At Digital University, in association with Mozilla Responsible Computing Challenge India, the team work on an interesting project titled "Integration of Modules on "Responsible NLP" into Existing Natural Language Processing Course for Computing Students using Flipped Classroom Strategies and Outreach Components", which aims to create and integrate a module on Responsible Natural Language Processing with an existing curriculum. The proposed methodology and implementation envision the following components:

(1) Need Assessment: Conduct a need assessment to understand the existing NLP course content. This may help in understanding the level of student familiarity with responsible AI concepts and any gaps that need addressing.

(2) Module Development: Develop modules on "Responsible NLP" that cover ethical considerations, biases, fairness, and social impacts. In this component, engaging content, including videos, reading materials, and case studies, is planned.

(3) Flipped Classrooms: To foster active learning and deeper engagement, the teaching materials may be given to the students to review outside the classrooms. This may enable more time inside the classroom for discussions, hands-on activities, and project work.

(4) Interactive Discussions: This component proposes interactive discussions, debates, and case analyses related to responsible NLP. This may help the learners share insights and diverse viewpoints that promote critical thinking and collaborative learning.

(5) Outreach and Awareness Components: Make the students engage in community outreach initiatives. This includes the learners developing workshops for local schools,  colleges, and other organizations to raise awareness about responsible AI and its impact.

(6) Evaluation and Feedback: Regular assessment of student comprehension through quizzes, discussions, and project presentations is encouraged, and feedback will be collected to refine module content and teaching methods.

These components may bring new and diverse perspectives into the program that acknowledge the societal impact of AI technologies by attracting students from diverse backgrounds and fostering discussions that encompass cultural, ethical, and social aspects. Another perspective would be to encourage students to consider the potential harms and benefits of NLP technologies and to cultivate empathy and a sense of responsibility, ensuring future AI practitioners prioritize ethical considerations.