Susan Wojcicki argues the underrepresentation of women in tech starts long before college. By making coding a mandatory subject for all middle schoolers, like math or reading, it normalizes the skill and creates a universal baseline of knowledge. This prevents it from becoming an elective that primarily attracts students already inclined towards it.

The education system is fixated on preventing AI-assisted cheating, missing the larger point: AI is making the traditional "test" and its associated skills obsolete. The focus must shift from policing tools to a radical curriculum overhaul that prioritizes durable human skills like ethical judgment and creative problem-solving.

College Board surveys revealed a fundamental disconnect between educators: high school math teachers believe every topic matters and race through broad curricula, whereas college professors prioritize deep fluency in very few core concepts. College professors emphasize that students need absolute command over basic arithmetic, fractions, rates, proportions, and linear equations, noting that deficiencies in these foundations cannot be easily remedied in college courses.

Scaling high school data education does not require an immediate, massive retraining of teachers to become expert statisticians. David Coleman emphasizes that education is often most engaging when the instructor learns alongside their students. Structuring courses around active inquiry and collaborative experimentation allows teachers and students to discover analytical insights together without requiring years of prior statistical expertise.

Instead of relying on arbitrary time-based measures like credit hours, schools can implement performance-based assessments. For example, some schools hold "defenses of learning" where students publicly present and defend their work to community members, fostering active demonstration of skills over passive memorization and increasing community accountability.

The modern American high school math curriculum was designed after the launch of Sputnik to prepare a workforce for manual military and scientific calculations before modern computing existed. Jo Boaler argues that schools continue to teach antiquated procedural methods by hand that students will never perform again, rather than cultivating the creative and flexible problem-solving abilities that computers cannot replicate.

To remain relevant, universities need a radical overhaul. Economist Tyler Cowen suggests dedicating one-third of higher education to teaching students how to use AI. The remaining two-thirds should focus on fundamental skills like in-person writing instruction and practical life skills like personal finance.

When economist and former teacher Sally Sadoff tasked ninth graders with collecting real-world data and computing linear regressions, previously disengaged students excelled by investigating topics tied to their personal identities. Allowing students to collect and analyze data relevant to their own lives bridges the gap between abstract mathematical procedures and practical utility, sparking genuine student engagement.

The curriculum prioritizes easily testable, obsolete math skills over practical, modern concepts like estimation and optimization. This is because standardized tests favor single-answer questions over creative problem-solving, creating a system that teaches what is convenient, not what is valuable.