Some of main challenges and implications of ChatGPT in higher education are:
As AI technology continues to evolve, it brings forth a range of intellectual property concerns. The creation and use of AI models often involve complex algorithms and vast datasets, raising questions about ownership, rights, and the protection of intellectual property. The resources below explore the legal and ethical challenges associated with AI, including issues related to copyright, patents, and the fair use of data. They underscore the importance of establishing clear guidelines and policies to safeguard intellectual property while fostering innovation. Resources and case studies are provided to help navigate the intricate landscape of AI and intellectual property.
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The development and maintenance of AI systems often rely on a hidden workforce, commonly referred to as "ghost workers." These individuals perform crucial tasks such as data labeling, content moderation, and training AI models. Many of these workers are located in the Global South and are paid minimum wages for their labor, often under harsh and precarious conditions. The resources below explores the ethical and social implications of labor exploitation in the AI industry and provides resources for further understanding and advocacy.
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Digital Labor Dynamics explores the transformation of work in the age of AI and digital platforms. The following articles highlight the emergence of various forms of platform-based labor, including on-demand work, microwork, and social networked labor. These new labor models involve human tasks essential for training and maintaining AI systems, such as data annotation and content moderation. Understanding these dynamics is crucial for addressing the socio-economic impacts of AI, including labor rights, fair wages, and the future of employment in a technology-driven world.
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While AI technology offers significant advancements and efficiencies, it also comes with considerable environmental costs. The training and deployment of AI models require vast amounts of computational power, leading to high energy consumption and substantial carbon footprints. This resources below delve into the environmental impact of AI, highlighting the need for sustainable practices and the development of greener technologies. Resources and studies are provided to facilitate a deeper understanding of AI's ecological implications.
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The above 'Challenges' and 'Things to Consider' are adapted from:
Khodarahmi, M. (n.d.). AI Literacy and Critical Thinking. Retrieved August 7, 2024, from https://libguides.macalester.edu/c.php?g=1329270&p=9787220
