For this post I will be reflecting and evaluating Bruce Mao’s Blog Post #5.
Bruce’s blog section regarding Ethical Considerations of AI in Education brings up important issues about prejudice and privacy, emphasizing the necessity of robust data protection regulations. Building on this, it’s also critical to take into account the shared accountability of AI’s creators, educators, and politicians. The promotion of student autonomy over their data adds another level of ethical AI use. Platforms could, for example, offer dashboards that allow parents and students to monitor the usage of their data or to disable specific functionalities.
Bruce’s emphasis on algorithmic bias highlights a crucial but often overlooked component of AI application. When developing AI tools, diverse representation and input is essential. To achieve diversity and lessen bias, instructors from a variety of socioeconomic and cultural backgrounds should be included in AI decision making.