The Manifesto for Teaching and Learning in a Time of Generative AI: A Critical Collective Stance to Better Navigate the Future
Open Praxis is a peer-reviewed open access scholarly journal focusing on research and innovation in open, distance, and flexible education. The aim of Open Praxis is to provide a platform for global collaboration and discussion of issues in the practice of open, online, and distance education. And in an editorial 47 authors have published 'The Manifesto for Teaching and Learning in a Time of Generative AI: A Critical Collective Stance to Better Navigate the Future'.
"Algorithms now shape human interaction, communication, and content creation", they say, "raising profound questions about human agency and biases and values embedded in their designs. As GenAI continues to evolve, we face critical challenges in maintaining human oversight, safeguarding equity, and facilitating meaningful, authentic learning experiences. This manifesto emphasizes that GenAI is not ideologically and culturally neutral. Instead, it reflects worldviews that can reinforce existing biases and marginalize diverse voices. Furthermore, as the use of GenAI reshapes education, it risks eroding essential human elements—creativity, critical thinking, and empathy—and could displace meaningful human interactions with algorithmic solutions. This manifesto calls for robust, evidence-based research and conscious decision-making to ensure that GenAI enhances, rather than diminishes, human agency and ethical responsibility in education."
The key focus role seen for the Manifesto is how can we ensure that the design and development of GenAI align with our values, fostering care, equity, and inclusivity in education and beyond?
Thus they offer a critical perspective on the use of GenAI in the educational landscape aiming to provoke thoughtful discourse on the topic, reflecting the potential benefits and critical considerations for integrating GenAI into educational contexts. They put forward key themes "accompanied by critical insights to foster a comprehensive understanding of these issues."
Committing to this manifesto offers a way to break free from the constraints of formalized and institutionalized writing modes typically used in academic settings (Bayne & Ross, 2016; Bayne et al., 2020). Rather than repeating clichéd narratives about the educational landscape, we crafted this manifesto to deepen our understanding of GenAI, raise awareness, and encourage critical, thought-provoking discourse to help us navigate its evolving role in shaping the future.
This approach, they say, "follows a qualitative research paradigm, using collective writing as a method of inquiry (Gale & Bowstead, 2013). Bringing creative minds together in collective studies leads to innovative solutions that can surpass individual capacities (Huijser et al., 2024)."
The study "adopted a modified Delphi technique (see Pelletier et al., 2021), which involves a structured process for collecting and distilling knowledge from a group of experts through a series of questionnaires and discussion processes. A modified Delphi study maintains the fundamental assumption of achieving consensus through the iterative data analysis process (Slagter van Tryon & Bishop, 2006)."
The manifesto is not a short read, but provides an in depth examination of the issues with GenAI in education. . GenAI is not just a tool; they explain. "it is often treated as an agent with capabilities to communicate, interact, and create content on demand, despite differences with human-to-human processes. This positioning requires a shift not only in our attitude toward GenAI but also in the way we discuss it. As an influencing participant that we cannot ignore in the educational ecosystem, GenAI presents a potential symbiotic relationship between humans and machines that necessitates critical reflection on how we engage with it."
No technology, including GenAI, is ideologically and culturally neutral. "It reflects certain worldviews and ways of thinking that present both opportunities and challenges. While GenAI might appear to offer neutral and objective answers, it is not capable of true reasoning and produces output through predictive algorithms."
Furthermore, they conclude "we must rethink the very nature of education, teaching, learning, and assessment in light of GenAI. GenAI could provide opportunities to move beyond a deterministic view of knowledge if, rather than expecting students to provide ‘right answers’, the focus shifts to the learning process, where GenAI may support personalized educational experiences. Moreover, knowledge is no longer confined to traditional classroom settings; it is accessible everywhere."
But in educational settings, "it is vital to be cautious of how corporate interests might influence AI-generated information. If AI systems are driven by revenue or political agendas, they could shape the responses that students receive, hence impacting their learning and critical thinking."
About the Image
This illustration draws inspiration from Leonardo da Vinci’s masterpiece The Last Supper. It depicts a grand discussion about AI. Instead of the twelve apostles, I replaced them with the twelve Chinese zodiac animals. In Chinese culture, each zodiac symbolizes distinct personality traits. Around the table, they discuss AI, each expressing their views with different attitudes, which you can observe through their facial expressions. The table is draped with a cloth symbolizing the passage of time, and it’s set with computer-related objects. On the wall behind them is a mural made of binary code. In the background, there’s an apple tree symbolizing wisdom, with its intertwining branches representing neural networks. The apples, as the fruits of wisdom, are not on the tree but stem from the discussions of the twelve zodiacs. Behind the tree is a Windows 98 System window, opening to the outside world. Through this piece, I explore the history of AI and computer development. Using the twelve zodiacs, I emphasize the diversity of voices in this conversation. I hope more people will join in shaping the diverse narratives of AI history in the future.
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