Titlebook: Building Responsible AI Algorithms; A Framework for Tran Toju Duke Book 2023 Toju Duke 2023 Responsible AI.Fairness Metrics.Data Quality.Tr

Fecundity

Thoralf Johansson,Ulrich Fotheringhams is a great step toward building a responsible AI system. Some of these dangers can be avoided by having humans involved. This chapter looks at the different ways humans can review the ML workflow process and ensure its safety.

Generosity

Post-Processing by Laser Cutting,in the previous chapter, is highly important in building trust in AI, so is privacy (and all the other dimensions discussed in previous chapters). This chapter takes a closer look at privacy and how it contributes to building a responsible AI framework.

易怒

小故事

Operator Theory: Advances and ApplicationsThe first chapter set the foundation for responsible AI frameworks, kicking off with responsibility and a few examples of AI and its ethical limitations. This chapter delves into “AI principles,” which are fundamental components of building responsible AI systems.

Basilar-Artery

民間傳說(shuō)

Substance

Mohamed El Morsalani,Abderaouf MourtadaThe previous chapter looked at fairness and explained how it relates to responsible AI. This chapter looks at AI safety and explains how it contributes to a responsible AI framework.

無(wú)能力

無(wú)能的人

Andrés Iglesias,Nobuki TakayamaIn addition to ensuring that ML models and applications are respectful and cognizant of people’s privacy, and that they don’t infringe on human rights by violating privacy laws, it’s also important that AI technologies be protected from cyberattacks. This involves building robust ML models, which is another fundamental part of responsible AI.

商談

AI PrinciplesThe first chapter set the foundation for responsible AI frameworks, kicking off with responsibility and a few examples of AI and its ethical limitations. This chapter delves into “AI principles,” which are fundamental components of building responsible AI systems.