Social companionship means that AI programs can form emotional connections and have meaningful talks, not just do simple tasks. It is more than just answering questions or setting appointments—it involves noticing how a person feels and responding with care. This makes the AI feel more like a real friend.
In healthcare, this is very important. Many patients feel worried or stressed about their health or visits. An AI companion that communicates kindly can help lower stress, keep patients involved, and encourage better care after visits. Also, healthcare places need to give answers quickly even with many patients and work to do. AI companions with social skills can help, making both the work and patient experience better.
A study from August 2023 looked closely at social companionship in AI that talks with people. The authors — Rijul Chaturvedi, Sanjeev Verma, Ronnie Das, and Yogesh K. Dwivedi — reviewed lots of research and put together a framework to guide AI use in healthcare.
The framework has four main parts:
Knowing these parts helps healthcare workers make AI companions that not only work well but also care about patients’ feelings.
Some important ideas guide how AI can act as a social companion:
In U.S. healthcare, these ideas mean AI should be made to fit different kinds of patients. This helps make AI tools feel less cold and more friendly.
Ethics are very important when using AI in healthcare. This includes keeping patient privacy safe, getting permission, being open about how AI works, and avoiding bias. As AI becomes more social, keeping ethics becomes even harder and more needed.
Medical administrators in the U.S. need to make sure AI follows the Health Insurance Portability and Accountability Act (HIPAA) and other rules. AI must protect patient info, tell patients when they are talking to AI, and be clear about its actions.
Also, AI should not try to trick patients or make them think AI can do more than it can. AI should help people, not replace human care.
Researchers see several ways social AI can get better in healthcare:
For U.S. providers, using these developments can improve patient talks, lower staff work, and make healthcare better overall.
Running healthcare offices is hard for practice owners and IT managers in the U.S. Tasks include scheduling, answering patients’ questions, billing, and insurance. Manual methods often cause long waits, errors, and staff shortages.
AI-powered phone systems, like those from companies such as Simbo AI, improve these workflows by answering calls smartly. These AI systems handle common patient needs, letting staff handle harder jobs and lowering wait times.
How AI Companions Help Workflow Automation:
Using these AI tools in the U.S. means IT managers must make sure systems work well with current setups, follow security rules, and have staff support. Good training and clear communication help make adoption easier.
Healthcare providers in the U.S. need to improve patient talks while keeping costs low. AI companions made with social companionship and ethics in mind offer useful solutions.
Medical administrators can use AI tools to:
IT managers have key jobs in choosing, setting up, and keeping AI systems working. They must keep systems secure, connect AI to clinical work, and watch AI to keep it ethical. Working with healthcare leaders is important to make sure AI helps patient care.
Research on social companionship AI comes from scholars like Rijul Chaturvedi, who studies emotional AI in marketing and commerce; Sanjeev Verma, with experience in marketing and engineering; Ronnie Das, an expert in digital marketing and machine learning; and Yogesh K. Dwivedi, a well-known researcher in digital marketing and information systems. They combine knowledge from many areas, mixing technology, marketing, patient behavior, and healthcare problems.
Dwivedi helped create a detailed framework that shows how AI companions work socially and emotionally. This helps U.S. healthcare leaders use better AI tools.
Building ethical and efficient AI companions for healthcare means focusing on social companionship that connects emotionally, keeps patients involved, and follows rules. Adding these AI tools to U.S. healthcare work with careful ethics lets medical administrators and IT managers improve patient talks, automate office jobs, and get ready for future AI improvements. Research by Chaturvedi, Verma, Das, and Dwivedi gives a good base for these efforts.
Social companionship in conversational agents refers to the feature enabling emotional bonding and consumer relationships through interaction, enhancing user engagement and satisfaction.
The field shows exponential growth with fragmented findings across disciplines, limiting holistic understanding. A comprehensive review is needed to map science performance and intellectual structures, guiding future research and practical design.
The study employed systematic literature review, science mapping, intellectual structure mapping, thematic, and content analysis to develop a conceptual framework for SC with conversational agents.
It encompasses antecedents, mediators, moderators, and consequences of social companionship with conversational agents, offering a detailed structure for understanding and further research.
The study identifies five main research streams, though specifics were not detailed in the extracted text; these likely cover emotional AI, anthropomorphism, social presence, affective computing, and ethical AI companions.
The study suggests future avenues focused on designing efficient, ethical AI companions, emphasizing emotional bonding, user experience, and integrating multidisciplinary insights.
Antecedents initiate social companionship, mediators influence the strength or quality of interaction, and moderators affect the conditions or context under which companionship outcomes occur.
Anthropomorphism, attributing human-like qualities to AI agents, enhances social presence and emotional bonding, crucial elements in social companionship.
Affective computing enables AI agents to recognize and respond to user emotions, improving empathy, engagement, and personalized healthcare interactions.
It provides a comprehensive conceptual framework and future research guidance to develop efficient, ethical conversational AI agents that foster authentic social companionship and improve user outcomes.
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