Consciously striving to mitigate against all forms of bias to engage, understand, and treat all people fairly and equally. This includes addressing embedded biases and bias in the use of smart tech.
AI dividend:
See dividend of time.
AI for Good (AI4Good):
The extensive use of AI in support of humanitarian causes, particularly to address transnational humanitarian crises. The main players include large nonprofit organizations in partnership with universities, international development agencies, healthcare, and large tech companies.
algorithm:
A series of computations that ranges from the most simple to the most complex. Machine learning uses an algorithm to process data and discover rules that are hidden in the data, which are then encoded in a model that can be used to make predictions on new data.
augmented intelligence:
See co-botting.
bias:
Systematically favoring one group over another. Common areas of bias include gender, race, LGBTQ+, ableism, ageism, religion, class, education, nationality, and more.
big data:
The huge amount of data that is constantly being created, stored, shared, used, and reviewed by machines to track, analyze, and make predictions about people's behavior.
busyness paradox:
The state of being so busy concentrating on immediate, low-value tasks that a person's attention and ability to focus narrows, making it difficult to distinguish true crises from everyday work and ...
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