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Answer :
The ethical challenges with AI development include concerns over privacy, potential job loss, lack of transparency, and the need for antiracist and equity-focused approaches. Professional development and corporate responsibility are vital in navigating these ethical terrains, as is considering the social and environmental costs of AI.
There are numerous ethical challenges associated with AI development in higher education (HE) and beyond. One major concern is privacy, as the use of AI in educational settings can lead to discrimination if student data is not handled with care. Lack of transparency in AI algorithms can result in unfair outcomes, particularly affecting vulnerable populations. Additionally, the potential for job loss due to AI automation is a significant issue that society must address.
Ethical considerations must prioritize antiracist, equity, and privacy principles to ensure that AI does not disenfranchise or disempower students and educators. Corporate responsibility is critical to guide the ethical deployment of AI technologies, considering the broader societal impacts, including surveillance, profiling, and cybersecurity threats. Furthermore, there is a need for professional development and upskilling of staff and students to navigate these complex ethical terrains effectively.
The ethical use of AI is also critical to prevent contract cheating and other forms of academic dishonesty. Issues such as the massive amounts of data and energy required for AI development, often at the expense of poorly paid global workers, raise serious concerns about the sustainability and human toll of advancing these technologies.
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