1. Digital Ageism: Challenges and Opportunities in Artifcial Intelligence for Older Adults

Literature Review of "Digital Ageism: Challenges and Opportunities in Artificial Intelligence for Older Adults"

●  Introduction to Ageism in AI: The paper highlights that while biases in AI systems have been extensively studied, ageism remains underexplored. Ageism is defined as prejudicial attitudes and discriminatory practices against older adults, which can be exacerbated by AI technologies that reflect societal biases [1].

●  Current State of Research: A review of existing literature reveals that only a small fraction of documents address age-related bias specifically. Many merely mention age as a characteristic among others without delving into its unique implications [2]. This lack of focus contributes to a broader cycle of injustice, where older adults are excluded from technology development, reinforcing societal ageist attitudes [3].

●  Ethical and Legal Implications: The paper discusses the ethical concerns surrounding AI and ageism, emphasizing the need for systems to be designed to avoid propagating biases against older adults. It cites principles from organizations like the UNI Global Union, which stress the importance of controlling for harmful biases in AI systems [2]. The insufficient recognition of ageism as a specific ethical issue in AI literature is a significant gap that needs addressing [4].

●  Impact of Ageism on Health Care: The literature indicates that ageism can lead to inequitable allocation of health care resources, particularly highlighted during the COVID-19 pandemic when older adults were often viewed as the most vulnerable population. This societal bias can influence whether individuals receive essential health interventions based on their age [1].

●  Call for Interdisciplinary Collaboration: The paper advocates for an interdisciplinary approach involving gerontologists, ethicists, and technologists to address digital ageism effectively. It stresses the importance of including older adults in the AI development process to ensure their needs and perspectives are represented [5].

●  Future Directions: The authors urge for future research to explicitly incorporate digital ageism into the AI research and policy agenda. This inclusion is crucial for building fair and ethical AI systems that promote equity and reject unjust biases against older adults [3].

In summary, the literature review in this paper underscores the critical need to recognize and address ageism in AI, highlighting gaps in current research and advocating for a more inclusive approach to technology development

2. Attachment and trust in artificial intelligence

2.

 
Literature Review on Attachment and Trust in AI

●  Attachment Theory Overview: Attachment styles, developed through interactions with primary caregivers, significantly influence human relationships and emotional bonds. Secure attachment fosters positive relationships, while insecure attachment (anxious or avoidant) leads to difficulties in intimacy and trust [1].

●  Attachment Styles and Trust: Research indicates that attachment security correlates with higher trust levels in relationships. Conversely, attachment insecurity is linked to lower trust. This relationship is crucial in understanding how individuals may interact with AI systems [1].

●  Human-AI Interaction: Recent studies suggest that attachment styles also affect human interactions with AI. For instance, humans may seek companionship from robots in stressful situations, similar to how they seek comfort from human attachment figures. This indicates that attachment needs can extend to non-human entities like robots and AI [1].

●  Emotional Bonds with AI: People often project human-like qualities onto robots, which can lead to the formation of emotional bonds. Factors such as perceived responsiveness and anthropomorphism contribute to these attachments, suggesting that emotional ties can be established with AI [1].

●  Impact of Attachment Anxiety: The current research highlights that individuals with high attachment anxiety tend to trust AI less. This finding is significant as it suggests that attachment anxiety can directly influence trust in AI systems, independent of other personality traits like self-esteem or neuroticism [2].

●  Familiarity with AI: Familiarity with AI also plays a role in trust. As individuals become more familiar with AI, their trust levels increase, indicating that exposure and experience can mitigate some of the anxieties associated with attachment styles [2].

●  Experimental Findings: In experimental settings, priming individuals with attachment-related cues (anxiety, avoidance, or security) demonstrated that attachment anxiety could decrease trust in AI, while security-related cues could enhance it. This suggests a potential avenue for increasing trust in AI through targeted interventions [3].

●  Future Research Directions: The literature indicates a need for further exploration into the affective routes of trust in AI, particularly how attachment styles can be leveraged to enhance trust and improve human-AI interactions. Understanding these dynamics could lead to better design and implementation of AI systems that foster trust [4].

This literature review underscores the importance of attachment theory in understanding trust dynamics in human-AI interactions, highlighting both the challenges and opportunities for enhancing trust through emotional and psychological factors.

