World Solve

Lunar infrastructure and resource extraction could create new strategic inequalities. The challenge is developing rules that enable science and commercial activity while protecting shared interests and preventing territorial competition. 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.

Autonomous spacecraft may make split-second avoidance decisions using imperfect data and proprietary software. The unresolved problem is assigning responsibility, proving fault, and compensating affected parties across jurisdictions. 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.

AI-designed biological molecules may be created faster than their safety, ecological, and clinical properties can be characterized. The open problem is building evaluation pipelines proportionate to capability and deployment risk. 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.

Large-scale fermentation may compete with food, land, and water if it depends on agricultural inputs. Future systems need safe, affordable, low-carbon feedstocks that do not shift environmental burdens to poorer regions. 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.

AI agents may perform tasks once done by contractors, analysts, translators, and assistants. The challenge is creating rules for liability, taxation, attribution, and market fairness when human labor and machine labor overlap. The challenge is especially acute across multiple jurisdictions, where legacy systems, coordination failures, and weak oversight can magnify harm.

AI agents may perform tasks once done by contractors, analysts, translators, and assistants. The challenge is creating rules for liability, taxation, attribution, and market fairness when human labor and machine labor overlap. The challenge is especially acute in informal settlements, where legacy systems, coordination failures, and weak oversight can magnify harm.

Predictive policing can reinforce historical bias even when built from apparently neutral data. The open problem is designing standards that make public safety tools testable, reviewable, and defeasible when they cause harm. The challenge is especially acute in informal settlements, where legacy systems, coordination failures, and weak oversight can magnify harm.

Biological design tools are becoming more accessible while oversight remains fragmented across countries and institutions. The challenge is detecting dangerous activity without suppressing legitimate research or creating an intrusive global surveillance system. 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 cities may experience extreme heat precisely when electricity and water systems are least able to support cooling. The challenge is coordinating urban design, demand management, public health, and energy policy under compound stress. 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.

Claims about quantum advantage often depend on narrow benchmarks or idealized assumptions. The challenge is creating reproducible measurements that identify when quantum systems deliver meaningful benefits over classical alternatives. 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 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.

Private companies may increasingly run water, transport, energy, communication, and housing systems with public consequences. The open problem is designing regulation that ensures reliability, accountability, and public recourse when essential services fail. The challenge is especially acute in informal settlements, where legacy systems, coordination failures, and weak oversight can magnify harm.

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 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.

The technical problem is coupled with a social allocation problem: production varies, meters may be imperfect, and residents need rules they trust. Tariff design, optimization, and transparent settlement tools could make shared generation investable. 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 forecast uncertainty, incentives, or resource constraints; entrepreneurship can turn a reliable workflow into a viable service.

Frontline workers often face incomplete records, unreliable connectivity, and high consequences for missed deterioration. Decision-support models must be calibrated locally, auditable, and paired with referral logistics rather than treated as standalone AI. 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 verify uncertainty, incentives, or resource constraints; entrepreneurship can turn a reliable workflow into a viable service.

Materials may be valuable but poorly documented, contaminated, or unavailable at the needed time. Standardized audits, uncertainty-aware marketplaces, and logistics coordination could make reuse competitive with disposal. 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 measure uncertainty, incentives, or resource constraints; entrepreneurship can turn a reliable workflow into a viable service.

Small teams frequently lack stable repositories, metadata discipline, and affordable compute for preservation. Incentives for reproducible packaging, federated archives, and low-cost reruns could strengthen the reliability of applied science. 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 verify uncertainty, incentives, or resource constraints; entrepreneurship can turn a reliable workflow into a viable service.

Safety filters designed to block clearly harmful requests can sometimes be bypassed through indirect or creatively phrased questions that still elicit dangerous information. Closing this gap while preserving the system's general usefulness remains an unresolved balancing act.