The emergence of safe and cheap human teleportation would radically change global collaboration by enabling instantaneous gatherings for collective problem-solving. This technology requires new norms, infrastructures, and approaches within work, education, and policy-making. Generative AI, while not physically transporting individuals, is already reshaping collective intelligence by altering how ideas and data circulate. Policymaking involves two traditional camps: design-minded, focusing on in-person collaboration, and model-minded, based on simulations and data. Both face limitations: convenings may lack sufficient scope, while models may lack real-time data inputs. AI can bridge these gaps by integrating discussions into structured data that inform models, facilitating faster and more informed decision-making processes. This article proposes testing AI-enabled collaboration systems to enhance shared problem-solving across various domains, emphasizing the need for interdisciplinary cooperation among policymakers, scientists, and technologists.
| name | description | change | 10-year | driving-force | relevancy |
|---|---|---|---|---|---|
| Transformative Teleportation Technology | The emergence of safe and affordable human teleportation as a means for collaboration. | Shift from traditional assembly methods to instantaneous collective gatherings. | Teleportation will revolutionize global collaboration, enabling seamless interaction across distances. | The need for more efficient and effective collaboration in various sectors driven by technological advancement. | 4 |
| Generative AI in Policy | Utilization of generative AI to enhance collective intelligence in policymaking. | Transition from historical data reliance to real-time data integration in decision-making processes. | Generative AI could lead to more accurate and timely policy responses based on live data and interactions. | The demand for improved decision-making tools that reflect real-world complexities and dynamics. | 5 |
| Integration of Design and Model-minded Approaches | Blending design-oriented and model-oriented methodologies in policymaking. | From siloed approaches to a combined framework for better problem solving. | A more holistic method of decision-making that improves outcomes by leveraging diverse perspectives. | The recognition that complex challenges require multi-faceted solutions. | 4 |
| AI-Enabled Collaborative Spaces | Establishment of AI-integrated rooms for enhanced collaborative efforts. | Shift from conventional meeting formats to AI-supported deliberation and decision-making. | Collaborative spaces could become more productive and inclusive, allowing for greater participation. | The pursuit of more effective collaborative environments in an increasingly complex world. | 5 |
| Real-Time Policy Adaptation | The ability to adapt policies in real-time based on ongoing data and insights. | Moving from static policy responses to dynamic adjustments guided by real-time information. | Policymakers could become more agile, responding to changes with unprecedented speed and relevance. | The rapid pace of change in societal problems necessitates quicker policy adaptations. | 5 |
| Emergence of Hybrid Models in Policymaking | New models that incorporate both qualitative narratives and quantitative data for policymaking. | From separate narrative and statistical considerations to an integrated approach using AI. | Policymaking could lead to richer, more nuanced decision-making that meets community needs. | The complex nature of societal issues calls for blended methodologies that realize both human experiences and data. | 4 |
| Public Participation in Modeling | Engagement of the public in creating and adjusting models for policy guidance. | Transition from expert-only models to inclusive public participation in modeling frameworks. | Greater public involvement could lead to more relevant models that reflect community needs and dynamics. | Increased demand for participatory governance and inclusive decision-making processes. | 4 |
| name | description |
|---|---|
| Societal Disruption Due to Teleportation | The introduction of human teleportation could disrupt existing social and institutional structures, necessitating a complete rethink of collaboration norms. |
| Impact of AI on Collective Intelligence | Generative AI may enhance or hinder the collaborative process, affecting how people share knowledge and make decisions in real-time. |
| Potential Loss of Cultural and Institutional Integrity | Rapid technological advancements might erode essential cultural ties and institutional frameworks necessary for collaboration. |
| Coordination Challenges in Complex Systems | Difficulties in coordinating actions across multiple stakeholders can lead to suboptimal outcomes in policy and decision-making. |
| Reliance on Incomplete Data | Models relying on historical data may overlook live inputs, leading to skewed perspectives and ineffective solutions. |
| Ethical Concerns Over AI Integration | There are risks associated with governance and control related to data sharing and AI influence on human agency in collaborative processes. |
| Cultural Resistance to AI in Policy | Resistance from individuals and groups to accept AI as a core component in decision-making processes may stifle progress and innovation. |
| name | description |
|---|---|
| Enhanced Collaborative Assemblies | Communities rethink how to gather and collaborate with instant teleportation technology, allowing diverse groups to convene easily. |
| AI-Enabled Problem Solving | Integration of AI in collective intelligence processes enhances understanding and decision-making in real-time during collaborative efforts. |
| Dynamic Learning Systems | Creation of ‘room+model’ systems that continuously learn and adapt based on collaborative discussions and real-time data inputs. |
| Instant Translation of Ideas | Generative AI enables seamless translation of narratives and data between diverse cultural and disciplinary frameworks. |
| Participatory Scenario Development | Involving stakeholders in co-producing scenarios and models for policy-making, ensuring all voices are heard in the design process. |
| AI Teammates | Using AI as an active collaborator in meetings to facilitate dialogue, enhance focus, and maintain clarity in discussions. |
| Inclusive Decision-Making Frameworks | Developing frameworks that prioritize inclusivity and collective understanding to address complex policy challenges effectively. |
| Shared Knowledge Ecosystems | Building structures for shared knowledge that facilitate ongoing collaboration and connection among different communities and sectors. |
| Real-Time Data Feedback Loops | Implementing systems that provide live updates and data on collaborative progress and external impacts during policy discussions. |
| name | description |
|---|---|
| Human Teleportation | Imaginary technology enabling instant travel for groups, transforming how we assemble and collaborate. |
| Generative Artificial Intelligence (AI) | AI tools that enhance collective intelligence by improving collaboration, data processing, and information flow. |
| Participatory Dynamic Systems Modelling | An approach to integrate community input into system dynamics for better policymaking. |
| AI Teammate Systems | AI integrated into collaborative processes to support real-time decision-making and information sharing. |
| Room+Model Learning System | A system where collaborative discussions generate data that feeds into models for enhanced understanding and decision-making. |
| name | description |
|---|---|
| Human Teleportation and Its Societal Impact | The potential for safe and cheap human teleportation could reshape how we assemble and collaborate across various sectors. |
| AI in Collaborative Problem Solving | The integration of AI in collaborative processes may enhance understanding and decision-making, transforming collective intelligence in policymaking. |
| Integration of Design and Model Minded Approaches | The need for collaboration between design-minded and model-minded practitioners for effective problem-solving in complex systems. |
| Norms and Infrastructure for AI Usage | Establishing new norms and infrastructures to ensure responsible use of AI in collaborative environments while preserving human agency and societal well-being. |
| Cultural Impacts of AI Technologies | AI technologies could potentially hollow out existing cultural and social structures essential for collaboration and problem-solving. |
| Real-Time Data Utilization | Challenges of utilizing real-time data in models and maps to reflect actual on-ground dynamics in policymaking. |
| Capacity Building in Policy Domains | The necessity of building capacity for policy domains to adapt and respond to technological advancements and complex systemic issues. |
| Participatory System Dynamics | The need for participatory system dynamics to co-create policies that reflect complex environmental and social interactions. |
| Ethics of AI in Policy Spaces | The ethical considerations and potential misuse of AI data in representing interests and making decisions in policy spaces. |