Here’s what you need to know about AIEDU’s Forum on AI Education
Last week, The AI Education Project (AIEDU) hosted a virtual gathering of more than 100 leaders from government, K12 education, academia, and civil society for a conversation about how we can bring AI education to K12 schools. Our Forum on AI Education and Workforce Readiness aimed to identify concrete steps that these stakeholders can take to equip schools with distinct curricula that addresses the many ways that artificial intelligence will impact students, especially with regard to jobs and the Future of Work. We’ve included recordings of the event, along with an overview of some of the most important points below.
We encourage you to take a moment from your day to watch at least part of the video—but below are some of moments and discussions from the Forum:
Talking Workforce Transformation with Ohio’s Lt. Governor
Ohio Lieutenant Governor Jon Husted
The meeting opened with remarks from Ohio Lieutenant Governor Jon Husted, who leads the state’s InnovateOhio Initiative and also oversees the Governor’s Office of Workforce Transformation. Lt. Gov. Husted spoke about the state’s work to help people gain the skills they need to participate in the economic success that technology will bring forth.
“There is a huge divide in access, both educationally and in terms of being able to participate in the modern economy, education system, and healthcare system. We have the opportunity and responsibility to help bridge those divides and educate people,” said Husted. “We have to get the proper incentives in place—this is why we are paying our high schools and career and technical education centers to equip people with the in-demand industry credential skills that are needed in the innovation economy.”
Husted pointed to TechCred—an Ohio grant program which reimburses employers for industry-recognized, technology-focused, credentialed training programs and certificates—as an example of what this looks like on the ground. Ohio met its goal to authorize 10,000 industry credentials within the first year of the program’s launch, covering the cost of short-term learning programs across multiple sectors. Educational institutions are responding by setting up learning programs in response to this demand.
Ohio has also allowed high school students to apply Computer Science credits towards their foreign language graduation requirements. Husted says this is one example of the ways states can begin to shift their education systems to adapt to the new demands of the 21st century economy.
A Conversation with Code.org CEO Hadi Partovi
Hadi underscored that we are in a unique moment in time at which it is critical to educate students about artificial intelligence.
“In particular, the rise of machine learning using neural networks enables us to pattern match and do basic recognition tasks much more easily than before. When I was in college, AI used to be a theoretical technology, whereas now you can train a neural network within seconds to recognize a smile, emotions, objects, and more,” said Hadi. “Whether it’s speech recognition, computer vision, natural language processing, weather prediction, medical diagnosis, crop optimization, these are so many different applications of the exact same technology.”
Over the next 10–20 years, the changes that machine learning will bring to society will be as significant as when the internet or the computer were invented—and for each of those technologies, our education system had to give students a basic introduction about how to use the technology.
“In the 1950s schools didn’t have computer education classes because the technology didn’t exist. That all changed in the 1980s and 90s. And machine learning is as foundational—the only difference is that it isn’t something that you can touch or feel like a computer or device that you can hold in your hand. It’s an approach.”
Hadi Partovi donned his characteristic Code.org baseball cap, and shared details of his nonprofit’s new AI modules, launched earlier this month.
When asked about whether it is too early to begin talking to students about AI’s ethical and logistical challenges that they might encounter as users, workers, and citizens, Hadi warned, “you could almost argue it is too late.”
A fireside with two leading women in technology education
The Forum’s plenary session closed with a two-way fireside chat moderated by Emily Tate of EdSurge with Tarika Barrett, Chief Operating Officer at Girls Who Code, and Ora D. Tanner, AIEDU’s Chief Learning Officer.
Tarika emphasized one of the challenge facing the field of Computer Science: women make up only 26% of all computing jobs. For women of color, they make up only 5% of those jobs. We also know that these jobs are among the highest paying and fastest-growing in the country. The solution? Increase accessibility, cater to young women and girls, and showcase other women role models in the field.
