Define
data
bias
and
problem of inclusion
Answers
Answer:
the answer is
Explanation:
The huge success of applications of machine learning (ML) applications in the past decade — in image recognition, recommendation systems, e-commerce and online advertising — has inspired its adoption in domains such as social justice, employment screening, smart interactive interfaces such as Siri, Alexa, and the like. Along with the proliferation of these applications, there has been an alarming rise in reports of gender, race and other types of bias in these systems. A widely discussed report in the periodical Propublica claimed serious bias against African Americans in a tool to score criminal defendants for recidivism risk [1]. Amazon shut down a model to score candidates for employment after they realized that it penalized women [2]. Predictive policing systems [3] have come under close scrutiny and their use has been curtailed due to discovered biases. Content personalization systems create filter bubbles [23] and ad ranking systems have been accused of racial and gender profiling [22].
Most people like to talk about the benefits of an inclusion classroom. Those are numerous, popular, and easy to list. But what about the problems with inclusive classrooms? It is almost as if it is taboo to even suggest there are problems with creating an inclusive classroom. However, as any mainstream or special education teacher can tell you, there are indeed problems.
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