World Solve

Future progress on human development and planetary health depends on solving animal welfare laws remaining weak. Conventional approaches have proven insufficient. The required intervention must integrate community knowledge, data and appropriate technology while remaining affordable, privacy-preserving and operable with minimal external support. Strong solutions will articulate measurable impact metrics, risk mitigation strategies, and a plan for sustained operation by local actors after the pilot phase.

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.

Pets that age backward or forward according to measured human engagement create welfare and ethical dilemmas. The challenge is ensuring consistent, healthy lifespans independent of fluctuating owner behaviour.

If pets can be induced to shift attachment based on economic offers, the human-animal bond becomes a marketable asset. The problem is protecting enduring relationships from commercial override while still allowing rehoming under genuine welfare conditions.

When companion animals gain the ability to express complex preferences and demands, existing ownership models break down. The problem is defining rights, responsibilities, and welfare standards that protect both animals and humans without creating unmanageable legal or social burdens.

Biometric identity can reduce fraud while also excluding people whose fingerprints, faces, or documents do not match. The open problem is creating identity governance that is secure without making access to basic entitlements brittle. The challenge is especially acute in informal settlements, where legacy systems, coordination failures, and weak oversight can magnify harm.

As benefits move online, errors can become opaque and difficult to reverse. The challenge is creating fast, accessible grievance systems that help ordinary people correct eligibility mistakes without requiring legal expertise. 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.

Pension and healthcare costs rise as the working-age population shrinks, forcing reforms in labour markets and social protection. Modelling tools and policy pilots for sustainable welfare redesign are needed.

Pension and healthcare costs rise as the working-age population shrinks, forcing reforms in labour markets and social protection. Modelling tools and policy pilots for sustainable welfare redesign are needed.

Over 80% of workers in countries like India, Bangladesh, and Nepal operate within informal economies without access to pensions, disability insurance, or minimum wage guarantees. Traditional bureaucratic tax and welfare systems fail to track or protect these transient and cash-reliant populations during economic shocks.

When an algorithm denies someone benefits or flags them as a risk, it's often unclear who is responsible for reviewing or correcting that decision. This accountability gap grows as governments rely more heavily on automated systems.

Reviving extinct species raises questions about ecological impact, animal welfare, and whether it's truly meant to help nature or satisfy human curiosity. There's no consensus on whether this is a responsible use of the technology.

If advanced artificial systems could one day be conscious, we'd face serious ethical obligations toward them, but we lack any reliable test for detecting genuine inner experience. This uncertainty already complicates debates about AI rights and welfare.

Nationalist ethics often justify prioritizing citizens, while cosmopolitan views argue all human welfare deserves equal moral weight regardless of nationality. This unresolved tension underlies major debates in international policy and immigration.

Ensure older adults, disabled people, rural residents, and undocumented groups can access benefits when governments shift from cash to digital channels.

Build accessible, time-bound, auditable mechanisms for people wrongly denied benefits, especially where automated eligibility systems create opaque errors.

The absence of robust, context-adapted solutions for methods for quantifying and reducing the animal welfare impacts of different food production systems 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.

A persistent gap exists in realizing practical, scalable solutions for methods for quantifying and reducing the welfare impacts of wild animal suffering. Scientific understanding, engineering readiness and institutional capacity remain insufficient to translate promising concepts into durable impact under real-world constraints of cost, skills and governance.