The Role of Natural Language Processing in AI: The Power of NLP
Intelligent Classrooms: What AI Means For The Future Of Education
Our young people are leading the adoption and advancement of these new technologies.
gettyArtificial intelligence is changing the world.
The world's attention is now fixed on the unfolding impact of Generative AI tools on knowledge and creator economies. Schools, serving as the very epicenters of knowledge and creative work, may well be the first place the broader public sees tangible change take shape.
Leaders and visionaries the world over are actively advancing the applications of this rapidly developing technology. The pace of progress is measured in days and weeks, rather than months and years, and it's only getting faster. The quickening of AI's capabilities and applications mean that its potential impact, both good and bad, is growing rapidly.
Already, we can see around the corner that generative AI systems will have expansive implications for how schools function, teachers work, and how students develop personally and professionally for tomorrow's world of work.
As is so often the case, our young people are leading the adoption and advancement of these new technologies. The term "digital native" already seems outdated as Gen Z and those that follow them will invariably be expert in these new technologies faster than many adults. Seeing youth as experts with real understanding and knowledge can open new and exciting use cases and applications for new technologies like generative AI.
Applying the power of AI to some of our greatest challenges in school and system design offers similarly incredible opportunities. It's already helping teachers design courses and analyze data of student performance to engineer learning interventions and new lesson plans. But its potential to do more is clear. It could help us better know how the school day and all the learning experiences contained therein should look given the rapid evolution of the global economy. It could aid states and districts in developing new career pathways and structures for lifelong learning that keeps people connected to gainful employment across decades.
There is a sense, among many, that these technologies are pushing toward new horizons and opening us to futures both new and powerful. That group includes those pushing the leading edge forward, like Sal Kahn, CEO and Founder of Khan Academy.
"We're at the cusp of using AI for probably the biggest positive transformation that education has ever seen," he said during a recent TED Talk. "And the way we're going to do that is by giving every student on the planet an artificially intelligent but amazing personal tutor. And we're going to give every teacher on the planet an amazing, artificially intelligent teaching assistant."
That would be a seachange in education if only because such personal learning and teaching supports are now profoundly expensive. To address pandemic learning loss, the federal government spent some $190 billion itself, with many state and local jurisdictions adding to that total. But, if we see the future as the Sal Kahns of the world do, massive funding infusions may not be necessary to provide customized and personalized learning experiences for every learner. Intelligent agents can already play the role of tutor and are likely to be more and more effective as the technology advances.
This ambitious and optimistic perspective, Khan says, must be balanced by an all out effort to thwart the negative, even dangerous possibilities with advanced AI, saying that all must "fight like hell for the positive use cases."
Fears more broadly about AI include everything from potential job loss to losing control over lethal military capabilities. The national concern has grown to the point that OpenAI's CEO Sam Altman was recently called to testify before the U.S. Congress and meet with lawmakers about the technology's rapid growth. Altman himself urged the creation of new legal frameworks to keep pace with the new technology.
Worry about AI's deleterious effects on education specifically are also spreading. New York City Public Schools effectively banned the use of the most popular forms of the technology, ChatGPT, out of fears of student cheating. New York isn't alone. Many K-12 school systems and institutions of higher learning are taking a defensive posture.
Experts in the field say the strategy of banning or blocking the technology could have unintended consequences of its own. The vast majority of successful companies and organizations will be using AI in their work, and seeking applicants that know how to leverage its power to increase productivity. Banning AI in schools could therefore reinforce digital inequities, the digital divide, and ultimately opportunity gaps.
"Many school systems decided to ban it," Code.Org CEO Hadi Partovi recently told CNN. "In New York City where the public school system has banned it, private schools are teaching AI prompt engineering. We have to find a middle ground to safely include it in how and what we teach."
That call to a rational middle ground is both reasonable and appropriate given the awesome potential that generative machine learning offers educators, leaders and students. We should not only think about how technology can assist teachers and learners in improving what they're doing now, but what it means for ensuring that new ways of teaching and learning flourish alongside the applications of AI.
"Technology offers the prospect of universal access to increase fundamentally new ways of teaching," said Graduate School of Education Dean Daniel Schwartz at a recent AI and education conference.
Indeed, teachers are already early adopters of the technology. Some 30 percent of teachers are now using AI to develop lesson plans, according to Hadi Partovi, Code.Org. Pandora's box appears to be open, but that doesn't mean we lack agency and capacity to shape the effects of that fact. And it doesn't mean that we're headed to a future where AI replaces professional human educators. In fact, it could well mean that highly trained and capable teachers are even more important facilitators of learning in an AI-enabled academic environment. But we need to act now.
Teachers need professional development specifically on AI and its productive applications. Teachers will need "pedagogical content knowledge specific to AI," Daniela Ganelin, a Stanford researcher and doctoral student, told Education Week. They'll need to understand the technology to fully grasp its potential and applications in the classroom.
