{"id":47753,"date":"2026-04-01T15:18:43","date_gmt":"2026-04-01T15:18:43","guid":{"rendered":"https:\/\/naijaglobalnews.org\/?p=47753"},"modified":"2026-04-01T15:18:43","modified_gmt":"2026-04-01T15:18:43","slug":"what-do-we-teach-now","status":"publish","type":"post","link":"https:\/\/naijaglobalnews.org\/?p=47753","title":{"rendered":"What Do We Teach Now?"},"content":{"rendered":"

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Technologists, economists and visionaries are warning us that in the next three to 18 months, we are going to experience rapid and pervasive disruption of our professional lives, workplace models and distribution of income. Professional positions requiring college degrees will be lost, remade into highly productive, cost-efficient, hybrid human-AI\u00a0models where human contributions and compensation will collectively shrink and evaporate.<\/p>\n

The question we must answer very soon is what can we teach that will prepare our learners to endure the huge changes that are upon us? We must not stay the course as it becomes abundantly clear that things are not going to be the same. Lest we say that these forecasts and claims are mere hyperbole, let\u2019s examine the GDPval benchmark report \u201cMeasuring the performance of our models on real-world tasks,\u201d indicating AI\u00a0models are approaching or matching industry expert performance in complex tasks like spreadsheet modeling and document editing, with significantly higher speed and lower cost than human professionals in 44\u00a0professions.<\/p>\n

GDPval is OpenAI\u2019s evaluation benchmark, dated Sept.\u00a03, 2025, for economically valuable, real-world knowledge-work tasks. According to OpenAI, this version spans 44 widely distributed professional occupations drawn from the top nine industries contributing to the U.S. GDP, with a total of 1,320 specialized tasks in the full set and 220 tasks in the \u201copen-sourced gold set.\u201d OpenAI\u00a0says these tasks were built and vetted by experienced professionals in those fields and are intended to measure performance on realistic work products rather than narrow academic benchmarks.<\/p>\n

GDPval is intended to estimate how well models perform on work that resembles what professionals actually do, such as drafting legal briefs, preparing accounting materials, building schedules, generating diagrams and similar outputs. OpenAI\u00a0suggests it as a way to track model capability on economically meaningful tasks, not just standard benchmark questions. This means that such applications of AI\u00a0are likely to lead in implementation in the next few months because of the savings it promises to those entities that use AI\u00a0to replace previously salary-compensated humans.<\/p>\n

OpenAI\u00a0also indicates that GDPval is part of a broader effort to understand AI\u2019s labor market relevance and practical usefulness. The public overview page emphasizes that realistic occupational tasks provide a clearer signal of how models may support day-to-day professional work, while also noting limitations and future iteration. The applications are now upon us\u2014they are not merely vague speculation, rather they are near-term, cost-saving implementations that we are seeing installed today.<\/p>\n

I\u00a0asked Gemini 3 Fast Mode to address the reality so far in 2026:<\/p>\n

\u201cWe are currently in a period of \u2018Job Redesign\u2019 rather than total elimination. 91% of enterprises report that while they haven\u2019t eliminated entire departments, the nature of the roles within those departments has fundamentally changed. The primary evidence today isn\u2019t a high unemployment rate (which remains relatively stable at 4.28%), but a widening wage gap between those who can \u2018pilot\u2019 AI\u00a0and those whose tasks have been fully automated.\u201d<\/p>\n

Yet, there is evidence of which professions as well as people are more likely to persevere rather than be laid off. In a very recent Washington Post<\/em> article, Kevin Schaul and Shira Ovide write,<\/p>\n

\u201cAs artificial intelligence becomes more capable, some jobs may remain in demand while others decline. Web designers and secretaries are more at risk than janitors, according to one recent study. But there\u2019s another dimension to the picture. Some workers will find it easier to adapt, the researchers argue, based on factors like their savings, age and transferrable skills\u00a0\u2026 Women make up about 86\u00a0percent of those most vulnerable workers, the researchers said, suggesting the negative effects of automation won\u2019t be borne equally across society.\u201d<\/p>\n

An extinct occupation, telephone switchboard operators, offers some possible reasons for both hope and pessimism about AI\u2019s effects. It was once one of the most common jobs for American women, but jobs were wiped out as telephones modernized starting in the early 20th century, according to a research paper published in 2024 in the Quarterly Journal of Economics<\/em> by American professors James Feigenbaum and Daniel Gross. Switchboard operators who lost their jobs were far more likely than their peers to never find other work or to take lower-paying jobs, the research found. But within years, new opportunities opened for young women as secretarial and restaurant work boomed. \u201cI\u00a0read that as somewhat hopeful,\u201d Feigenbaum, a Boston University economic historian, said in an interview.<\/p>\n

To survive the likely disruption in needed workplace skills that is rapidly overtaking our workplaces, Gemini 3 Thinking identified four key durable personal traits:<\/p>\n