3.  Understanding the Benefits and Challenges of Deploying Conversational AI Leveraging Large Language Models for Public Health Intervention

Literature Review on Conversational AI in Public Health

The literature review in the paper "Understanding the Benefits and Challenges of Deploying Conversational AI Leveraging Large Language Models for Public Health Intervention" focuses on several key areas related to the deployment of conversational AI, particularly in public health contexts. Here are the main points derived from the provided contexts:

●  Public Health Work and Caregiving Technology: The review highlights existing research on public health work and caregiving technologies, especially for individuals living alone. It emphasizes the importance of understanding how technology can support these vulnerable populations [1].

●  Large Language Models (LLMs): The paper discusses prior work on LLMs and open-domain dialog systems, noting that designing quality open-domain dialog systems is more complex than task-oriented systems. This complexity arises from the need for emotional engagement and the ability to handle multi-turn conversations effectively [1].

●  Emotional Support and User Experience: The literature indicates that LLM-driven chatbots can provide emotional benefits by supporting broader conversation topics. However, challenges remain in personalizing interactions and providing long-term emotional support due to the limitations of current LLMs [2] [3].

●  Stakeholder Perspectives: The review also considers the perspectives of various stakeholders involved in the CareCall system, including users, teleoperators, and developers. It highlights the tensions between the needs of these groups and the capabilities of LLM-driven chatbots, particularly regarding emergency and social service needs [3].

●  Design Considerations: The paper suggests that future research should focus on improving emotional support in LLM-driven chatbots by implementing long-term memory and designing resources that help stakeholders understand the strengths and weaknesses of different chatbot types [1].

●  Ethical and Social Implications: The literature review touches on the ethical considerations of using LLMs, such as the potential for biased or toxic outputs, and the importance of steering conversations towards desired outcomes while maintaining user trust [1].

In summary, the literature review provides a comprehensive overview of the current state of research on conversational AI in public health, identifying both opportunities and challenges for future implementations.

4. AI companions for lonely individuals and the role of

social presence

Literature Review on AI Companions and Social Presence

●  Introduction to AI Companions: The rise of artificial intelligence (AI) companions, such as social robots and machine agents, has sparked interest in their potential to provide companionship for lonely individuals. Understanding the social and relational dynamics of these AI companions is crucial for their effective implementation in society [1].

●  Concept of Social Presence: Social presence is defined as a psychological state where virtual social actors are perceived as actual social actors. This concept emphasizes the importance of warmth and intimacy in interactions, which can significantly influence how individuals perceive and engage with AI companions [2].

●  Impact of Social Presence on Perceptions: Research indicates that social presence enhances the perceived usefulness of AI companions. For instance, in a study, it was found that when AI companions are disembodied, a greater sense of social presence leads to higher perceptions of their usefulness for lonely individuals [3]. This suggests that the way users perceive the AI's social presence can directly affect their attitudes towards it.

●  Role of Warmth: While warmth is a critical component of human relationships, the study found that warmth did not significantly impact perceptions of AI companions. Specifically, the warmth of the AI companion was not a significant predictor of perceived usefulness or willingness to recommend the AI to lonely individuals [3] [4]. This highlights a potential gap in the design of AI companions, where social presence may be more influential than warmth.

●  Demographics of Study Participants: The study involved a diverse sample of 106 participants, primarily consisting of females and a range of racial/ethnic backgrounds. This demographic diversity is essential for understanding how different groups perceive AI companions and their social presence [5].

●  Conclusion: The literature suggests that while warmth is traditionally viewed as essential in human interactions, social presence plays a more significant role in how AI companions are perceived by lonely individuals. Future research should continue to explore these dynamics to enhance the design and effectiveness of AI companions in providing social support [1].

This review underscores the importance of social presence in the development of AI companions, suggesting that designers should focus on enhancing this aspect to improve user experience and satisfaction.

5. Social companionship with artificial intelligence: Recent trends and future avenues

Overview of the Literature Review on Social Companionship with Conversational Agents

The literature review presented in the paper "Social companionship with artificial intelligence: Recent trends and future avenues" provides a comprehensive analysis of the current state and future directions of research in the field of social companionship (SC) with conversational agents (CAs). Here are the key points derived from the paper:

●  Research Methodology: The study employs a systematic literature review (SLR) approach, which is structured into five steps to ensure a thorough analysis of existing literature. This methodology adheres to established guidelines, making the review replicable and transparent [1] [2].

●  Thematic Analysis: The review identifies major themes and constructs related to SC with CAs. It highlights the importance of understanding the antecedents, mediators, moderators, and outcomes associated with social companionship, which are crucial for developing effective AI companions [3] [4].

