S.A.F.E. BENCHMARKS
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THE FRAMEWORK
The work of the EDSAFE AI Alliance centers around the SAFE Benchmarks Framework as we engage stakeholders to align to an equitable outcome for all learners and improved working experiences for dedicated and innovative educators. Our intent is to clarify the urgency and specific areas of need to prevent failures in data management that compromise the potential for how responsible AI can be a lever for equity for educators and learners alike. Frameworks and benchmarks are important to innovation as a means of targeted guidance, focusing disparate efforts towards shared objectives and outcomes, and ensuring the development of appropriate restraints.
The goal for safety is ensuring edtech users can be active in a digital environment which protects their data and privacy security while vendors continue in their roadmaps, responsibly innovating learning solutions.
SAFETY
Standards co-written by subject matter experts, edtech vendors, the educators and the learners using the tools can provide such accountability if appropriately reinforced by relevant policymakers and stakeholders.
ACCOUNTABILITY
Providing ethical, unbiased and equitable learning opportunities can be achieved as long as developers are intentional about the quality of the data being received from both the procurement of large datasets and the usage of their products, and vigilant regarding potential unconscious biases within their designs.
FAIRNESS
Vendors can support efficacy by incorporating diverse and transparent measurement capabilities into edtech for assessing gains, informing both educator and learner of progress.
EFFICACY
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The Software and Information Industry Association (SIIA), a trade association comprised of over 380 global tech companies and a member of the EDSAFE AI Alliance Steering Committee, has recently created guidelines for the responsible development of artificial intelligence (AI) tools for education. "Principles for the Future of AI in Education" prioritize civil rights, inclusion, and educational equity as critical considerations when implementing AI technologies in K-12 and colleges and universities.