Conceptual Framework
1. Building Trust for Participation:
Participants need to trust the organizers, facilitators, and each other to engage in open conversations. Trust is crucial for motivating individuals to contribute to genuine discussions. Facilitators must establish an environment where vulnerability is welcomed, and personal stories are shared freely. Trust is vital for participants to feel safe, both with the facilitators and other attendees.
2. Trust During and After Conversations:
Trust extends beyond the conversation itself. Participants need assurance that their contributions will be treated with respect and care, even after the discussion ends. Maintaining trust involves transparency about data handling and how their experiences will be used in the future. Uncertainties after the conversation can influence trust levels; therefore, clear communication and guidance are pivotal.
3. Long-term Nature of Trust:
Trust doesn't develop instantaneously; it's a product of long-term relationships and repeated interactions. Trust evolves as participants engage in conversations and gradually build accurate mental models of expectations. Experience with the conversation format and facilitation style contributes to a better understanding of what to anticipate, leading to increased trust over time.
4. Sensitive Data and Trust:
The handling of sensitive data, such as personal stories or traumatic experiences, raises questions about trust. Ensuring participants' trust involves safeguarding sensitive information from unauthorized access. Careful handling of sensitive content and maintaining participants' anonymity can positively impact trust levels.
5. Management of Expectations:
Managing participants' expectations regarding the purpose of conversations, data usage, and potential outcomes is crucial for fostering trust. Open communication about the post-conversation process helps prevent uncertainties that might erode trust. Setting clear guidelines and informing participants of the entire process can mitigate trust-related concerns.
6. Trust in Data Ownership and Privacy:
The ownership of data and participants' control over their contributions enhance trust. Participants should have the autonomy to retract their inputs if desired, giving them a sense of control over their data. Ensuring that participants understand their rights and options for data management contributes to trust in the conversation platform.
7. Balancing Trust and Reporting Obligations:
Trust may clash with legal or organizational reporting obligations. While participants' voices are essential, sensitive information, such as potential harm to oneself, must be managed responsibly. Balancing participants' trust with necessary reporting requirements is a complex challenge.
8. Community Voice and Ownership:
A critical aspect of trust is acknowledging that participants are stakeholders, not just data sources. Empowering participants with decision-making authority over their contributions reinforces trust. A participant's right to retract their data demonstrates respect for their ownership and enhances overall trust.
9. Navigating Conversational Data Trust:
Navigating trust in conversational data involves a nuanced approach. Striking a balance between transparency, privacy, security, and participants' expectations is paramount. As the landscape evolves, frameworks need to address challenges arising from participant interactions, data handling, and societal expectations.