Automation bias is the propensity for humans to favor suggestions from automated decision-making systems and to ignore contradictory information made without automation, even if it is correct. [1]

This bias primarily stems from token bias—that is, the model assigns a higher a priori probability to specific answer tokens (such as "A") when generating responses.

The ethics of artificial intelligence covers a broad range of topics within AI that are considered to have particular ethical stakes. [1] This includes algorithmic biases, fairness, accountability, transparency, …

Automation includes the use of various equipment and control systems such as machinery, processes in factories, boilers, [3] and heat-treating ovens, switching on telephone networks, steering, stabilization …

The book focuses on how automation negatively impacts the poor. [1] In the United States during the 19th century, poor people were often sent to poorhouses. [2]

There are different definitions of ADM based on the level of automation involved. Some definitions suggests ADM involves decisions made through purely technological means without human input, [4] …

Chyby kvůli automation bias se objevují v případech, kdy rozhodování závisí v určitém míře na počítačích nebo jiném automatizovaném pomocníkovi a lidská činnost se zde omezuje pouze na …

Références (en) Cet article est partiellement ou en totalité issu de l’article de Wikipédia en anglais intitulé « Automation bias » (voir la liste des auteurs).

Algorithms and training AI paradigms have been debated, especially their efficacy and bias. Bostrom and Eliezer Yudkowsky have argued for decision trees (such as ID3) over neural networks and …

Out-of-the-loop performance problem Part of a series on Automation Automation in general Banking Building Home Highway system Laboratory Library Broadcast Mix Pool cleaner Pop music …