AI Has Not Broken Education, It Has Exposed It
In this opinion piece, Santiago Schnell argues that generative artificial intelligence has not destroyed the education system but rather revealed its long-standing flaws. For years, universities have prioritized performance, fluency, and the appearance of mastery over genuine understanding and deep thinking. Assessment systems were designed to evaluate final products as evidence of learning, a method that worked until AI made it possible for students to produce elaborate work in minutes without actual comprehension. Schnell illustrates this with an anecdote about a student who could not explain the logic behind an AI-generated draft, highlighting the separation between fluid output and critical thought. The author contends that while AI excels at synthesizing existing knowledge, it cannot replicate the human acts of noticing anomalies or asking novel questions. These cognitive processes are essential for training judgment, not just producing results. Consequently, the rise of AI forces educators to confront why they previously accepted superficial metrics of learning. The article calls for a shift in educational focus from delegable tasks to the cultivation of unique human intellectual capabilities, urging institutions to stop pretending that product-based assessments measure true learning.
Wire timeline
AI Has Not Broken Education, It Has Exposed It
In this opinion piece, Santiago Schnell argues that generative artificial intelligence has not destroyed the education system but rather revealed its long-standing flaws. For years, universities have prioritized performance, fluency, and the appearance of mastery over genuine understanding and deep thinking. Assessment systems were designed to evaluate final products as evidence of learning, a method that worked until AI made it possible for students to produce elaborate work in minutes without actual comprehension. Schnell illustrates this with an anecdote about a student who could not explain the logic behind an AI-generated draft, highlighting the separation between fluid output and critical thought. The author contends that while AI excels at synthesizing existing knowledge, it cannot replicate the human acts of noticing anomalies or asking novel questions. These cognitive processes are essential for training judgment, not just producing results. Consequently, the rise of AI forces educators to confront why they previously accepted superficial metrics of learning. The article calls for a shift in educational focus from delegable tasks to the cultivation of unique human intellectual capabilities, urging institutions to stop pretending that product-based assessments measure true learning.
elpais