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Amid the cacophony of voices either championing the advances of genAI or warning of its power to destroy human utility, some thinkers are willing to sit with the complexity of this moment and offer nuanced thoughts. One such thinker, Tim Knowles, President of the Carnegie Foundation for the Advancement of Teaching, shared his thoughts recently in this letter published by Whiteboard Advisors. Knowles emphasizes the complicated but necessary partnership of human intelligence and AI, noting that "growing evidence—including Anthropic's own economic index — suggests that AI does not make human reasoning or quantitative thinking obsolete. In fact, it appears to do just the opposite. The ability to write clearly, think carefully, and analyze complex problems is more important than ever."
Not only do thinking skills continue to be relevant and sought by employers, they have a particular value when it comes to the growing need for genAI skills in the workplace. As this article on the 4th Anthropic Economic Index indicates, there is a statistically near-perfect correlation between the level of thinking used to create a prompt that directs a gen AI tool and the level of thinking evidenced by the resulting output. Put simply, the results are only as sophisticated as the request, creating what is referred to as a "cognitive ceiling" effect.
Rather than abdicate learning and skill building in despair over potentially being "replaced," today's students need to double down on building key durable (or transferable) skills, such as these three identified by the Carnegie Foundation: Collaboration, communication, and critical thinking. GenAI needs operators who can elevate the potential of the tools, and learners who up their own game will prove valuable to employers who need both human employees and technological tools that get the job done in concert.
What are some things coaches can do, in conversation with students, to emphasize the relevance of learning and of human intelligence and skill?
- Share the concept of the "cognitive ceiling"
- Ask them to talk about their own experiences with genAI tools and evaluate how useful they have been, noting what they do well and where they fall short
- Invite them to recount any example of "garbage in, garbage out" that might highlight the value of using quality thinking to design input and prompts
- Listen for language about feeling replaceable, like there is "no point" to learning, and ask questions that unpack the emotions and identify areas of control
- Ask them to describe a time when they have combined durable skills and genAI-specific skills, and to identify how they complemented and perhaps elevated each other
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