human – Intercultural perspectives on information literacy and Metaliteracy (IPILM)

11. January 2026 / Neele Baumgart

Conference Session Report: 7th IPILM-Conference on 11.12.2025

Original illustration, AI-generated with ChatGPT (OpenAI).

What happens when artificial intelligence becomes part of mental health care, and how should we deal with its risks and responsibilities?

Key Focus of the Session

AI as a support tool in mental health
Benefits: Early detection, accessibility, continuous support
Risks: Data protection, bias, transparency
Cultural and social contexts shaping perceptions, use, and risks of AI
Importance of information literacy and meta literacy

Building on these focal points, the Session examined the potential and limitations of artificial intelligence in the field of mental health from an information literacy and metaliteracy perspective. Drawing on a systematic literature review and concept mapping, it showed that AI-based applications can offer advantages, particularly with regard to early detection, continuous support, and low-threshold accessibility.
These findings were largely consistent across the reviewed literature and were primarily informed by two key studies that shaped the session.
Scientific evidence on the effectiveness and acceptance of AI-based mental health applications was mainly drawn from Dehbozorgi et al. (2025 – Read More).
In contrast, ethical, cultural, and epistemic risks, such as data protection concerns, algorithmic bias, and limited transparency, were largely informed by the ethical review of Saeidnia et al. (2024 – Read more).
The international survey largely reflected and reinforced the risks discussed in these studies, while also illustrating how these issues are perceived in practice. Overall, the findings emphasized that AI in mental health contexts should primarily be understood as a complementary tool to human expertise and that well-developed information literacy and metaliteracy are essential for responsible use.

❗️Below are a few selected examples of mental health services that incorporate AI-based support tools.

Therapeak; VIA HealthTech; Wysa & Woebot

The examples illustrate current applications of AI in mental health and are not intended as recommendations.

Cultural and Ethical Considerations

Mental health is deeply shaped by cultural norms, social stigma, and structural inequalities, an aspect that was central to the intercultural perspective of the session and the conference as a whole.
These factors also influence how AI-based systems are developed and used. AI applications risk reinforcing existing disparities through biased data, data poverty, and predominantly Western-centered models of mental health. Ethical challenges such as privacy, autonomy, and emotional adequacy are therefore particularly intensified for vulnerable and marginalized groups, highlighting the need for culturally sensitive and ethically grounded AI design.

Discussion

The discussion focused in particular on questions of responsibility. A majority of participants attributed responsibility for potentially harmful or misleading AI-based advice primarily to the providing companies, indicating a strong demand for institutional safeguards while simultaneously raising questions about the role of user responsibility. From an information literacy and metaliteracy perspective, this highlights the importance of enabling users to critically assess AI-based systems, understand their limitations, and recognize potential risks.
At the same time, individual awareness alone cannot replace structural responsibility, especially in light of asymmetrical power and knowledge relations between providers and users, as well as the vulnerability of mental health contexts.

Another key point concerned the ambivalent level of trust in AI within mental health applications. Although many participants expressed general openness toward the use of AI, trust remained limited due to concerns about data protection, reliability, and the quality of AI-generated advice. Increasing trust was found to depend on transparent system design, strong data protection measures, explainable decision-making processes, and the clear integration of AI into human-supported care structures.
Overall, the discussion suggests that trust in AI is shaped less by technological performance alone than by ethical design, cultural sensitivity, and informed and reflective practices of use.

Key Takeaways

AI can meaningfully support mental health care, but its value depends on ethical design, cultural sensitivity, and human oversight.
Users tend to view AI as a supportive tool rather than a replacement for professional care, while concerns about privacy and trust remain strong.
Cultural context plays a significant role in shaping how AI-based mental health services are perceived and used.
Strong information literacy and metaliteracy are essential for enabling critical, informed, and responsible engagement with AI in mental health contexts.

Our Screencast

The Screencast summarizing our session and key findings is available on YouTube:
🎬 Watch the Screencast on YouTube

Key Takeaways

AI can provide emotional comfort and a sense of social presence.
Users often perceive AI as non-judgmental and constantly available.
Emotional attachment to AI is possible, but true reciprocity is missing.
AI tends to replace functional roles rather than deep emotional relationships.
AI complements human relationships but does not replace them.

AI-generated image created using ChatGPT (DALL·E), 2026.

Introduction

This session aimed to provide an initial overview of the question of whether artificial intelligence can function as a substitute for human relationships. With AI tools increasingly used not only for information retrieval but also for emotional and social interaction, this topic has gained growing relevance in both academic research and everyday life.

The presentation combined a theoretical perspective, based on key findings from current scientific literature, with a practical approach. While the theoretical part outlined how human–AI relationships are conceptualized and evaluated in research, the practical component presented an exploratory survey to illustrate a possible research approach and to identify early tendencies in user experiences.

Summary

The presentation focused on two key academic studies and an exploratory survey to examine how AI may take on social and emotional roles traditionally associated with human relationships. The presented studies are: Brandtzaeg et al. (2022) showed that users candevelop friend-like attachments to social chatbots, perceiving them as safe and non-judgmental, while emphasizing the lack of reciprocity and emotional depth. Smith et al. (2025) further highlighted that although generative AI can convincingly simulate emotional responsiveness, it lacks key psychological components of genuine human connection, such as mutuality, shared experience, and emotional depth, which limits its ability to fully replicate human relationships.
In addition, an exploratory online survey was conducted to demonstrate a possible
research approach and to identify initial tendencies, such as emotional comfort,
functional role substitution, and perceived non-judgment. Further details on the survey design, sample characteristics, and key findings are presented in the screencast linked below.

Discussion: Questions, Answers, and Reflections

During the discussion, a few questions focused on the methodology of the survey and the validity of its results. Participants critically addressed the small and non-representative sample. In response, it was emphasized that the survey was intended as an exploratory approach rather than a source of generalizable conclusions. Its purpose was to illustrate how human–AI relationships can be empirically examined and to reveal early tendencies that may guide future research. These included the frequent use of AI for emotional comfort, the perception of AI as less judgmental than humans, and the limited replacement of human roles.

Another discussion point concerned whether and how emotionally responsive AI systems should be regulated. It was debated whether emotional support provided by AI should be restricted and, if so, how “too emotional” AI could be defined. While arguments for regulation often focus on preventing emotional dependence, potential benefits are also emphasized, particularly AI’s role as a low-threshold form of support for individuals experiencing loneliness or social anxiety.

Finally, the discussion addressed broader opportunities and risks. Opportunities
included availability, emotional relief, and reduced social pressure, whereas risks
centered on privacy concerns, emotional dependence, and the potential weakening of real-life social relationships. Overall, the discussion underscored the need for continued critical reflection and interdisciplinary research on emotional AI.

Screencast

Below you can find the screencast of our presentation “AI as a Substitute for Human Relationships”, which summarizes the theoretical background and the practical insights discussed during the session.

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https://www.youtube.com/watch?v=pq3S09PA0Tk

Tag: human

AI and Mental Health

Key Focus of the Session

Cultural and Ethical Considerations

Discussion

Key Takeaways

Our Screencast

Further Reading

AI as a Substitute for Human Relationships

Key Takeaways

Introduction

Summary

Discussion: Questions, Answers, and Reflections

Screencast

Further Reading & Resources

Address and contact

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Links

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