AI conferences are a key part of education for knowledge sharing, networking, and collaboration, shaping research and applications, and informing curricula. This paper presents preliminary findings from analyzing the mission statements of AI conferences to see if they support or hinder inclusivity and accessibility. In examining language and focus, we identify barriers to entry for educators, researchers, practitioners, and students from underrepresented groups in AI. We use the Language as Symbolic Action (LSA) framework to reveal gaps like the lack of explicit emphasis on DEI, vague promises of empowerment, and elitism. These findings highlight the need for more inclusive language, a clear commitment to DEI initiatives, clearer conference goals, and strategies to address power imbalances and promote equal participation. Our work has two impacts: 1) demonstrating preliminary results from using the Language as Symbolic Action framework for text-analysis, and 2) providing valuable insights for the education community to plan outreach. This work is useful for conference organizers, educators in engineering and CS, researchers, and the broader AI community. Addressing these issues can create a more inclusive and accessible environment for all in AI, promoting innovation, collaboration, and progress.
The full paper will be available to logged in and registered conference attendees once the conference starts on June 22, 2025, and to all visitors after the conference ends on June 25, 2025