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White House commemorates #CSEdWeek, and calls for AI education across the country.
DS4E's Director Zarek Drozda joins an assembly of educators and advocates at the White House for CSEdWeek.
On December 5, Data Science 4 Everyone joined a White House convening commemorating #CSEdWeek and calling for education on the fundamentals of AI for students everywhere.
This year marks the tenth anniversary of the first Presidential call for Computer Science education in K-12, following a viral video from Code.org in 2013 entitled “What Most Schools Don’t Teach,” featuring President Obama alongside many tech founders, from Jack Dorsey to Bill Gates, and even celebrities like Will.I.Am of the Black Eyed Peas. That momentum eventually led to the 2016 launch of CS for All, built upon even earlier work for Computer Science Education Week beginning in 2009 through the joint efforts of ACM, CSTA, the National Science Foundation, and bi-partisan Congressional support.
CSEdWeek has since grown year-over-year, with hundreds of organizations joining in and served as the incubator for the now global “Hour of Code.” The week also coincides with the birthday of the late Grace Hopper — one of the first computer programmers and inventor of the first compiler who coined the term “bug.” You can read more about the rich and ongoing history of CSEdWeek here.
Now enter generative AI.
While AI technology such as neural networks have existed since the 1960s, these systems suddenly become powerful when powered by massive amounts of training data; data that spans the internet and nearly all digitally recorded human interactions.
Overnight, tools like ChatGPT galvanize the public, make technology hidden behind the scenes incredibly visible, and growing the public user-base 250X faster than Netflix. In the best-case scenario world, AI has the potential to transform economies, replace work that is unsafe or unpleasant for humans, and rapidly advance scientific and empirical research. In the worst-case scenario, AI has the potential to widen the digital divide, disrupt our economic fabric, and further entrench systemic harms through biased data and algorithms.
Ami Fields Meyer, Senior Policy Advisor to Vice President Kamala Harris, stated this perfectly: “There can be extraordinary outcomes [from AI] that people in this room know, which comes from the ability to solve problems at scale. Those exact same outcomes can be done negatively, at scale.”
In any scenario, education about AI (or lack thereof) will determine the outcome — including who gets to participate, who it benefits, and how it is applied.
Charity Freeman, Chair of the CSTA Board of Directors
If we continue marching toward an AI-powered world, all students will need to be equipped with at least some foundations of AI and the many other emerging digital technologies. Whether pursuing entry-level careers in healthcare or manufacturing, engaging in advanced research, or building the AI systems of tomorrow, today’s students are more likely to affect the outcome, both for our country and others.
Karen Marrongelle, Chief Operating Office of the National Science Foundation, shared, “We need an AI savvy workforce, and we need to start today, to support 21st century workforce development, ensure our national competitiveness, and our national security.”
Students need to know the limits of AI tools, how they operate, and when (and why) they make mistakes. We will build a better future if we can all harness this technology with confidence rather than simply respond to it.
Data is critical to that mission.
Chirag Parikh, Executive Secretary of the National Space Council and Deputy Assistant to the President, shared that, “we included both the Secretary of Education and Secretary of Labor in the National Space Council, because this is about the future space workforce… there are huge amounts of data coming down from our space equipment and observations — petabytes of data coming down daily — whether used to explore space or fight the climate crisis. How do we make that data useful? It’s not just computer scientists, it’s everyone that needs to be prepared. We need a diverse workforce to make this a reality: scientists, software engineers, machine learning experts — AI is a broad umbrella that needs a lot of work, from efficient data conditioning to data management, and [with diverse applications] from crew transfers to autonomous equipment to more efficient transfer of data back to earth.”
Teachers are showing what’s possible.
Nora Burkhauser, a Computer Science Teacher in Montgomery Blair High School, shared that “high schools are already learning about AI in my classroom. It is possible.” Students are “excited about learning AI and very excited to do AI projects — they collect the data, train the model, and then I frequently remind them “what problem is this solving?”
Today, 57% of high schools nationally now offer computer science programs, yet student enrollment numbers are still unfortunately hovering in the single-digits (5.8% as of 2023). During the same period, the power of “big data,” internet of things, artificial intelligence, and other emerging technologies were concurrently transforming both industry and everyday life outside of the classroom.
Jake Baskin, Executive Director of CSTA
Technology is quickly accelerating, just as our education system is struggling the most.
Daaiyah Bilal-Threats, of the National Education Association, reminded the group that “there are school districts right now that are 100% staffed with emergency substitute teachers,” due to teacher shortage and retention issues in many communities acorss the country.
How do we create opportunities for students to learn how AI works, within a K-12 system that is facing record learning loss in existing school subjects, teacher shortage and retention challenges, and an engagement gap of only 5% of students in computing courses?
This systematic challenge cannot fall on computer science teachers alone.
We need to continue building the momentum to grow CS access and participation nationally — and invest like we say that it matters — but we also need to quickly broaden the focus, and leverage the teachers and capacity we already have in the other five or seven school subjects. Nor should we expect our existing CS educators to cover every emerging technology under-the-sun each year. The data is proving we need to engage students in these subjects through more avenues. If we truly want to diversify technology users and builders, we need to meet students where they are at: with diverse subjects and interests, whether in biology, history, or economics.
Krystal Chatman, Instructional Technology Specialist for Jackson Public Schools and CSTA Equity Fellow, emphasized the importance of “the cross-curricular conversation, it can happen in math or social studies. Understanding the limitations and how things work, how things can be harmful, that is a job for many disciplines.”
It must be accessible, regardless of a students’ identity or interest.
Gina Fugate, Maryland School for the Blind, shared “My students love AI, and it’s because they feel included. I have students who aren’t allowed to take Computer Science courses. It’s not because the disability stopped them. It’s because the disability made others think they weren’t able to participate. How can we make sure that my students can jump back in through AI?”
Margaret Martorsi, Associate Director, National Science Foundation Directorate for CISE (Computer and Information Science and Engineering), shared that “AI is deeply rooted in CS, but also needs to be broader. Neither ignoring CS foundations nor ignoring its broader disciplines would make any sense. This is big; and in order to benefit students around the country; it will take a lot of people and resources.”
Tom Berry of Amazon noted that “NGSS has data science in it. Students are excited to learn data and navigate projects that include computing. We can be a value-add; and students can find a window into the future and a mirror of themselves back in many areas.”
AI education should not be exclusively about developing more AI tools and technologies; that will happen. AI education should also arm the public with the skills to navigate an increasingly algorithmic landscape that will govern major aspects of their lives (with or without their knowledge), both in their career and in daily life. That begins with knowing the input and output of these systems, and questioning that data rigorously.
We spent the past decade building a 21st-century school subject. Now we need to go back to the rest of the school curriculum, and identify ways to modernize them, with specific interventions aligned to the discipline — whether math, biology, history, or computer science itself — to capture every student and ensure they are ready. That way, everyone will be able to truly participate in the AI future.
We thank Dr. Thema Monroe White and Sean Sukol for informing the perspectives in this summary article.