL-E are considered a breakthrough for the acceleration of AI technology due to their ease of use, intuitive interface, and performance. With GAI, it is possible to create a variety of content such as texts, images, audio, code, and even videos. This creates a variety of implications for businesses requiring a deeper examination, including an influence on business model innovation (BMI). Therefore, this study provides a BMI perspective on GAI with two primary contributions: (1) The development of six comprehensive propositions outlining the impact of GAI on businesses, and (2) the discussion of three industry examples, specifically software engineering, healthcare, and financial services. This study employs a qualitative content analysis using a scoping review methodology, drawing from a wide-ranging sample of 513 data points. These include academic publications, company reports, and public information such as press releases, news articles, interviews, and podcasts. The study thus contributes to the growing academic discourse in management research concerning AI's potential impact and offers practical insights into how to utilize this technology to develop new or improve existing business models.

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“…Partnerships will be central to this endeavor, looking specifically beyond the walls of academia [26]. In doing so, there is a requirement for investing in people, not just the AIbased technologies and solutions, while compelling multiple stakeholders to contribute to the ethical and just design and development of AI, in contexts such as digital mental health services [30], and others. To achieve this, a preliminary step proposed in this Editorial is dissolving disciplinary boundaries, looking to disciplines such as psychology, and indeed social psychology, for an enhanced understanding of the "human".…”

Section: Interdisciplinarity and Multi-stakeholder Participationmentioning

confidence: 99%

Designing AI Using a Human-Centered Approach: Explainability and Accuracy Toward Trustworthiness

Schoenherr

Michael

Rivas

et al. 2023

IEEE Trans. Technol. Soc.

Self Cite

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One of the major criticisms of Artificial Intelligence is its lack of explainability. A claim is made by many critics that without knowing how an AI may derive a result or come to a given conclusion, it is impossible to trust in its outcomes. This problem is especially concerning when AI-based systems and applications fail to perform their tasks successfully. In this Special Issue Editorial, we focus on two main areas, explainable AI (XAI) and accuracy, and how both dimensions are critical to building trustworthy systems. We review prominent XAI design themes, leading to a reframing of the design and development effort that highlights the significance of the human, thereby demonstrating the importance of human-centered AI (HCAI). The HCAI approach advocates for a range of deliberate design-related decisions, such as those pertaining to multi-stakeholder engagement and the dissolving of disciplinary boundaries. This enables the consideration and integration of deep interdisciplinary knowledge, as evidenced in our example of social cognitive approaches to AI design. This Editorial then presents a discussion on ways forward, underscoring the value of a balanced approach to assessing the opportunities, risks and responsibilities associated with AI design. We conclude by presenting papers in the Special Issue and their contribution, pointing to future research endeavors.

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AI-Based and Digital Mental Health Apps: Balancing Need and Risk

Cited by 25 publications

References 35 publications

RETRACTED: Integration of GPT3 and Dialog GPT Framework in Mental Health Chatbot - A Systematic Literature Research

RETRACTED: Integration of GPT3 and Dialog GPT Framework in Mental Health Chatbot - A Systematic Literature Research

The GenAI is out of the bottle: generative artificial intelligence from a business model innovation perspective

Designing AI Using a Human-Centered Approach: Explainability and Accuracy Toward Trustworthiness

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