Date
Publisher
arXiv
Artificial intelligence (AI) has transformed various sectors and institutions, including education and healthcare. Although AI offers immense potential for innovation and problem solving, its integration also raises significant ethical concerns, such as privacy and bias. This paper delves into key considerations for developing AI policies within institutions. We explore the importance of interpretability and explainability in AI elements, as well as the need to mitigate biases and ensure privacy. Additionally, we discuss the environmental impact of AI and the importance of energy-efficient practices. The culmination of these important components is centralized in a generalized framework to be utilized for institutions developing their AI policy. By addressing these critical factors, institutions can harness the power of AI while safeguarding ethical principles.
Study at a glance
- Question: What key factors should institutions consider when developing policies for artificial intelligence?
- Setting and data: Not stated in the abstract
- Method: Not stated in the abstract
Why it matters
While artificial intelligence offers immense potential for innovation and problem solving in sectors like education, its integration raises significant ethical concerns regarding privacy, bias, and environmental impact.
Key findings
- Across institutions including education, artificial intelligence provides problem-solving potential but poses substantial ethical concerns regarding data privacy and bias.
- System interpretability, explainability, privacy protection, and bias mitigation serve as foundational components for institutional artificial intelligence policy frameworks.
- Institutional artificial intelligence policies encompass environmental impacts, identifying energy-efficient practices as a critical component of institutional adoption.
Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.
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