AI & Education Policy

AI is recomposing jobs, not erasing them Throughput with judgment beats years of experience Schools and employers must teach, verify, and hire for AI-literate workflows Between 60% and 70% of the tasks people perform at wor

Students already use AI for writing; literacy must mean transparent, auditable reasoning Redesign assessment to grade process—sources, prompts, and brief oral defenses—alongside product Skip detection arms races; provide approved tools, disclosure norms, and teacher training for equity

AI is collapsing routine “middle” software work as adoption soars Schools must teach systems thinking, safe AI use, and verification-first delivery Employers will favor small, senior-led teams; therefore, curricula must reflect this reality

AI excels on known paths, so schools must shift beyond procedure Assessments should reward framing and defense under uncertainty This prepares students for judgment in an AI-driven world Every era has its pivotal moment.

AI doesn’t make students “dumber”; low-rigor, answer-only tasks do Redesign assessments for visible thinking—cold starts, source triads, error analysis, brief oral defenses Legalize guided AI use, keep phones out of instruction, and run quick A/B pilots to prove impact

AI use is ubiquitous; current assessments reward fluency over thinking Grade process, add brief vivas, and require transparent AI-use disclosure Train teachers, ensure equity, and track outcomes to make AI a partner Eig

LLMs are not conscious, only probabilistic parrota They often mislead through errors, biases, and manipulations Education must use them as tools, never as advisors