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S.A.F.E. BENCHMARKS 

White Waves

THE FRAMEWORK

The work of the EDSAFE AI Alliance centers on the SAFE
Benchmarks Framework. The framework creates a policy process and roadmap for the essential issues in creating a SAFE AI ecosystem. The framework was built starting in 2021 and brings together more than 24 global AI safety, trust and market frameworks. Frameworks and benchmarks are essential to innovation as a means of targeted guidance, focusing disparate efforts towards
shared language, objectives, and outcomes and ensuring the development of appropriate guidelines and guardrails for use. By working together through the Framework, EDSAFE aims to accomplish two things: achieve equitable outcomes for students and improve working conditions for teachers.

Safety is a primary consideration for ensuring edtech users
can be active in a digital environment that prioritizes protecting their data and privacy while managing
cybersecurity risks. At the same time, solution providers have a shared commitment to responsibly building
innovative education solutions. Solution providers must be able to continue developing and deploying tools
and the evolution of their product roadmaps while responsibly building innovative learning solutions.

SAFETY

Accountability is a cornerstone for establishing benchmarks that are collaboratively defined by a diverse group of constituents, encompassing subject matter experts, edtech solution providers, educators from Pre-K through higher education, and learners of all ages. This approach ensures the creation of standards
that not only foster accountability but also bolster it through the integration of pertinent existing policies and
regulatory undergirding. Concurrently, all parties involved are dedicated to the transparent development and
implementation of these standards, ensuring they are in line with the evolving educational landscape and
effectively address the needs and expectations of all stakeholders.

ACCOUNTABILITY

Achieving ethical, unbiased, and equitable learning opportunities necessitates a conscious and deliberate
effort from both solution providers and users to scrutinize the quality of data being utilized, including the
acquisition of datasets, the application of their products, and the monitoring for any inadvertent biases. AI
products and experiences must be accessible for all individuals and there needs to be strategies for creating
standards, guidelines, and/or quality indicators to gauge this accessibility. This endeavor extends to ensuring
fairness and transparency, particularly in the procurement of materials produced by AI outputs, underlining
the importance of vigilance and intentionality in every aspect of educational technology engagement.

FAIRNESS AND TRANSPARENCY

Deliberations are essential regarding the effectiveness of applying AI in specific scenarios, coupled with the
commitment by edtech solution providers to integrate comprehensive and transparent evaluation tools within educational technologies. Such integration aims to precisely measure advancements and provide educators and learners with insightful feedback on usage and progress. Efficacy is understood to be deliberately tied to an equity in student experiences as well as outcomes. This approach underscores the significance of carefully considering the utility of AI and the importance of inclusivity and clarity in the mechanisms used to gauge and communicate educational outcomes.

EFFICACY

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. 

SIIA Principles for the Future of AI in Education

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