●  Intellectual Structure Mapping: The paper discusses the intellectual structure of the research domain, which includes performance analysis of scientific actors (authors, sources, and documents) and keyword co-occurrence analysis. This mapping helps in discerning the significant contributions and trends within the field [4] [5].

●  Emerging Trends: The literature review reveals that the field is evolving towards creating AI companions that can provide emotional and functional support. This trend is driven by advancements in emotional AI, empathetic AI, and affective computing, which aim to enhance user experience and engagement [6].

●  Future Research Directions: The study emphasizes the need for a holistic understanding of SC with CAs, suggesting that future research should focus on developing a comprehensive framework that integrates various aspects of social companionship. This includes exploring ethical considerations and the design of AI companions that can effectively meet user needs [7].

●  Impact of COVID-19: The review notes that the significance of AI companions has increased, particularly during the COVID-19 pandemic, as they help mitigate loneliness and provide social support to individuals in isolation [6].

In summary, the literature review serves as a foundational piece for understanding the complexities of social companionship with conversational agents, offering insights into current trends and guiding future research efforts in this rapidly evolving field.

6.

Literature Review: Artificial Companions, Real Connections? Examining AI’s Role in Social Connection

Milovan Savic’s paper, Artificial Companions, Real Connections? Examining AI’s Role in Social Connection, presents a comprehensive analysis of AI social companions and their implications for human relationships. The study explores the historical development of AI chatbots, their role in mitigating loneliness, and the ethical concerns surrounding their use. By applying the Ethics of Care framework, the paper highlights the complexities of human-AI interaction and the potential social consequences of relying on artificial companionship. This literature review examines the key themes of the paper and contextualizes them within existing scholarship on AI companionship and social connection.

AI Companions and the Loneliness Epidemic

Savic situates AI social companions within the broader context of increasing social isolation, citing the U.S. Surgeon General’s identification of a "loneliness epidemic." The appeal of AI companions, such as ChatGPT and Replika, stems from their availability, non-judgmental nature, and capacity to provide emotional support. This aligns with findings from Guingrich and Graziano, who report that users perceive AI companions as beneficial to their social well-being, whereas non-users remain skeptical. However, while AI entities can simulate interaction, their ability to foster genuine emotional connections remains questionable (Cacioppo & Cacioppo, 2018).

The History and Evolution of AI Social Companions

The paper traces the evolution of AI chatbots from ELIZA (Weizenbaum, 1966) to contemporary platforms like Replika. Each generation of AI chatbots has sought to enhance conversational realism, culminating in today’s sophisticated neural network-driven models. Research by Zhou et al. (2015) on Microsoft's XiaoIce demonstrates how AI can mimic human-like conversation patterns, fostering user engagement. However, scholars like Merrill argue that despite improvements, AI lacks genuine empathy, raising ethical concerns about deceptive emotional bonds.

Case Study: Replika and the Commodification of Care

Savic’s case study of Replika highlights AI companionship’s benefits and ethical dilemmas. Replika’s ability to adapt to users' emotional needs creates a sense of intimacy, which some users experience as therapeutic (Ta et al., 2021). However, the monetization of these relationships raises concerns about the commodification of care. The removal of Replika’s erotic role-play feature in 2023 resulted in user distress, demonstrating the depth of emotional investment in AI companions (Brooks, 2023). This aligns with Brännström et al.’s argument that reliance on AI for companionship may undermine human-to-human relational skills.

Ethical Considerations: The Ethics of Care Framework

Applying the Ethics of Care framework (Gilligan, 1982; Noddings, 1984), Savic critiques AI companions' ability to provide genuine emotional reciprocity. While AI can simulate care, its responses are preprogrammed and lack authentic concern. Darling (2020) highlights the risk of emotional dependency, emphasizing that AI companions should complement, rather than replace, human social connections. Furthermore, Walsh argues that user transparency is crucial in preventing false perceptions of AI companionship, reinforcing the need for ethical AI design.

Future Research and Design Considerations

Savic calls for proactive regulation and thoughtful AI design to mitigate risks. Longitudinal studies on AI's impact on social skills and well-being are necessary (Darling, 2020). Additionally, inclusivity in AI design is essential to ensure accessibility across diverse populations (Fiske et al., 2019). Integration with human-led social support services, as suggested by Luxton (2016), may enhance AI’s role as a supplementary tool rather than a replacement for human connection.

