World Solve

AI and laboratory automation can identify promising compounds that fail during scale-up, processing, or deployment. The open problem is connecting discovery models to cost, supply, safety, and lifecycle constraints. 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 increasingly use prediction to allocate policing, welfare, migration, health, and education resources. Future rights frameworks must address errors, feedback loops, opacity, and the danger of being treated as a probability rather than a person. 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.

Silhouettes that lengthen or shorten according to predicted lifespan turn private health data into ambient visual information. The challenge is protecting individuals from involuntary longevity signalling in everyday environments.

Pavements that remember and respond to historical load patterns can create uneven safety conditions. The problem is designing surfaces that remain predictably safe for all users regardless of prior traffic.

Roadways that shrink in real time based on predicted density can trap pedestrians and restrict access. The problem is managing crowd flow without creating physical bottlenecks that endanger people or exclude those with mobility needs.

Official documents that continuously revise expected lifespan can shape education, insurance, relationships, and self-perception from birth. The challenge is providing useful health information without embedding deterministic forecasts into legal identity.

Localised gravity fluctuations caused by energy or structural load management can injure residents and damage property. The challenge is designing buildings and occupancy rules that prevent such failures or make them predictable and survivable without requiring constant monitoring.

Vehicles that dynamically alter destinations according to collective emotional signals create unpredictability for both passengers and city logistics. The challenge is balancing responsiveness with reliability so that mobility remains dependable for work, care, and emergency needs.

Urban platforms that reposition based on market indicators create unpredictable geography, disrupt supply chains, and separate communities. The problem is coordinating mobility, infrastructure continuity, and resident rights when the ground itself moves for financial reasons.

Residences that rearrange themselves overnight according to algorithmic mood forecasts may increase comfort for some while creating disorientation, loss of control, or surveillance concerns for others. The challenge is balancing adaptive environments with resident agency, privacy, and predictability.

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.

Border systems may increasingly use risk scoring, biometric checks, and predictive screening. The unresolved problem is ensuring security tools do not become opaque instruments of arbitrary exclusion or rights violations. The challenge is especially acute in informal settlements, where legacy systems, coordination failures, and weak oversight can magnify harm.

Governments may use health and behavioral data to predict outbreaks, allocate care, or target interventions. The open problem is enabling public-health benefits while preventing discrimination, mission creep, and privacy erosion. 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.

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.

Even with extensive automated testing, software products regularly ship with bugs that only appear once real users start interacting with them in unpredictable ways. Comprehensive, fully reliable bug detection before release remains an unsolved engineering challenge.

Homes are full of unpredictable obstacles, from pets to scattered toys, that robots still struggle to navigate as reliably as humans do without careful pre-mapping. This limits how useful home robots can be for daily tasks.

Rising temperatures and changing winds are destabilising ice shelves and altering Southern Ocean circulation, with global implications for sea-level rise and extreme weather. High-resolution coupled climate–ice models and sustained observation networks are needed to predict these changes.

Solar flares, coronal mass ejections, and stellar winds shape atmospheric escape and habitability, yet models remain approximate. Continuous monitoring and improved magnetohydrodynamic simulations can refine predictions.

Theory predicts metal-free stars that reionized the Universe, but no such stars have been observed. JWST-class telescopes and 21cm cosmology experiments could provide indirect signatures.