World Solve

Future quantum networks will need coexistence with conventional fiber, satellites, and noisy metropolitan infrastructure. A major unresolved problem is developing practical repeaters, interfaces, standards, and operational security for real-world deployment. 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.

Quantum capabilities could transform optimization, chemistry, intelligence, and cryptanalysis while becoming concentrated in a few states. The challenge is preventing destabilizing secrecy and unequal access without blocking peaceful scientific collaboration. 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.

Quantum sensors may detect hidden water, minerals, leaks, tunnels, and structural anomalies, but their cost, calibration, and interpretation remain barriers. The open problem is converting laboratory sensitivity into dependable field services. 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.

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.

Post-quantum authentication must work on inexpensive devices, intermittent networks, and systems with limited technical support. A practical solution must avoid forcing vulnerable populations to replace all hardware at once. 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.

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 AI systems may improve software, research workflows, and model-training pipelines faster than institutions can review them. The open problem is designing international oversight that supports beneficial progress while preventing uncontrolled capability escalation. 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 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.

Patients waste time visiting multiple shops, while inventory data are private and substitution rules are complex. Privacy-preserving stock signals, route optimization, and pharmacist-led protocols could reduce search costs without creating a dominant intermediary. The opportunity is intentionally human-scale: a cooperative, clinic, workshop, school, or municipal team could pilot it within one locality and measure outcomes before expanding. Mathematical modeling can help with route uncertainty, incentives, or resource constraints; entrepreneurship can turn a reliable workflow into a viable service.

Current approaches to affordable diagnostics and treatments for the leading causes of maternal mortality either underperform under variable field conditions or generate externalities that undermine long-term sustainability and equity. Closing the gap requires coordinated advances in science, systems design and enabling institutions.

Current approaches to solutions for providing safe and accessible public transport in rapidly growing secondary cities either underperform under variable field conditions or generate externalities that undermine long-term sustainability and equity. Closing the gap requires coordinated advances in science, systems design and enabling institutions.

Current approaches to technologies enabling the continuous monitoring of air quality and its health impacts at high resolution either underperform under variable field conditions or generate externalities that undermine long-term sustainability and equity. Closing the gap requires coordinated advances in science, systems design and enabling institutions.