GenAI has environmental consequences, centering around the energy and spaces required to power the data-centers (and increasing demand for them) that GenAI run on. These environmental issues are exacerbated by the practices of large technological companies and conglomerates to not disclose or record carbon emissions of their industries (a current and historical issue). Research on the environmental consequences of GenAI continues to be done. To start learning more about the environmental impacts of AI, please see the video below:
When it comes to AI and algorithmic systems, we tend to think of computers magically doing all the work for us. But behind the scenes, there’s a lot of human labor involved in the training and maintenance of these systems.
Most machine-language models learn how to make decisions from datasets that have been labelled, classified, verified, and filtered by real people. These quality control tasks, which are invisible to end users, are referred to as ghost work (Gray & Suri, 2019).
When using an AI application, you should avoid entering any personal, sensitive, or confidential information. Why?