The work of the EDSAFE centers around the SAFE Benchmarks Framework as we engage stakeholders to align equitable outcomes for all learners and improved working experiences for dedicated and innovative educators. We intend 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 and innovation while protecting student privacy. 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 guidelines and guardrails.
Informing product leads and their teams of innovators, designers, and developers as they work toward safety, security, and trust while creating AI products and services for use in education.
A. Newell, и H. Simon. Communications of the ACM, 19 (3):
113-126(марта 1976)p. 116:
"The Physical Symbol System Hypothesis. A physical
symbol system has the necessary and sufficient
means for general intelligent action."
p. 120:
"Heuristic Search Hypothesis. The solutions to
problems are represented as symbol structures.
A physical symbol system exercises its intelligence
in problem solving by search--that is, by
generating and progressively modifying symbol
structures until it produces a solution structure."
p. 121:
"To state a problem is to designate (1) a test
for a class of symbol structures (solutions of the
problem), and (2) a generator of symbol structures
(potential solutions). To solve a problem is
to generate a structure, using (2), that satisfies
the test of (1).".