No Baselines for an AI World

Two worthwhile no baselines articles appeared in The Wall Street Journal written by Freakonomics author Steve Levitt and Grow with Google Lisa Gevelber (click image below).  Their insights do not treat AI as a distant trend or a marginal efficiency gain. Instead, they frame AI as a present-day structural shift that is already reshaping education, work, and how people build long-term value in their lives and careers.

What makes the perspective out of the box is the focus on systems rather than tools. Levitt and Gevelber are not arguing about which AI model is best or how to optimize workflows. The conversation moves away from innovation theater and toward the deeper question of what education must become when information is abundant and automation is unavoidable.

The articles are also unconventional in how they assign responsibility. Rather than placing the burden solely on individuals to “keep up,” they challenge universities, employers, and public institutions to rethink their roles. Education is presented as continuous, modular, and adaptive, not something completed early in life and referenced forever. This directly questions legacy systems built around fixed degrees, slow curricular change, and static definitions of preparedness.

Finally, Levitt and Gevelber emphasize judgment, curiosity, and adaptability over narrow technical expertise. The argument is that in an AI-driven world, value comes less from memorized knowledge and more from asking better questions, making better decisions, and continuously recalibrating. That mindset is what makes these articles genuinely out of the box: they reject finish lines, rigid benchmarks, and one-time credentials in favor of lifelong learning and constant reinvention.