World Solve

Political communication will increasingly include deepfakes, voice cloning, and AI-generated persuasion at scale. The challenge is developing election rules, platform standards, and enforcement systems that protect speech while limiting manipulation. The challenge is especially acute in informal settlements, where legacy systems, coordination failures, and weak oversight can magnify harm.

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.

As machine learning enters welfare, policing, housing, tax, and licensing systems, bias can become harder to detect and contest. The open problem is creating enforceable standards for fairness, appeals, and independent review across all public-sector uses of automated decision-making. The challenge is especially acute in informal settlements, where legacy systems, coordination failures, and weak oversight can magnify harm.

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.

Governments will increasingly rely on automated systems to allocate benefits, flag risks, prioritize inspections, and recommend enforcement. The unresolved problem is creating governance structures that make these systems transparent, contestable, and accountable without disabling public service delivery. The challenge is especially acute in informal settlements, where legacy systems, coordination failures, and weak oversight can magnify harm.

Vendors operate with thin margins and little historical data. Lightweight forecasting, shared cold storage, and cooperative purchasing could convert neighborhood-level signals into practical decisions without requiring enterprise software. 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 allocate uncertainty, incentives, or resource constraints; entrepreneurship can turn a reliable workflow into a viable service.

Competence is often real but invisible to employers because certificates measure course completion rather than performance. Practical assessments, portable evidence, and trusted local validators could improve matching without forcing workers into expensive retraining. 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 allocate uncertainty, incentives, or resource constraints; entrepreneurship can turn a reliable workflow into a viable service.

Unpaid domestic and care work performed predominantly by women in Papua New Guinea is largely excluded from national economic statistics and social protection policy, undervaluing its contribution.

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.

The absence of robust, context-adapted solutions for institutional arrangements that accelerate the adoption of proven public health interventions creates cascading risks across interconnected human and natural systems. Key missing elements include durable performance, low lifetime cost, and governance arrangements capable of sustaining impact beyond pilot stages.

The absence of robust, context-adapted solutions for governance frameworks ensuring that advances in longevity science benefit all socioeconomic groups creates cascading risks across interconnected human and natural systems. Key missing elements include durable performance, low lifetime cost, and governance arrangements capable of sustaining impact beyond pilot stages.

The absence of robust, context-adapted solutions for technologies enabling precise and low-impact application of agricultural inputs creates cascading risks across interconnected human and natural systems. Key missing elements include durable performance, low lifetime cost, and governance arrangements capable of sustaining impact beyond pilot stages.

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.

Women in formal-sector jobs in Peru continue to earn less than men in comparable roles, and current pay-transparency requirements are too weak to be enforced effectively.

Current approaches to cognitive and social interventions that improve collective problem-solving under uncertainty 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.

The absence of robust, context-adapted solutions for cryptographically private national-scale health data analytics creates cascading risks across interconnected human and natural systems. Key missing elements include durable performance, low lifetime cost, and governance arrangements capable of sustaining impact beyond pilot stages.

Networks of AI-assisted fake dating profiles can be deployed at scale to build trust with vulnerable users before extracting money or personal information. Detecting these coordinated networks before real harm occurs remains an unresolved platform challenge.

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.

Instruction manuals generated automatically for online product listings sometimes contain fabricated or inaccurate safety information, since the process isn't always reviewed by someone with real product knowledge. This creates real safety risks for consumers.