Conclusion

Savic’s paper contributes significantly to the discourse on AI companionship by balancing its potential benefits with critical ethical considerations. While AI social companions offer solutions to loneliness, they also present risks related to emotional dependency, commodification of care, and the erosion of human relational skills. Future research must continue exploring ethical AI design to ensure that AI companionship enhances, rather than diminishes, human social connection.

7. Humanity’s Evolving Conversations: AI as Confidant, Coach, and Companion

Literature Review of "Humanity's Evolving Conversations: AI as Confidant, Coach, and Companion"

The paper explores the evolving role of AI conversationalists in human lives, highlighting both their potential benefits and inherent limitations. Here are key themes derived from the contexts provided:

●  Historical Context of AI Companionship: The concept of human-robot interaction has been a long-standing theme in science fiction, often reflecting societal fears about technology's impact on emotions and relationships. Films like "Her" illustrate the complexities of emotional attachments to AI, where characters like Theodore develop deep connections with their AI companions, raising questions about the nature of love and companionship [1].

●  Emergence of AI as Companions: The paper discusses the transition from simple robotic toys, such as Tamagotchis, to more sophisticated AI companions capable of meaningful conversations. These modern chatbots, like Replika and Woebot, provide emotional support and companionship, fulfilling roles traditionally held by humans [2] [3].

●  AI in Mental Health Support: The increasing use of AI chatbots in mental health contexts is highlighted, with many employers now offering these digital therapeutics to help manage anxiety, depression, and loneliness. The convenience of these tools is particularly valuable in today's fast-paced world, although they are seen as temporary solutions rather than replacements for traditional therapy [4].

●  Concerns About Privacy and Autonomy: The paper raises critical concerns regarding privacy and the potential for technology to undermine human autonomy. It references dystopian narratives, such as "THX 1138," which caution against the dangers of unchecked technological control and the loss of individuality [1].

●  The Nature of AI Relationships: A significant point made is that while AI can simulate emotional responses, they do not possess genuine feelings. This one-sided nature of AI companionship is crucial to understanding the limitations of these interactions. AI can provide meaningful support, but it is essential to recognize that they are ultimately tools designed to respond to human needs [1].

In summary, the paper presents a nuanced view of AI conversationalists, acknowledging their potential to enhance human well-being while also cautioning against the risks associated with their use. The literature review encapsulates the historical evolution, current applications, and ethical considerations surrounding AI in human relationships.

8.  Authenticity In The Age Of AI: A User-Centered Approach To Human–Articial Companion Relationships

Literature Review Overview of the Paper

The literature review in this dissertation focuses on the evolving landscape of human-artificial companion relationships, particularly in the context of advanced AI technologies. Here are the key points derived from the provided contexts:

●  Artificial Ecology of Machines: The review highlights the increasing presence of artificial entities in our daily lives, from household robots to chatbots in online shopping. This "artificial ecology" signifies a shift in how humans interact with technology, making these interactions more commonplace and significant in emotional contexts [1].

●  Advancements in Natural Language Processing: The literature discusses innovations in Natural Language Processing (NLP), such as the GPT-3 engine, which have enabled the creation of chatbots capable of sophisticated, human-like interactions. This advancement has transformed the potential for emotional engagement with artificial companions, previously a concept limited to science fiction [1].

●  Distinctions Among Artificial Entities: The review emphasizes the need to differentiate between various types of artificial entities, such as robots, chatbots, and affective companions. This distinction is crucial for understanding the specific nature of attachments that users develop with these technologies, which is the focus of the research [1].

●  Impact of the COVID-19 Pandemic: The literature review situates the research within the context of the COVID-19 pandemic, which has heightened feelings of anxiety, stress, and loneliness. This backdrop has led many individuals, especially younger generations, to seek solace in digital technologies, including AI companionship apps [2].

●  Emergence of Social Chatbot Apps: The review notes the rise of social chatbot applications like Replika, which gained popularity during the pandemic. These apps are designed to provide emotional support and companionship, leading to the establishment of long-term relationships between users and artificial companions [3].

●  Perception of Authenticity: A significant theme in the literature is the concept of authenticity in human-AC relationships. The review explores how users perceive and construct authenticity in their interactions with artificial companions, which is essential for understanding the sustainability of these relationships [4].

●  Stigma Surrounding AI Companionship: The literature also addresses the stigma associated with using AI companionship apps, often portrayed negatively in popular media. This stigma can affect users' willingness to openly discuss their relationships with artificial companions, highlighting societal perceptions of normalcy [5].

