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Privacy-preserving Computation of Fairness for ML Systems: Acknowledgement & References
Manage episode 393667483 series 3474385
This story was originally published on HackerNoon at: https://hackernoon.com/privacy-preserving-computation-of-fairness-for-ml-systems-acknowledgement-and-references.
Discover Fairness as a Service (FaaS), an architecture and protocol ensuring algorithmic fairness without exposing the original dataset or model details.
Check more stories related to tech-stories at: https://hackernoon.com/c/tech-stories. You can also check exclusive content about #ml-systems, #ml-fairness, #faas, #fairness-in-ai, #fairness-as-a-service, #fair-machine-learning, #fairness-computation, #cryptograms, and more.
This story was written by: @ashumerie. Learn more about this writer by checking @ashumerie's about page, and for more stories, please visit hackernoon.com.
Fairness as a Service (FaaS) revolutionizes algorithmic fairness audits by preserving privacy without accessing original datasets or model specifics. This paper presents FaaS as a trustworthy framework employing encrypted cryptograms and Zero Knowledge Proofs. Security guarantees, a proof-of-concept implementation, and performance experiments showcase FaaS as a promising avenue for calculating and verifying fairness in AI algorithms, addressing challenges in privacy, trust, and performance.
301 قسمت
Manage episode 393667483 series 3474385
This story was originally published on HackerNoon at: https://hackernoon.com/privacy-preserving-computation-of-fairness-for-ml-systems-acknowledgement-and-references.
Discover Fairness as a Service (FaaS), an architecture and protocol ensuring algorithmic fairness without exposing the original dataset or model details.
Check more stories related to tech-stories at: https://hackernoon.com/c/tech-stories. You can also check exclusive content about #ml-systems, #ml-fairness, #faas, #fairness-in-ai, #fairness-as-a-service, #fair-machine-learning, #fairness-computation, #cryptograms, and more.
This story was written by: @ashumerie. Learn more about this writer by checking @ashumerie's about page, and for more stories, please visit hackernoon.com.
Fairness as a Service (FaaS) revolutionizes algorithmic fairness audits by preserving privacy without accessing original datasets or model specifics. This paper presents FaaS as a trustworthy framework employing encrypted cryptograms and Zero Knowledge Proofs. Security guarantees, a proof-of-concept implementation, and performance experiments showcase FaaS as a promising avenue for calculating and verifying fairness in AI algorithms, addressing challenges in privacy, trust, and performance.
301 قسمت
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