  Efforts to enhance education and broaden participation in AI will benefit
from a systematic understanding of the competencies underlying AI expertise. In
this paper, we observe that AI expertise requires integrating computational,
conceptual, and mathematical knowledge and representations. We call this the
``AI triplet,'' similar in spirit to the ``chemistry triplet'' that has heavily
influenced the past four decades of chemistry education research. We describe a
theoretical foundation for this triplet and show how it maps onto two sample AI
topics: tree search and gradient descent. Finally, just as the chemistry
triplet has impacted chemistry education in concrete ways, we suggest two
initial hypotheses for how the AI triplet might impact AI education: 1) how we
can help AI students gain proficiency in moving between the corners of the
triplet; and 2) how all corners of the AI triplet highlight the need for
supporting students' spatial cognitive skills.
