From the course: AI Accountability: Build Responsible and Transparent Systems (2022)
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Bias in AI
From the course: AI Accountability: Build Responsible and Transparent Systems (2022)
Bias in AI
- [Instructor] It's a common theme in science fiction that as soon as the machines, the robots, the Ais, whatever, are given autonomy, they immediately commence a murderous rampage against humanity, and it's a dystopian hellscape before you can even figure out what's happening. I mean, it even led to people posting pictures that made their robot vacuums look like they were part of the scourge. But while I will in fact talk about items associated with military AI later in this course, a more prevalent issue is the social damage that can happen through irresponsible use of AI. This includes things like contributing to racism or to sexism or to homophobia or classism, colorism, ageism, ableism, religious and national biases among so many others. If you can think of a social prejudice, there's a way that artificial intelligence can unfortunately contribute to it and even exacerbate it. A few examples of these can include…
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Contents
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The challenge of classification errors3m 39s
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(Locked)
The causes of classification errors6m 18s
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(Locked)
Bias in AI3m 50s
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(Locked)
Supervised and unsupervised learning8m 16s
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(Locked)
Biased labeling of data7m 15s
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Construct validity6m 14s
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The absence of meaning4m 54s
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Vulnerability to attacks4m 45s
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