This year, the number of people in the U.S. using AI voice assistants is forecast to reach 154.3 million and will continue to increase to 170.3 million by 2028.
One of the key drivers behind this growth of AI-assisted technology in general is the accuracy of these tools. For example, Google Assistant answers user questions correctly 96 percent of the time.
Why is AI becoming more and more accurate and reliable? Well, AI can consume more data than ever when responding to inquiries. Data created in 2010, totaled two zettabytes—that’s one billion terabytes. That number is forecast to reach 147 zettabytes by the end of 2024. In fact, experts estimate more data has been created in the past two years than in all human history combined.
With AI sparking innovation in smart homes, self-driving vehicles, and wearable devices, many look forward with somewhat apprehensive excitement to an interconnected future that feels like “magic.” However, this magic doesn’t seem to have made its way into the American education system.
The interconnectedness we seek in education is largely made possible by data interoperability. Data interoperability is defined as “the seamless, secure, and controlled exchange of data between applications.”
This precise, standards-aligned exchange of data isn’t rocket science. It’s data science, with a bit of computer science rolled in. Educators should have information about student performance to provide high-quality classroom instruction, and this data should be easy to gather, organize, access, and analyze.
Bringing the “magic” to education
There are specific market conditions that must be addressed when laying the groundwork for effective data interoperability across educational applications and systems. At Resultant, we believe the K–12 sector needs the following:
1. Openly available data standards
Although data standards in K–12 education exist today, awareness and adoption of these standards varies greatly. For these standards to enable data interoperability at scale, they can’t just be standards on paper. They must be widely and authentically adopted in the real world.
The Ed-Fi Data Standard was created for that specific purpose—to operationalize data exchange across disparate educational data systems. When implemented effectively, a data standard enables the magic of systems communication, data integrity, and synchronization between applications, without the user being aware of the nuanced complexity of the data exchange that occurred behind the scenes.
2. State and district demand for data standards
One of the most fascinating realizations I’ve had in the education sector is that school districts, states, and higher education institutes have not prioritized data interoperability among their vendors. In fact, it’s almost the reverse scenario!
I’ve witnessed firsthand district and charter schools, as well as state education agencies, sign contracts that limit their own ability to access their data and provide aggregate data views and reports to their end users!
Fortunately, the tide seems to be turning, thanks to movements like Project Unicorn. We’re seeing an increasing number of districts and states now demanding secure, accessible pathways to vendor data systems. They’re requiring vendors to use open standards like the Ed-Fi Data Standard so they can get the data they need, when they need it.
3. Privacy and security of educational data
At Resultant, we believe that every piece of personally identifiable information (PII) about students must be protected. As of this writing, at least 45 states have introduced AI bills, while 31 have adopted resolutions or enacted legislation. Earlier this year, Rhode Island became the 20th state to enact data transparency and privacy legislation.
At the federal level, the American Privacy Rights Act, which would preempt most state laws, has been introduced but faces significant hurdles to passage. Many are advocating for an AI-era update of the Family Educational Rights and Privacy Act (FERPA), which protects the privacy of student education records and turned 50 this year.
The point is that the need for secure data interoperability is fundamentally built upon widely approved, adopted, and understood data privacy and security principles and standards. This applies to public and nonprofit sectors.
Tech giants Google, Amazon, Microsoft, Salesforce, IBM, and Oracle pledged years ago to accelerate data interoperability in health care. Many AI organizations such as EdSAFE AI Alliance research AI and advocate for AI education policies. Data Quality Campaign, the Consortium of School Networking (COSN), and Common Sense Media have contributed significant research in defining these principles and processes.
Collectively, we must ensure students reap the benefits of data interoperability in a secure way that doesn’t compromise their privacy.
Think about the possibilities…
What level of success could students achieve if technology and applications in classrooms connected and worked together with the students’ best interest in mind? What types of outcomes could educators deliver if they had AI-connected data systems delivering accurate, actionable performance data in real-time about their students’ learning progression?
Think about what would be possible if the promise of AI were introduced and realized in American education ethically and responsibly. Well, the outcome could be magical.
At Resultant, we’re helping school systems and education agencies develop and implement data interoperability strategies that use AI responsibly to improve performance, protect privacy, and contribute to better student outcomes. If you’d like to discuss how we can do the same for you, please reach out to have a conversation.
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