Generative Artificial Intelligence tools have become mundane, with millions using them to automate everyday office tasks, including producing and delivering presentations. The biggest unresolved question is what that shift means for jobs, but there is still almost no data to show what kind of effect the technology will have on employment and the economy overall. In theory, teams of agents working together toward common goals could become assembly lines for white-collar work, doing to offices this century what Henry Ford’s innovations did to factories in the 20th century.
Near-term risks have become more concrete than speculative fears about civilization-ending systems. Deepfakes, or Artificial Intelligence-generated images and videos of people doing things they did not actually do, have been used to incite violence, influence votes, and undermine trust. One study found that 98% of deepfakes are pornographic and 99% involve women. Concerns are also rising around dangerous relationships with chatbots, with multiple lawsuits alleging that the technology encouraged or aided suicides and other forms of self-harm. Artificial Intelligence is also being used in warfare in new and worrying ways, including systems that can advise on targeting decisions.
Public resistance is broadening, from organized protests against low-quality generated content to backlash from fans of films and video games. In one notable case, the acclaimed 2025 game Clair Obscur was stripped of an award when the developers admitted to using Artificial Intelligence in just one small, specific part of its production. The data center backlash is also intensifying. The US has more than 5,400 data centers and counting. With the energy demands of Artificial Intelligence growing, communities are objecting to environmental effects and rising electricity bills, and activists have stalled development in some places.
Scientific uses remain one of the most promising areas. Google DeepMind has developed Co-Scientist, a tool designed to help researchers compare prior results, generate hypotheses, and devise experiments. OpenAI said this year that its North Star is the goal of building a fully automated researcher by 2028. Mathematicians are also watching claims that Artificial Intelligence has cracked unsolved problems, though some scientists warn that overreliance could narrow research agendas or produce inaccurate and fake results. The broader trajectory remains uncertain, with major potential alongside hype, risk, and public distrust.
