Future research opportunities
| Research opportunities | Potential research approach |
|---|---|
| Overarching research propositions | |
| How should consumers, providers, regulators and service firms determine appropriate levels of sacrifice of personal control? How should stakeholders manage transparency, trust and accountability? How can society prevent failure to reduce overall vulnerability/avoid contributing to greater inequality? | Interdisciplinary and collaborative research across policy makers, community leaders, service providers and academic scholars to address the broad based overarching research propositions |
| Personal AI-agent design and role archetypes research | |
| To what extent does a personal AI-agent reduce vulnerability (by depth or breadth)? | Semi-structured interviews with consumers experiencing vulnerability |
| To what extent do personal AI-agents enhance consumers' perceived control and how does this vary by context? | Experiments to manipulate breadth/depth of vulnerabilities that compare consumer or provider control |
| How can personal AI-agent design attributes that make a difference to consumers experiencing vulnerability be operationalized? | Semi-structured interviews and surveys to explore completeness and contribution of each design attribute in enhancing well-being |
| How can personal AI-agents be adopted and what are the barriers and enablers to adoption with consumers experience vulnerability? | Case studies or ethnographies in vulnerability contexts. Interviews with consumers, AI-agent providers and regulatory bodies. Consumer post-interaction surveys, focus groups or interview |
| How to implement and deploy a personal AI-agent? How can agents be implemented with the four archetypes identified? | Field experiments with AI-agents across stakeholders in various roles |
| How does decision making change when inversion of control allows AI-agents to act as an intermediary? E.g., Do purchasing, querying and service request patterns change? | Semi-structured interviews with marketing and customer service representatives and surveys of consumers using personal AI-agents |
| To what extent do modalities of AI-agents influence design and adoption of personal AI-agents in consumers experiencing vulnerabilities? | Inter-disciplinary research between: Embodied AI; robot-human interaction; and consumer vulnerability in services |
| How to design appropriate regulatory safeguards that provide the guardrails around personal AI-agents but also do not limit innovation? | Inter-disciplinary work with policy researchers, ethics researchers and information systems researchers to explore compliance standards |
| How to identify roles and create personas of personal AI-agents? | Service blueprinting techniques developed by means of case studies to define, design and develop a process to create AI-agent personas |
| How does service sector influence the archetypes of personal AI-agents. For, e.g. highly regulated sectors like energy and finance vs less regulated sectors like retail | Surveys, interviews, Delphi method, observation with consumers, service providers, designers and implementors of AI |
| How can AI-agents be designed for employees or frontline staff who may be experiencing vulnerability? | Extend this work conceptually or empirically with vignettes from employee experience contexts across sectors and settings |
| Research opportunities | Potential research approach |
|---|---|
| Interdisciplinary and collaborative research across policy makers, community leaders, service providers and academic scholars to address the broad based overarching research propositions | |
| To what extent does a personal AI-agent reduce vulnerability (by depth or breadth)? | Semi-structured interviews with consumers experiencing vulnerability |
| To what extent do personal AI-agents enhance consumers' perceived control and how does this vary by context? | Experiments to manipulate breadth/depth of vulnerabilities that compare consumer or provider control |
| How can personal AI-agent design attributes that make a difference to consumers experiencing vulnerability be operationalized? | Semi-structured interviews and surveys to explore completeness and contribution of each design attribute in enhancing well-being |
| How can personal AI-agents be adopted and what are the barriers and enablers to adoption with consumers experience vulnerability? | Case studies or ethnographies in vulnerability contexts. Interviews with consumers, AI-agent providers and regulatory bodies. Consumer post-interaction surveys, focus groups or interview |
| How to implement and deploy a personal AI-agent? How can agents be implemented with the four archetypes identified? | Field experiments with AI-agents across stakeholders in various roles |
| How does decision making change when inversion of control allows AI-agents to act as an intermediary? E.g., Do purchasing, querying and service request patterns change? | Semi-structured interviews with marketing and customer service representatives and surveys of consumers using personal AI-agents |
| To what extent do modalities of AI-agents influence design and adoption of personal AI-agents in consumers experiencing vulnerabilities? | Inter-disciplinary research between: Embodied AI; robot-human interaction; and consumer vulnerability in services |
| How to design appropriate regulatory safeguards that provide the guardrails around personal AI-agents but also do not limit innovation? | Inter-disciplinary work with policy researchers, ethics researchers and information systems researchers to explore compliance standards |
| How to identify roles and create personas of personal AI-agents? | Service blueprinting techniques developed by means of case studies to define, design and develop a process to create AI-agent personas |
| How does service sector influence the archetypes of personal AI-agents. For, e.g. highly regulated sectors like energy and finance vs less regulated sectors like retail | Surveys, interviews, Delphi method, observation with consumers, service providers, designers and implementors of AI |
| How can AI-agents be designed for employees or frontline staff who may be experiencing vulnerability? | Extend this work conceptually or empirically with vignettes from employee experience contexts across sectors and settings |