“We need our girls—all of our girls—to be equipped for these jobs, and ensure they are welcomed into the technology industry,” said Tarika.
Ora built on this, citing a World Economic Forum report that predicts AI will eliminate 75 million jobs by 2022.
“But if you drill down in those numbers, women and people of color are overrepresented in the jobs that are most at risk of being replaced. Hispanic, Black, Indigenous workers face on average an automation potential that is well above their White and Asian counterparts. If you look at the intersectionality of that, they are right at the center of the negative impacts that the technology is predicted to have on our economy. We feel an urgency.”
The Forum’s capstone plenary featured three women working at the center of education innovation in the U.S.
The Forum’s capstone plenary featured three women working at the center of education innovation in the U.S.
Ora also spoke about the fact that AI systems are already having disproportionate effects on women, people of color, and people in low-income communities due to algorithmic bias and other failures of the still nascent but fast-growing technology.
“In 2019, for the first time ever, the majority of K12 students in public schools were non-white. This has implications for increasing the relevance of the curricula we develop to address their diverse needs,” said Ora. “We centered the students in our design process—beyond race and gender, we considered the beliefs and values of Gen-Z. Also, because we launched in the midst of COVID-19, we had to consider situational factors including parental supervision and access challenges. Culturally relevant pedagogy is an important part of what I like to call our ‘pedagogy stack.’
Ora pointed to a passion for social justice issues as one of things that Gen-Z gravitate toward, and a key feature of AIEDU’s curriculum.
Emily also asked about the challenges that the coronavirus pandemic has created for education nonprofits.
“Students from minority and low-income communities are routinely left behind, and the pandemic has only made that more clear,” said Tarika. “When schools closed their doors this past March, they did so leaving as many as 12 million without access to WiFi. We didn’t give much thought or weren’t prepared to support the 1.4 million students who are actually caregivers—they have these responsibilities, and most of them are girls. Days turned into weeks, which turned into months, and over time fewer and fewer public school students attended their online classes as compared with their private school peers.”
Girls Who Code responded quickly, shifting from in-person instruction to online learning within a matter of weeks, employing a blend of virtual courses and asynchronous instruction that allowed them to reach 5,000 girls. They also raised funds to get girls the necessary hardware and hotspots to address the technology gap.
A question, and a brainstorm for the leaders in attendance: how can we advance AI education?
The latter half of the Forum broke the group of 130+ experts into groups of roughly twelve to discuss a central question for the event those in attendance—how can we scale AI education to the underserved communities which sit on the front lines of the economic transformation being ushered in by artificial intelligence?
Such a project requires a multi-sector, multi-disciplinary approach; and this was reflected in the diverse makeup of these brainstorm groups. Participants included Fortune 500 CEOs, congressional legislative directors, university deans, high school administrators, AI experts, and industry experts. The conversations were varied, but all of them landed on two central themes:
We must find ways to incentivize educators to bring AI-related content into classrooms. Ensuring AI education reaches all students (and not just those naturally curious about technology) is an equity challenge that will require buy-in from stakeholders at all levels of education in the U.S. Motivated teachers shouldn’t be expected to be advocate to building and district administrators in order to bring AI literacy to their students.To address this, participants suggested creating new K-12 learning standards which address AI and digital literacy, providing more resources and funding for professional development and teacher credentialing, and creating cross-curricular AI content that fits into established standards in other subjects like Math, History, English, and especially Career & Technical Education (CTE).
AI curriculum must engage students across career interests, and be relevant to their lived experiences. Given the potential for artificial intelligence to impact nearly every sector of the economy, AI education should cultivate a diverse set of entry points for students. Participants suggested that offering non-technical curricula about AI, focusing on its economic, societal, and ethical impacts, could spark interest in students beyond those already compelled to pursue careers in STEM. This would help to address some of the core equity and accessibility for students from underrepresented communities. Discussions also highlighted the importance of project-based learning and career exploration with a focus on case studies that illustrate human-computer interaction across a variety of fields.
