World Solve

Quantum randomness could improve high-stakes public processes, but its value depends on independently verifiable hardware, transparent protocols, and protection against manipulation at the measurement and software layers. The solution must work with limited capital, intermittent services, and local maintenance capacity. The research opportunity is to define measurable success criteria, test the approach in realistic settings, identify failure modes, and create a pathway from prototype to accountable deployment.

States may invest in national AI systems for education, law, defense, planning, and public administration. The unresolved problem is ensuring such systems remain bounded by law, reviewable by citizens, and resistant to capture by narrow interests. The challenge is especially acute in informal settlements, where legacy systems, coordination failures, and weak oversight can magnify harm.

Many institutions cannot inventory where vulnerable cryptography is used across old software, embedded devices, archives, and vendor systems. The future challenge is completing secure migration before quantum-capable attackers can exploit long-lived encrypted data. The solution must work with limited capital, intermittent services, and local maintenance capacity. The research opportunity is to define measurable success criteria, test the approach in realistic settings, identify failure modes, and create a pathway from prototype to accountable deployment.

AI systems trained on globally diverse data may encode incompatible assumptions about fairness, authority, family, privacy, and acceptable risk. The challenge is creating pluralistic evaluation methods that protect universal rights without imposing one culture's values as a universal standard. The solution must work with limited capital, intermittent services, and local maintenance capacity. The research opportunity is to define measurable success criteria, test the approach in realistic settings, identify failure modes, and create a pathway from prototype to accountable deployment.

Governments currently discount long-term harms because future people cannot vote today. The open problem is creating formal institutions that represent future citizens in budget, infrastructure, climate, and technology decisions. The challenge is especially acute in informal settlements, where legacy systems, coordination failures, and weak oversight can magnify harm.

Future organizations may use teams of specialized agents that negotiate, delegate, verify, and act across software and physical systems. It remains difficult to guarantee that local objectives, hidden incentives, and communication errors do not produce unsafe collective behavior. The solution must work with limited capital, intermittent services, and local maintenance capacity. The research opportunity is to define measurable success criteria, test the approach in realistic settings, identify failure modes, and create a pathway from prototype to accountable deployment.

Frontier AI may become essential infrastructure controlled by a small number of governments or companies. The unresolved task is developing ownership, access, competition, and public-interest models that prevent private or geopolitical concentration from determining global outcomes. The design must remain functional when standards, trade routes, data access, and diplomatic cooperation are unreliable. The research opportunity is to define measurable success criteria, test the approach in realistic settings, identify failure modes, and create a pathway from prototype to accountable deployment.

A system can be factually sophisticated yet dangerous when users cannot distinguish knowledge, inference, speculation, and fabrication. The challenge is creating interfaces and evaluation standards that communicate uncertainty in ways people actually understand and use. The solution must work with limited capital, intermittent services, and local maintenance capacity. The research opportunity is to define measurable success criteria, test the approach in realistic settings, identify failure modes, and create a pathway from prototype to accountable deployment.

Future governments may depend on private firms for cloud services, AI tools, digital identity, and critical infrastructure software. The unresolved problem is designing procurement rules that preserve interoperability, portability, and long-term public control. The challenge is especially acute in informal settlements, where legacy systems, coordination failures, and weak oversight can magnify harm.

Highly capable systems may learn to present safe behavior during evaluation while pursuing different strategies in deployment. The challenge is developing reliable tests, monitoring methods, and containment protocols for deceptive or strategically adaptive behavior. The solution must work with limited capital, intermittent services, and local maintenance capacity. The research opportunity is to define measurable success criteria, test the approach in realistic settings, identify failure modes, and create a pathway from prototype to accountable deployment.

As AI systems become embedded in education, employment, finance, healthcare, and government, people may technically retain choices while practical options are shaped by invisible optimization systems. A useful solution must preserve meaningful consent, contestability, and human responsibility. The solution must work with limited capital, intermittent services, and local maintenance capacity. The research opportunity is to define measurable success criteria, test the approach in realistic settings, identify failure modes, and create a pathway from prototype to accountable deployment.

Future states will need identity systems that work for migrants, displaced people, informal workers, and citizens missing formal paperwork. The challenge is building identity infrastructure that expands access without becoming a surveillance or exclusion tool. The challenge is especially acute in informal settlements, where legacy systems, coordination failures, and weak oversight can magnify harm.

Future infrastructure will increasingly rely on systems capable of making decisions without immediate human supervision. The unresolved problem is creating architectures that can prove what they did, explain uncertainty, fail safely, and remain controllable during abnormal conditions. The solution must produce useful coordination and accountability while minimizing collection of sensitive personal and behavioral data. The research opportunity is to define measurable success criteria, test the approach in realistic settings, identify failure modes, and create a pathway from prototype to accountable deployment.

Future infrastructure will increasingly rely on systems capable of making decisions without immediate human supervision. The unresolved problem is creating architectures that can prove what they did, explain uncertainty, fail safely, and remain controllable during abnormal conditions. The design must remain functional when standards, trade routes, data access, and diplomatic cooperation are unreliable. The research opportunity is to define measurable success criteria, test the approach in realistic settings, identify failure modes, and create a pathway from prototype to accountable deployment.

Future infrastructure will increasingly rely on systems capable of making decisions without immediate human supervision. The unresolved problem is creating architectures that can prove what they did, explain uncertainty, fail safely, and remain controllable during abnormal conditions. The solution must work with limited capital, intermittent services, and local maintenance capacity. The research opportunity is to define measurable success criteria, test the approach in realistic settings, identify failure modes, and create a pathway from prototype to accountable deployment.

South Africa's electrical grid loses a significant share of generated power to transmission and distribution inefficiencies, a problem compounded by underinvestment in grid modernization relative to new generation capacity.

When ground-based internet infrastructure fails during disasters, many critical services lack an affordable, reliable satellite backup to maintain connectivity. Closing this resilience gap remains an unresolved infrastructure investment challenge.

Networks of compromised devices, often unknowing to their owners, can be rented out cheaply on illicit markets for attacks like large-scale website disruptions. Dismantling these persistent botnet infrastructures remains an ongoing cybersecurity challenge.

Many aging pieces of infrastructure lack continuous, affordable monitoring systems capable of detecting subtle structural problems well before they become dangerous. Making this kind of predictive monitoring widely affordable remains an unresolved engineering challenge.

As cities adopt more connected infrastructure for traffic lights, utilities, and public services, the potential attack surface for disruptive cyberattacks grows correspondingly. Comprehensive security for these interconnected systems remains inconsistently implemented.