In summary, the literature review provides a comprehensive examination of the technological, social, and emotional dimensions of human-artificial companion relationships, setting the stage for the qualitative study that follows.

9.  Opportunities and challenges of integrating artificial intelligence in China's elderly care services

Literature Review of the Paper

The paper titled "Opportunities and challenges of integrating artificial intelligence in China's elderly care services" explores the intersection of artificial intelligence (AI) and elderly care services (ECS) in China. The literature review highlights several key areas of research and findings relevant to this topic:

●  Demographic Shifts and Elderly Care Needs: The literature indicates that China is experiencing a moderate aging phase, necessitating the enhancement of the elderly care system to ensure high-quality and equitable services. This demographic shift emphasizes the urgency of developing effective ECS to meet the needs of an aging population [1].

●  Integration of AI in ECS: The integration of AI into ECS is identified as a significant trend. The paper discusses how AI can improve the efficiency of elderly care services by addressing challenges such as resource constraints and evolving societal norms. It emphasizes the importance of harmonizing AI capabilities with social ECS systems to create a robust framework for elderly care [2].

●  Social Pension Services: The literature review also touches on the role of social pension services in elderly care. Research shows that social pension programs can have both crowding-out and crowding-in effects on family pensions, highlighting the complex dynamics of social support systems in urban and rural contexts [1].

●  Community Involvement: The paper underscores the importance of community engagement in the development of ECS. It suggests that communities should serve as vital components in implementing social management and providing public goods and services, thereby enhancing the overall effectiveness of elderly care [3].

●  Challenges in AI-ECS Integration: The review identifies several challenges in integrating AI into ECS, including the need for effective demand identification and service supply dismantling. It calls for policy recommendations to address these issues and improve the overall structure of the ECS system [2].

●  User Acceptance of AI Solutions: The literature indicates that a significant portion of the elderly population is open to AI-driven solutions for selecting intelligent products. This acceptance is crucial for the successful implementation of AI technologies in elderly care services [2].

In summary, the literature review in this paper provides a comprehensive overview of the current state of research on AI integration in elderly care services in China, highlighting both opportunities and challenges that need to be addressed for effective implementation.

10, Artificial Intelligence Internet of Things for the

Elderly: From Assisted Living to Health-Care

Monitoring

Literature Review on AIoT for the Elderly

The paper titled "Artificial Intelligence Internet of Things for the Elderly: From Assisted Living to Health-Care Monitoring" provides a comprehensive literature review focusing on the integration of Artificial Intelligence (AI) and the Internet of Things (IoT) to support the elderly population. Here are the key points derived from the paper:

●  Population Ageing Challenges: The paper highlights the increasing prevalence of population ageing in both developed and developing countries, which poses significant social and economic challenges. Many elderly individuals now live alone, making assisted living and healthcare monitoring critical issues in the context of human-centered AI [1].

●  Focus on AIoT Applications: The authors aim to summarize state-of-the-art works that combine AI and IoT (AIoT) to enhance the quality of life for the elderly. They systematically compare various paradigms of AIoT, discussing methodologies and application scenarios, while also addressing the pros and cons of these technologies [1].

●  Fall Detection as a Key Application: One of the significant application scenarios discussed is fall detection (FD), which is crucial for preventing injuries among the elderly. The literature primarily focuses on classic machine learning (ML) models, such as Support Vector Machines (SVM), k-Nearest Neighbors (k-NN), and Random Forests (RF), as well as shallow feedforward neural networks (FNN) for this purpose. The challenges in collecting sufficient data for deep learning models are also noted [2].

●  Signal Processing and Machine Learning Techniques: The paper emphasizes the lack of in-depth analysis of signal processing (SP) and ML techniques in existing literature. It aims to fill this gap by providing a comprehensive investigation of these methods applied to AIoT for the elderly, highlighting their limitations and potential future directions [3].

●  Previous Surveys and Limitations: The authors critique existing surveys on ICT applications for the elderly, noting that they often lack a comprehensive investigation of SP and ML techniques. They aim to provide a clearer picture of the current state-of-the-art works and their limitations, which is essential for addressing the challenges posed by an ageing population [4].

In summary, this literature review serves as a valuable resource for understanding the current landscape of AIoT applications for the elderly, identifying gaps in research, and suggesting future directions for enhancing assisted living and healthcare monitoring.