World Solve

As cities adopt more connected infrastructure for traffic lights, utilities, and public services, the potential attack surface for disruptive cyberattacks grows correspondingly. Comprehensive security for these interconnected systems remains inconsistently implemented.

Implanted medical devices like pacemakers increasingly connect wirelessly for monitoring, but security protections for these devices haven't kept pace with the sensitivity of what's at stake if they're compromised. Closing this gap remains an urgent but underaddressed challenge.

AI can now generate entirely fake but convincing photos and personas used to build fraudulent romantic or social relationships online for financial exploitation. Detecting and removing these fake profiles quickly enough remains an unresolved platform challenge.

Scammers can deploy AI-driven chat systems that convincingly impersonate real customer service representatives to extract sensitive information from victims. Detecting and shutting down these operations quickly remains an unresolved challenge for platforms and regulators.

Fraudsters can use AI to generate entirely fake but convincing identities, complete with fabricated financial histories, to open accounts and commit fraud at scale. Detecting these synthetic identities before damage occurs remains a growing, unresolved challenge for financial institutions.

Scammers increasingly use AI to generate convincing fake job postings and interview processes designed to steal personal information or money from desperate job seekers. Platforms are still catching up to detect and remove these scams effectively.

Insurance companies increasingly use AI to assess claims, but there's limited independent, scalable auditing to ensure these systems aren't unfairly denying or delaying valid claims. Building trustworthy oversight for this remains an unresolved regulatory and technical challenge.

Low-code and no-code platforms have made software creation more accessible, but users without security expertise can still inadvertently build applications with serious vulnerabilities. Making these tools both accessible and inherently safe remains an unresolved design challenge.

As AI-generated faces and voices become more realistic, some biometric security systems can potentially be fooled by convincing synthetic versions of a real person's face or voice. Strengthening these systems against this emerging threat remains an active challenge.

Automatically applying every software update reduces security risk but occasionally introduces new bugs or incompatibilities, while manual review introduces dangerous delays. Balancing these risks reliably remains an unresolved operational challenge.

People increasingly turn to AI chatbots for guidance on legal or financial questions, but these systems can provide plausible-sounding yet incorrect advice with no clear warning of their limitations. Better safeguards around this kind of high-stakes advice remain underdeveloped.

AI-generated contracts, court filings, or legal notices can appear authentic enough to deceive people unfamiliar with proper legal formatting, creating new fraud risks. Detecting these fakes reliably remains an emerging unresolved challenge.

Terms of service and software licenses are often long, dense legal documents that almost no one actually reads before clicking agree. Making these terms genuinely understandable without losing their legal protection remains unresolved.

Fake reviews generated at scale by AI can be nearly indistinguishable from genuine customer feedback, undermining trust in online shopping decisions. Detection tools are struggling to keep pace with how convincing these fakes have become.

AI health tools can sometimes provide advice that sounds plausible but is subtly wrong or dangerous, and there's no consistent, scalable system for catching these errors before they reach real patients. This gap grows more urgent as AI health tools become more widely used.

Search results are increasingly cluttered with content engineered to game ranking algorithms rather than genuinely help users, and search engines are struggling to keep pace with these tactics. This has made finding trustworthy information online noticeably harder over time.

Early brain-computer interfaces show promise for helping paralyzed patients control devices with thought alone, but long-term safety, reliability, and signal accuracy remain unresolved. Wider medical adoption depends on solving these fundamental issues first.

Content that provokes strong emotional reactions tends to get algorithmically boosted because it keeps people engaged longer, regardless of whether it's accurate or healthy. Redesigning these systems without destroying platform business models remains unresolved.

The way solid-state drives store data internally makes secure, complete deletion technically harder than with traditional spinning hard drives. This creates lingering privacy and security risks when these drives are discarded or resold.

Most software vulnerabilities trace back to common coding mistakes that better language design could prevent from the start. Despite decades of research, mainstream programming still makes these mistakes easy to make.