Abstract
This special issue editorial of Human Computation on the topic "Crowd AI for Good" motivates explorations at the intersection of artificial intelligence and citizen science, and introduces a set of papers that exemplify related community activities and new directions in the field.
Highlights
The many advances in scientific insight we have witnessed in the past years should not cover up some of the challenges that these approaches face
Machine learning (ML)/artificial intelligence (AI) has come under scrutiny and received criticism because of black box models, and biases that have been caused by unbalanced
At the same time, growing awareness of the broad applicability of AI to societal problems including humanitarian issues has led to recent initiatives in the public and private spheres, including Microsoft’s AI for Good, Google’s AI for Social Good, as well as the UN’s AI for Good Global Summit, which seeks to apply machine intelligence to 17 Sustainable Development Goals (SDGs) set by the UN General Assembly
Summary
The many advances in scientific insight we have witnessed in the past years should not cover up some of the challenges that these approaches face. 2 Ostermann et al / Human Computation (2021) 8:2 training data (see, for example, Annoni et al 2018).
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