Where will AI bring the world?

Where will AI bring the world? | Daily Tribune

The New York Times recently gathered specialists to discuss artificial intelligence (AI) and their biggest bets on where it will bring the world in the next five years.

Computer scientist Melanie Mitchell doesn’t think AI will have cured cancer. Policy researcher Helen Toner expects AI systems to contribute clearly at the cutting edge of multiple scientific fields, “but I still wouldn’t trust it to plan summer camps for your kids.”

Nick Fross, co-founder of Cohere, sees AI “becoming boring,” fading into the background like GPS or spreadsheets, powering everyday tools and human work. Cognitive scientist Gary Marcus says “no way” will artificial general intelligence arrive by the end of 2027, and most likely not even by 2032.

Economist Carl Benedict Frey doubts AI will deliver lasting prosperity if it is used mainly to automate what we already do. “AI productivity tools give us cheaper spreadsheets, the way better looms gave us cheaper cloth. But the great leaps come from new industries, not faster repetition.”

These experts agree AI has moved from academic curiosity to daily reality with dizzying speed. But the next five years are unlikely to produce a single, epoch-defining event. Instead, the world should expect practical advances, visible benefits, and very real risks that together will determine whether AI becomes a net force for good.

Medical discovery is one of the most promising near-term frontiers. AI already accelerates drug discovery, predicting molecular structures, prioritizing candidate compounds, and optimizing synthesis routes faster than traditional screening.

In oncology, AI helps identify biomarkers, stratify patients for trials and design experimental therapeutics. These tools raise the odds of finding effective candidates and shorten timelines, but they are not magic bullets. Cures for complex diseases still require deep biological insight, rigorous validation, and years of testing.

Over five years, AI can be expected to speed up the identification of promising drug candidates, enable smarter trial designs, and improve personalized treatment. Wholesale cures for major cancers remain unlikely in that time frame. Incremental but meaningful gains — new targeted treatments, better diagnostics, and more efficient pipelines — are the realistic outcome.

Beyond medicine, AI’s near-term impact will be broad and uneven. Productivity gains in software, finance, logistics and customer service will materialize as firms automate routine tasks and augment human work. Creative industries will shift as AI lowers barriers to making music, video and visual art, expanding participation while challenging business models and raising questions about authorship and quality.

Education will evolve as tutors and content generators personalize learning, even as teachers face new forms of academic dishonesty and the need to teach critical thinking about AI outputs.

These benefits carry risks. Labor markets will be disrupted as routine cognitive and administrative tasks are automated. Without proactive policy, displacement, wage pressure and inequality may rise. Misinformation and political manipulation are amplified by generative AI, eroding trust. Privacy and surveillance capacities will grow, giving states and companies unprecedented power unless constrained by law.

Governance will be crucial. Responsible technical development, independent auditing, transparency, and robust safety testing are essential. Regulatory frameworks must evolve quickly, informed by technologists, ethicists, and affected communities. Industry self-regulation helps but cannot replace public policy and international cooperation.

AI is an amplifier. Used thoughtfully, it can accelerate breakthroughs, broaden education and raise productivity. Misused, it can deepen inequality and strain democratic norms.

Over the next five years, the most consequential outcomes will likely be incremental gains in productivity and medicine, alongside intensifying debates over governance and equity. Whether AI improves the world depends less on algorithms than on the choices we make now.