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The Ethical Implications of GenAI use: Social, Economic and Environmental

Any AI Literacy course requires participants to grasp the ethical implications of its use. This includes both positive and negative implications. While it is common to hear people talk about privacy, copyright and bias, there are many more implications that need to be considered. We present 32 implications.

An important study led by Zach Quince resulted in a comprehensive table outlining 32 distinct implications of GenAI use. While there may be more, we believe this provides a robust foundation without becoming overly granular. Our findings revealed that students tend to associate with only a limited number of these implications, often gravitating toward the more positive ones. This underscores the need to strengthen students' ethical awareness and understanding by supporting the development of a more balanced and critical perspective.

Affect recognition

Affect recognition interprets emotions via facial expressions, body language, and speech, offering potential benefits in areas like mental health support, adaptive learning, and customer service. However, it faces criticism for methodological flaws and inconsistency. Privacy concerns arise with its use in surveillance, like in schools, and it can perpetuate bias, as seen with an algorithm leading to racial profiling by linking behaviours to ‘terrorist behaviour’.

Bias

GenAI is a vast language model trained on a large dataset like common crawl, which gathers data from web pages and other sources over many years. It grants immense capabilities but also harbours biases. Internet scraping can introduce discriminatory language alongside valuable content.

Collaboration

GenAI can enhance collaboration by facilitating idea exchange, streamlining communication, and fostering shared insights for collective problem-solving. The impact depends on how it is used. Either as a helpful tool that supports people or as something that undermines human contribution.

Competitive advantage

Gen-AI tools can facilitate competitive advantage in the face of rapid digital transformation. This may include improved resource allocation, capability development, efficiency and increased revenue/profit through cost reduction and improved productivity. However, this can also widen the gap between organisations with access to advanced AI and those without.

Control and oversight

This relates to ensuring that humans remain in ultimate control of all critical processes. AI should be used to support, not replace, human judgment, especially in decisions that affect people’s lives, rights, or well-being.

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This is a Special Interest Group of the Australasian Association of Engineering Education

https://aaee.net.au/

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