GenAI tools can assist us in our daily lives, at work or studying. Like any tool, we should consider it's use through an ethical lens. Explore the various headings below for the ethical considerations connected to GenAI.

Accessibility

While AI offers exciting opportunities to enhance accessibility and inclusivity, it’s crucial to recognize that it can also inadvertently exclude many individuals, particularly those who already face accessibility challenges. As we explore GenAI tools, it's essential to prioritize equitable access for all users. For example, although many generative AI tools are currently free, a growing number are starting to charge fees for access, which can create barriers for those who may not be able to afford it.

At the same time, GenAI tools can also function as accessibility aids for learners. Here are several examples of AI tools designed to enhance accessibility across various platforms:

Environmental Impact

Development, training and use of GenAI models require systems that use a significant amount of energy and contribute to carbon emissions. They also consume vast amounts of water for cooling, and produce electronic waste generated from the hardware used in AI systems. While developers continue to seek more sustainable ways of operating, it is important to consider whether your use of AI is worth the environmental impact and to consider ways GenAI tools can be used more efficiently when possible.

As the reliance on AI tools grows, it's crucial to prioritize sustainable practices and consider the ecological footprint of these technologies to mitigate their impact on the environment.

Misinformation

Since GenAI is trained on real-world data, text, and media from the internet, the content it provides may be misleading, factually inaccurate, or outright misinformation—such as deep fakes. The lack of transparency about the sources of training data and AI’s inability to cite specific references raises ethical concerns, particularly in academic contexts. Its output may not always be credible or reliable and can reflect implicit or explicit biases, outdated information, or fabricated content (often referred to as “hallucinations”).

To uphold ethical standards and avoid spreading misinformation, always verify the accuracy of AI-generated content using reliable sources before including it in your work. Taking this step helps maintain the integrity of your research and ensures responsible use of AI tools.