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The Pan-Canadian Artificial Intelligence Strategy (2017) is supported by federal funding of Can $125 million with the objectives of increasing the number of outstanding AI researchers and skilled graduates in Canada, establishing nodes of scientific excellence at the three major AI centres, developing 'global thought leadership' on the economic ...
However, making code open source does not make it comprehensible, which by many definitions means that the AI code is not transparent. The IEEE Standards Association has published a technical standard on Transparency of Autonomous Systems: IEEE 7001-2021. [64] The IEEE effort identifies multiple scales of transparency for different stakeholders.
Specifically, "algorithmic transparency" states that the inputs to the algorithm and the algorithm's use itself must be known, but they need not be fair. " Algorithmic accountability " implies that the organizations that use algorithms must be accountable for the decisions made by those algorithms, even though the decisions are being made by a ...
“These new requirements will be supported by greater transparency,” Young said, highlighting the agency reporting requirements. “AI presents not only risks, but also tremendous opportunity ...
Executive Order 14110 is the third executive order dealing explicitly with AI, with two AI-related executive orders being signed by then-President Donald Trump. [ 10 ] [ 11 ] The development of AI models without policy safeguards has raised a variety of concerns among experts and commentators.
Stanford University researchers issued a report on Wednesday measuring the transparency of artificial intelligence foundation models from companies like OpenAI and Google, and the authors urged ...
ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT, formerly known as ACM FAT*) is a peer-reviewed academic conference series about ethics and computing systems. [1] Sponsored by the Association for Computing Machinery , this conference focuses on issues such as algorithmic transparency , fairness in machine learning , bias ...
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