World Solve

Once a company achieves significant market dominance, it can sometimes reduce quality or add restrictions with little competitive consequence, since users have few comparable alternatives. Preventing this kind of unchecked degradation remains an unresolved market structure issue.

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.

Recommendation systems tend to show users more of what they already agree with because that content performs better for engagement, gradually narrowing exposure to differing viewpoints. Correcting for this without reducing relevance remains an unresolved design challenge.

Mistakes in AI-assisted translation can have serious consequences in legal or medical contexts, yet independent verification of accuracy in these high-stakes settings remains inconsistent. Building reliable safeguards for critical-use translation remains an unresolved challenge.

AI can help generate convincing fake diplomas, transcripts, or certification documents, and verification systems haven't fully caught up with detecting these increasingly sophisticated forgeries. Closing this verification gap remains an unresolved challenge for employers and institutions.

Advanced surveillance technology developed for legitimate security purposes can end up being sold to and misused by governments to suppress dissent. Preventing this kind of misuse through export controls or corporate accountability remains inconsistently enforced.

Even with privacy safeguards, AI models can sometimes reproduce specific pieces of sensitive information they encountered during training when prompted the right way. Fully preventing this kind of unintentional data leakage remains an unresolved technical challenge.

Despite improved detection tools, non-consensual intimate images can still spread quickly across platforms before removal, causing lasting harm to victims. Faster, more comprehensive detection and removal systems remain an urgent unmet need.

When one website's user database is breached, attackers often successfully reuse those same stolen credentials on other unrelated websites where people reused the same password. Preventing this cascade of breaches remains an ongoing security challenge despite widespread password reuse warnings.

Existing assistive navigation tools for blind and visually impaired users remain limited in accuracy and are often too expensive for widespread daily use. A truly reliable, affordable solution remains an unmet accessibility need.

Cookie consent banners have become a near-universal nuisance without necessarily giving users meaningful, easy-to-understand control over their data. Redesigning this system to be both genuinely protective and user-friendly remains unresolved.

A huge share of global internet traffic between continents relies on a relatively small number of undersea cables, and damage to just one can disrupt connectivity for entire regions. Building enough redundancy to fully prevent this remains costly and incomplete.

Even after an AI model is retired, techniques exist that can sometimes extract fragments of its original training data, posing ongoing privacy risks. Fully preventing this kind of data leakage after decommissioning remains unresolved.

As AI-powered search and assistants become primary ways people find information, a small number of companies effectively shape what most people see and believe. Ensuring this influence remains fair and transparent remains a largely unresolved governance issue.

AI hiring systems trained on historical hiring data can inadvertently learn and repeat past patterns of discrimination, even when explicitly designed to avoid it. Fully eliminating this bias while maintaining useful screening capability remains unresolved.

A surprising amount of the internet's daily traffic runs through a small number of major cloud providers, meaning a single technical failure can take down countless unrelated websites and services at once. Reducing this concentrated fragility remains an unresolved structural issue.

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.

While hardware energy use gets some attention, the carbon footprint of running specific pieces of software, from development to daily use, remains largely unmeasured and unaccounted for. Building this tracking into standard practice remains unresolved.

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.

Specialized AI hardware is improving, but there's still a significant tradeoff between processing power and energy efficiency that hasn't been fully solved. Breaking this tradeoff could dramatically reduce AI's growing environmental footprint.