With appropriate development and support, routine and time-intensive tasks in the classroom can be outsourced to intelligent agents and human teachers can focus on the deeply relational work of higher-level instruction, as UK Education Secretary Gillian Keegan recently noted. Formative assessment, an essential evidence-based tool in every effective educator's toolbox, can be made even more real-time with responsive instruction plans and learning sequences adapting instantly to the specific state of a student's learning journey.
Students too will need to learn and understand the technology. With the assistance of capable and knowledgeable educators, they will likely leverage these tools in ways that we cannot even imagine at present. With the right scaffolding around them as young learners with powerful technology, they can thrive alongside and amidst the rise of intelligent machines. And critically, we will need to provide that opportunity to all learners–failure to do so will only entrench inequities and widen gaps in novel ways.
Our northstar must always be the democratization of learning opportunities as we bring the fruits of technological innovation to our classrooms and well beyond them. There will be challenges, to be sure, but the power of human ingenuity to mitigate those challenges is just as real and equally powerful.
In this new era of learning—and make no mistake about it, that is exactly what we are entering—we will, however, need an approach to the deployment of AI in education that is centered on real human flourishing.
Doing so will not only strengthen student learning, but ensure that future generations thrive in ever more human and humane ways. That's the kind of tomorrow in which all of our children and our planet can thrive.
The Future Of Artificial Intelligence In Education
Our world as we know it is running on artificial intelligence. Siri manages our calendars. Facebook suggests our friends. Computers trade our stocks. We have cars that park themselves, and air traffic control is almost fully automated. Virtually every field has benefited from advances in artificial intelligence, from the military to medicine to manufacturing.
However, almost none of the recent advancements in artificial intelligence have advanced the education industry.
Woolf, et al., (2013) proposed some "grand challenges" that artificial intelligence in education should work to address, including:
Over the last decade, applications of artificial intelligence have addressed several challenges of learning, including language processing, reasoning, planning, and cognitive modeling (Woolf, 2009). Known as Intelligent Tutor Systems, computer software is able track the "mental steps" of the learner during problem-solving tasks to diagnose misconceptions and estimate the learner's understanding of the domain. Intelligent Tutor Systems also can provide timely guidance, feedback and explanations to the learner and can promote productive learning behaviors, such as self-regulation, self-monitoring, and self-explanation. Furthermore, Intelligent Tutor Systems can also prescribe learning activities at the level of difficulty and with the content most appropriate for the learner (Azevedo & Hadwin, 2005; Shute, 2008; VanLehn, 2006). These systems are also able to mimic the benefits of one-to-one tutoring, and some of these systems outperform untrained tutors in specific topics and can approach the effectiveness of expert tutors (VanLehn, 2011). Noteworthy examples of these intelligent tutor systems include Tabtor, Carnegie Learning and Front Row. A meta-analysis comparing learner outcomes using Intelligent Tutor Systems to learner outcomes using other instructional methods found that over a wide aware of conditions, learning from Intelligent Tutor Systems led to higher outcome scores (Ma et al., 2014).
In another application to learning, artificial intelligence can help organize and synthesize content to support content delivery. Known as deep learning systems, technology can read, write and emulate human behavior. For example, Dr. Scott R. Parfitt's Content Technologies, Inc. (CTI) enables educators to assemble custom textbooks. Educators import a syllabus and CTI's engine populates a textbook with the core content.
Progress in artificial intelligence and machine learning has been impressive, but there is still much work to be done to advance learning science. While some progress is being made to bring artificial intelligence to the education space as described above, these efforts pale in comparison to advancements in the non-education space. Most of the exciting breakthroughs in 2015 were in fields outside of education. For example, companies such as Amazon and UPS have been piloting the use of drones to deliver packages and other goods to customers. Google recently purchased an AI software company, DeepMind, from a British startup for half a billion dollars. Google has dedicated more than 140 computer scientists to DeepMind, and the software recently taught itself how to play 49 retro video games so well that it consistently outperforms human players. Google has also been testing its driverless cars. PR2, a robot from Cornell University, learned how to perform various small tasks, and then "taught" Baxter, another robot from Brown University, how to perform the same tasks in an alternate setting. Another robot, ConceptNet 4, took an IQ test with tasks in vocabulary, comparisons and comprehension and was found to have the intelligence of a 4-year-old.
(Chaudhry, et al., 2013). (For more information about the potential for artificial intelligence in these areas, check out a recent special issue of AI Magazine.)
The possibilities for artificial intelligence to make significant contributions in any field are tremendous, and education shouldn't be left behind.
Is Early Childhood Education Ready For AI?
