In recent years, the field of education has witnessed a remarkable transformation with the integration of artificial intelligence (AI). AI refers to computer systems that can perform tasks requiring human intelligence, such as learning and decision-making. Machine learning, deep learning, and natural language processing are some techniques used in AI.
According to an annual Council of Chief State School Officers (CCSSO) survey among state education CIOs and CTOs, AI frameworks and uses rank above all other priorities related to digital infrastructure. Specifically, these leaders are looking for ways AI can be used as a productivity tool within the state education agency (SEA) in addition to frameworks that would guide and support AI’s advancements in the classroom.
A look at AI’s progress
AI dates back to the mid-20th century, with the emergence of electronic computers. Over the years, AI has evolved, with advancements in machine learning algorithms, expert systems, computer vision, natural language processing, and robotics. Today, AI has applications in various industries, including education, and is considered one of the most transformative technologies of the 21st century.
One example is the Artificial Intelligence Policy Lab initiative led by New York City Public Schools, which promotes AI literacy among educators and students, offering training programs, resources, and support for AI integration. Through this initiative, educators have reported increased student engagement and academic performance.
AI can potentially transform how education service agencies (ESAs) and state education agencies (SEAs) support school districts by personalizing learning, enhancing data analysis, and providing real-time insights. A growing number of states recognize the significance of artificial intelligence technology. However, the current guidance provided at the state level to school districts tends to be broad and avoids regulatory language, as indicated by the Center on Reinventing Public Education’s latest assessment of actions taken by state education departments regarding AI. While generative AI technology is advancing rapidly, many states continue to leave the decision-making regarding AI implementation in schools to individual districts.
According to a recent CRPEs survey conducted in October 2023, only two states—California and Oregon—have officially offered guidance to school districts regarding the use of AI in the upcoming academic year. Another 11 states are currently developing such guidance. In comparison, the remaining 21 states that have shared details about their approach do not have plans to provide AI guidance in the foreseeable future.
The generative AI boost
Beyond classroom applications, AI holds promise to enhance productivity through the automation of repetitive and time-consuming tasks, allowing state education agency officials to focus on more critical aspects of their jobs. It has been estimated that generative AI (GenAI) could boost government productivity by $1.75 trillion a year.
GenAI is a subset of artificial intelligence that can produce authentic new content across various formats, such as text, images, audio, code, data, and other media. It operates on foundational or generative models, with the most potent GenAI tools being trained on expansive large language models (LLMs). These models extensively process vast datasets to mimic human communication patterns.
GenAI offers multifaceted support to SEAs and ESAs. For example, it can optimize resource allocation by utilizing AI to efficiently distribute funds, personnel, and materials, aided by predictive analytics to prevent shortages. AI-driven communication tools enhance interactions among educators, students, parents, and administrators, utilizing language processing algorithms for clear communication.
GenAI’s data analysis capabilities enable the examination of large educational datasets, identifying trends and areas for improvement. Additionally, administrative tasks are automated through AI-powered chatbots, freeing human resources for more complex duties. GenAI’s language processing extends to translation services, fostering communication with diverse linguistic communities and supporting non-native English speakers.
AI requires a deliberate approach
Despite AI’s numerous benefits and potential applications in education, several challenges and concerns must be addressed. One major concern is the ethical use of AI in education. It is crucial to ensure that AI algorithms and tools are unbiased and do not perpetuate discriminatory practices. Steps must be taken to eliminate algorithmic biases and ensure fair and equitable access to educational opportunities for all students. This is why Resultant has developed a Data Equity Framework to address the negative impact of biases and systemic barriers when engaged with data analytics.
Rather than hastily rushing into technical solutions, we advocate for a thoughtful and deliberate approach that emphasizes the importance of design. Spending time on careful planning and design ensures that the implementation of AI in education is not only successful but also sustainable—we must first crawl before we can walk and then run.
The crawl phase involves laying the groundwork, understanding the unique needs of educational systems, and designing strategies that align with the goals of ESAs. As we progress to the walk and run phases, the focus shifts to refining technical solutions based on the insights gained during the design phase. This phased approach mitigates the risk of implementation failures and fosters a more nuanced understanding of how AI can truly benefit education.
Let us invest time and effort in thoughtful design, steering away from the temptation to rush into technical solutions, and collectively shape a future where AI enhances education with precision and purpose.
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