World Solve

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 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.

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.

Digital commerce, cloud services, and AI platforms can generate value across borders while escaping clear tax authority. The challenge is creating fair tax rules that smaller states can enforce without being excluded from the digital economy. The challenge is especially acute for low-resource administrations, where legacy systems, coordination failures, and weak oversight can magnify harm.

Digital commerce, cloud services, and AI platforms can generate value across borders while escaping clear tax authority. The challenge is creating fair tax rules that smaller states can enforce without being excluded from the digital economy. The challenge is especially acute across fragmented municipalities, where legacy systems, coordination failures, and weak oversight can magnify harm.

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.

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.

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.

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 produce useful coordination and accountability while minimizing collection of sensitive personal and behavioral data. 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.

Automated trading algorithms can sometimes trigger rapid, extreme price swings in smaller or less liquid markets, especially during unusual conditions, without any single actor intending market harm. Building safeguards against this kind of systemic risk remains incomplete.

Businesses seeking to cut corners could potentially use AI to generate fabricated but convincing compliance records for regulatory audits, and auditors don't always have the tools to catch increasingly sophisticated fake documentation. Strengthening audit verification remains an unresolved challenge.

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.

Digital contracts can potentially be modified after signing in ways that aren't always immediately detectable without specialized forensic review. Building this verification directly into standard contract systems remains incompletely adopted.

Attackers can automatically test massive numbers of previously leaked username and password combinations across many websites to find accounts where the same credentials still work. Reducing the effectiveness of this widespread technique remains an unresolved security challenge.

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.

Old photographs and videos can be digitally altered using AI in ways that are difficult to distinguish from genuine historical restoration, risking the distortion of the historical record. Forensic tools for detecting this kind of manipulation remain underdeveloped.

Tutoring platforms can be targeted by individuals using AI-generated fake credentials to appear more qualified than they actually are, and verification systems don't always catch this convincingly fabricated background information. Closing this trust gap remains an unresolved platform challenge.