Automated decision-making
สรุปใจความสำคัญ
- - ADM systems can range from decision-|- support systems (augmented intelligence)|- to fully automated processes (no human involvement).
- - Data quality is fundamental to the outcomes of ADM; problematic issues like bias, incompleteness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,ness,scale ADM is variable-|- support systems (augmented intelligence)|- to fully automated processes (machine learning)
Automated decision-making (ADM) is the use of data, machines, and algorithms to make decisions in a range of contexts, including public administration, business, health, education, law, and transport. These systems can range from decision-support systems that provide recommendations to humans, to fully automated processes that make decisions without human involvement.
Overview of ADM Technologies and Models
The level of automation can vary significantly. Some definitions, such as the EU's GDPR,-based definitions, suggest ADM involves purely technological means without human input. However, modern ADM technologies and applications can take many forms, including augmented intelligence or shared decision-making, where machines and humans work together. Models used in these systems can be as simple as decision trees or as complex as deep neural networks (DNN).
Machine Learning and Foundation Models
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