standards for K– 12 computing instruction developed
by the Computer Science Teachers Association, the
2017 version contains only two sentences about AI
(CSTA 2017). A growing number of teachers want
more guidance in this area, but this is a significant
challenge, given that most K– 12 educators do not
have a background in computer science or AI.
In May 2018, the Association for the Advancement
of Artificial Intelligence and the Computer Science
Teachers Association launched a joint initiative to
develop national guidelines for teaching AI in K– 12.
The AI4K12 Initiative ( AI4K12.org) is a National Science Foundation-funded project led by a four-person
steering committee (Touretzky, Gardner-McCune,
Martin, and Seehorn 2019). The AI4K12 Working
Group is composed of practicing K– 12 teachers and
AI subject-matter experts. In its first year, the working group published a list of five big ideas in AI that
serve as the organizing framework for the guidelines
(figure 1). Each big idea is unpacked into a set of concepts and subconcepts that are further expanded for
each grade band (K– 2, 3–5, 6–8, and 9–12) and then
summarized in a progression chart. Completing this
progression chart by mid-2020 is currently the major
focus of the AI4K12 Working Group. The chief aim
of this initiative is to support teachers as they engage
students in AI, and to provide guidelines that curriculum developers will choose to align their work with.
There are a number of K– 12 curriculum development efforts occurring worldwide in academia, nonprofits, and for-profit companies. Some significant
milestones in the last year were from Exploring
Computer Science, Microsoft TEALS, ReadyAI, AI4All,
the Massachusetts Institute of Technology, and the
Finnish Center for Artificial Intelligence. For example,
the Massachusetts Institute of Technology recently
released an AI + ethics curriculum for middle school
students that uses a combination of online and unplugged activities (Payne 2019). The curriculum not
only helps students learn about the technical aspects
of AI, but also helps them engage with its social and
ethical implications. One activity in the curriculum
introduces students to machine learning by having
them develop a visual classifier using Google’s Teachable Machine and then experiment with bias in training. This activity fosters discussion about sources of
bias and the ethical implications of technologies. This
curriculum has been accessed over 500 times and
is being translated into multiple languages by the
The range of AI topics students are able to explore is
closely tied to the availability of developmentally ap-
propriate tools for K– 12. Many K– 12 AI curricula make
use of materials that run the gamut from traditional
textbooks to interactive media such as Jupyter note-
books and online courseware and project-based learn-
ing opportunities that leverage student-friendly coding
platforms such as Scratch, App Inventor, and Snap!. A
number of these platforms integrate commercial cog-
nitive services, AI tools, and datasets developed by
university or corporate research laboratories to provide
user-friendly tools for K– 12 students. Cognimates and
Machine Learning for Kids combine IBM Watson’s
AI services with Scratch. Teachable Machine by
Google’s Creative Lab trains custom visual classifiers.
The Massachusetts Institute of Technology’s App Inven-
tor leverages the Amazon Alexa Toolkit to provide con-
versational AI tools for mobile app development. In
addition to these hands-on computer-based activities,
unplugged activities such as Socratic seminar, team-
based paper prototyping, and creative writing exer-
cises also have value for promoting AI literacy.
Given the impact of AI technologies on different
industries and society at large, future AI curricula
and tools need to incorporate curricular goals of sci-
ence, mathematics, social studies, humanities, and
the arts. To ensure that AI instruction is accessible
and developmentally appropriate for all students,
curriculum and tool development efforts need to be
iterative, collaborative processes that involve active
participation among all stakeholders, including de-
velopers, teachers, and the students themselves.
Since the launch of AI4K12, we are seeing the
growth of a new K– 12 AI Education Community con-
sisting of AI researchers, computer science education
researchers, K– 12 teachers, and curriculum develop-
ers. The biggest factor in the growth of the US K– 12
teacher community has been the rollout of a teacher
professional development course on AI from the
International Society for Technology in Education.
Joseph South, International Society for Technology
in Education’s chief learning officer, reports that as
of September 2019, over 560 K– 12 educators have
completed the course. We anticipate similar growth
globally as we are aware of parallel efforts to develop
capabilities in K– 12 AI Education in numerous other
countries, including China, Finland, the United
Kingdom, Canada, Turkey, Portugal, South Korea,
and Argentina. We hope to see continued growth of
this community and to leverage the expertise of AI
researchers in collaboration with teachers to produce
much-needed resources for K– 12 AI education.
Looking to become involved in K– 12 AI education? Join the AI4K12 mailing list (see AI4K12.org
for the subscription link). Develop online tools and
demos for making AI concepts accessible to the K– 12
audience. Volunteer at your local school to help
teachers and students explore AI.
CSTA. 2017. The CSTA K- 12 Computer Science Standards.
Chicago, IL: Computer Science Teachers Association. www.
Payne, B. H. 2019. AI+Ethics Curriculum for Middle School.
Cambridge, MA: MIT Media Lab. www.media.mit.edu/
Touretzky, D. S.; Gardner-McCune, C.; Martin, F. L.; and
Seehorn, D. 2019 Envisioning AI for K-12: What Should
Every Child Know about AI? In Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 9795-9.
Palo Alto, CA: AAAI Press. doi.org/10.1609/aaai.v33i01.