The GES Community Generative AI Literacy and Training Needs Survey is designed to help us understand how members of the GES community currently use generative AI, what challenges they encounter, and what kinds of training and resources would be most useful.
The survey will help the project develop training that reflects the needs of an interdisciplinary community working across genetic engineering, biotechnology, science, communication, policy, ethics, and public engagement.
The survey asks about:
Current generative AI use: which tools community members use and for what activities
AI literacy: participants' current approach to generative AI using the five-stage AI Literacy Continuum
Responsible use: verification, bias, privacy, transparency, human oversight, and other concerns
GES applications: potential uses such as literature synthesis, regulatory and policy analysis, public discourse analysis, science communication, coding, and data analysis
Training needs: topics, formats, difficulty levels, and workshop preferences
Role-specific needs: additional questions for faculty, graduate students, and undergraduate students
People may have very different levels of experience depending on their discipline, task, access, and context. The project uses the AI Literacy Continuum to understand these different starting points and identify where additional guidance or practice may be helpful. Survey findings will inform the development of GES-specific workshops, Google Colab tutorials, responsible-use guidance, and other open educational resources.
Estimated time: 10 - 12 minutes
Survey link: https://qualtricsxmbb6tzksxz.qualtrics.com/jfe/form/SV_bJZMzRBMOG15TQa
Participation is voluntary. The survey introduction will provide the approved information about consent, confidentiality, data use, and project contacts.
Please review the approved consent and privacy language before participating.
Survey findings will help the project team:
Assess → Design → Train → Evaluate → Share
The results will inform the project's training priorities and help create resources that support responsible, critical, and context-aware use of generative AI across the GES community.