Open Praxis: The Manifesto for Teaching and Learning in a Time of Generative AI – A Critical Collective Stance to Better Navigate the Future

Open Praxis: The Manifesto for Teaching and Learning in a Time of Generative AI – A Critical Collective Stance to Better Navigate the Future

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This document presents a collaboratively written manifesto offering a critical examination of the integration of Generative AI (GenAI) in higher education. It identifies both the positive and negative aspects of GenAI's influence on teaching and learning, stressing that it is not a neutral tool and risks reinforcing existing biases.

The manifesto calls for research-backed decision-making to ensure GenAI enhances human agency and promotes ethical responsibility in education. It also acknowledges that while GenAI has potential, educators must also think about the deprofessionalization of the education field if AI tools increasingly automate tasks like grading, tutoring, and content delivery, potentially leading to job displacement and reduced opportunities for educators.

The text explores the importance of AI literacy for users and also looks to the risks of human-AI symbiosis, including the erosion of human judgement, autonomy and creative agency. The authors hope to encourage debate and offer insight into the future of GenAI in educational contexts.

Here are the five main takeaways:

• GenAI is not a neutral tool. It reflects worldviews and can reinforce biases, potentially marginalizing diverse voices.
• GenAI can both enhance and diminish essential human elements in education. While it offers potential for personalized learning and efficiency, it also risks eroding creativity, critical thinking, and empathy.
• Ethical considerations are paramount. Issues such as bias, fairness, transparency, and data security must be addressed to ensure responsible deployment of GenAI.
• Educators, administrators, and policymakers need to rethink education. Continuing with 'business as usual' is not an option. A shift is needed to emphasize learning processes and adapt assessment methods.
• Robust, evidence-based research is crucial. Decisions about integrating GenAI in education should be guided by a deep understanding of its impacts.