Eliminating Algorithmic Bias Is Just the Beginning of Equitable AI
Descrição
When it comes to artificial intelligence and inequality, algorithmic bias rightly receives a lot of attention. But it’s just one way that AI can lead to inequitable outcomes. To truly create equitable AI, we need to consider three forces through which it might make society more or less equal: technological forces, supply-side forces, and demand-side forces. The last of these is particularly underemphasized. The use of AI in a product can change how much customers value it — for example, patients who put less stock in an algorithmic diagnosis — which in turn can affect how that product is used and how those working alongside it are compensated.
Algorithmic bias in machine learning-based marketing models
Dissecting Algorithmic Bias: A Digital Quality Summit Presentation
andrew sroka - Algorithmic Bias
Eliminating Algorithmic Bias Is Just the Beginning of Equitable AI
Applied Sciences, Free Full-Text
Managing AI chatbots to be less discriminatory: An exclusive Q&A
SHIFTing artificial intelligence to be responsible in healthcare
Article Archives Digital Data Design Institute at Harvard
What is Responsible AI Importance in Data Science Reporting
Greenlining Institute: Algorithmic Bias Explained – Q&A with
Ethics and discrimination in artificial intelligence-enabled
Greenlining Institute: Algorithmic Bias Explained – Q&A with
Eliminating Algorithmic Bias Is Just the Beginning of Equitable AI
de
por adulto (o preço varia de acordo com o tamanho do grupo)