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Interest in artificial intelligence has surged among K-12 and college educators, who are looking at ways it can be used to support both students and teachers. But in the early childhood arena, those discussions are still in the beginning stages. I asked Isabelle Hau, the executive director of Stanford Accelerator for Learning, to share about the potential benefits and challenges of AI in early learning. Our conversation below is edited for length and clarity.
Interest in AI has obviously surged the past couple of years in K-12, for both teachers and students. With early childhood, the use of AI may be a little less obvious. Have you noticed that trend in early childhood classrooms — are teachers interested in using AI or teaching about it?
Hau: I'm observing some activity in a few areas. One is interest in novel forms of assessment, or assessment areas that have been a big pain point for early childhood teachers for a long time, because observational assessments take a long time. There are some innovations that are starting to materialize in making assessments less visible, or invisible maybe, at some point. So discussion around how to leverage, for example, computer vision or some form of voice inputs in classrooms, or some gamified approaches that are AI-based.
Are there any specific ways you're seeing AI technology emerge in early childhood classrooms?
Hau: At Stanford, we have one super interesting project that is not necessarily in a classroom but could be in a classroom context. It's a tool my colleague, Dr. Philip Fisher, has developed called FIND that looks at child-adult interactions and takes video of that interaction. It is very expensive for humans to look at those videos and analyze the special moments in those interactions. Now, artificial intelligence is able to at least take a first pass at those interactions in a much more efficient manner. FIND is now an application for early childhood educators; it used to be mostly for parents, initially.
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Two of my colleagues, one in the school of medicine and one at the school of education, have partnered to build Google Glasses that children with challenges recognizing emotions can wear. And based on the advances that are happening with AI, especially in the area of image recognition, the glasses that young children can wear help them detect emotions from adults or other young people they are interacting with. Feedback, especially from parents and families of young children, is quite moving. Because for the first time, some of those young kids are able to actually recognize the emotions from the people they love.
Others have been working on language. Language is a complicated topic because we have, in the U.S., more and more children who speak multiple languages. As a teacher, it's very complicated. Maybe you're bilingual or trilingual at best, but if you have a child who speaks Vietnamese and a child who speaks Mandarin or Spanish, you can't speak all of those languages as a teacher. So how do we correctively support those children with huge potential to thrive when they may not be proficient in English when they arrive in this classroom? Language is a really interesting use case for AI.
When you look up AI tools or products for early educators online, a lot comes up. Is there anything you would be cautious about?
Hau: While I'm excited about the potential, there are lots of risks. And here we are speaking about little ones, so the risks are even heightened. I'm excited about the potential for those technologies to support adults – I have a lot of questions about exposing young children.
For adults, where it's very confusing right now is privacy. So no teacher should enter any student information that's identifiable in any of those systems, especially if they are part of a district, without district approval.
That information should be highly private and is not meant to go in a system that seems innocuous but is, in fact, sharing information publicly. There are huge risks associated with that, the feeling of intimacy for a system that doesn't exist. It's a public place.
And then one concern is on bias. We've done some research at Stanford on bias sentiments in those systems, and we have shown that systems right now are biased against multilingual learners. I can see that myself, as a non-native English speaker. When I use those systems, especially when I use voice, they always mess up my voice and accent. These biases exist, and being very mindful that they do. Biases exist everywhere, but certainly they do exist in [AI] systems. And we have proven this in multiple ways. And then I also have huge concerns on equity. Because right now some AI systems are paid, some are free.
Are there any other ways you could see AI used to fill a need in early childhood?
Hau: Right now, a lot of parents are struggling to find care. You have people who are providing care – it could be center, it could be home-based, nanny, preschool, Head Start, you have all these different types. And then you have families. It's a mess right now – the connection between the two. Of course it's a mess because we don't have enough funding, we don't have enough slots, but generally, it's a mess. This is an area that, over time, I'm hoping there will be better solutions
If I want to dine tonight at a restaurant in Palo Alto, this is really easy. Why don't we have this for early childhood? 'I'm a low-income parent living in X, and I'm looking for care in French, and I need hours from 8 to 5,' or whatever it is. It would be really nice to have [technology] support for our millions of parents that are trying to find solutions like this. And right now, it doesn't exist.
Do you have any tips for teachers who want to learn more about AI programs to use in class?
Hau: For safety, in particular, I really like the framework the EdSAFE AI Alliance has put together. It's mostly oriented toward K-12, but I think a lot of their accommodations on when is it OK to use AI and when it is not are very clear and very teacher-friendly. There are some great resources at other organizations, like TeachAI or AI for Education, that I really like. At Stanford, we partner with those organizations because we feel like this is an effort that needs to be collaborative, where research needs to be at the table. We need to build coalitions for effective and safe and equitable use of those technologies.
This story about AI in early education was produced by The Hechinger Report, a nonprofit, independent news organization focused on inequality and innovation in education. Sign up for the Hechinger newsletter.
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