Generative Artificial Intelligence: New Scenarios in Teaching, Learning, and Communication

Keynote at the VIII Congreso Internacional de Estudios sobre Medios de Comunicación, held in Universidad Complutense de Madrid on September 6th, 2023. In recent years, the landscape of Artificial Intelligence (AI) has witnessed a seismic shift with the emergence of Generative Artificial Intelligence (GenAI). This keynote explored the ground-breaking applications of GenAI in reshaping the arenas of teaching, learning, and communication. The historical trajectory of AI, from its inception to its current pinnacle, has been meteoric. Traditional AI models, mainly rule-based and deterministic, have evolved into sophisticated generative models capable of creating content that is often indistinguishable from that crafted by humans. Key exemplars in this category include the GPT series and DALL-E from OpenAI. Nevertheless, what exactly is GenAI? Unlike traditional AI models that are primarily reactive, GenAI models can produce new, previously unseen content. Their inherent characteristics enable them to simulate the process of human creation. Algorithms such as Generative Adversarial Networks (GAN), Long Short-Term Memory networks (LSTM), and Transformers stand as a testament to the diversity and capability of generative models. Applying these models transcends sectors, presenting immense opportunities and challenges in equal measure. The sphere of education stands on the cusp of a revolution thanks to GenAI. Personalised learning, a goal long sought by educators, is now a palpable reality. GenAI can tailor educational pathways to fit individual student needs, thus ensuring that no student is left behind. Beyond personalisation, virtual tutoring systems have started to bridge the gap in areas with teacher shortages. Equipped with GenAI, these systems can provide instantaneous feedback, ensuring continual student progress. Content creation, an integral facet of education, has also benefitted from GenAI. GenAI is pivotal in generating reading materials customised to each student’s reading level and formulating challenging questions based on current curricula. Moreover, GenAI fosters creativity among students. Tools equipped with generative models can assist students in crafting art, composing music, or even writing essays, all tailored to their unique style and preferences. Shifting the lens to communication, the potential of GenAI is equally profound. Automated content generation, once a lofty ideal, is now commonplace. News articles, financial reports, and even creative pieces can be produced by GenAI, often at speeds unmatched by humans. Personalised marketing campaigns harnessing the power of GenAI can target potential consumers with unparalleled precision, ensuring maximum outreach and engagement. Real-time translation, a boon in our increasingly globalised world, has seen leaps in accuracy thanks to generative models. Lastly, natural language processing, a subset of GenAI, has augmented human-computer interactions, making them more intuitive and organic. However, with immense power comes immense responsibility. The adoption of GenAI is full of challenges. Ensuring the accuracy and appropriateness of generated content is paramount. We need robust quality control mechanisms to mitigate the risk of misinformation or inappropriate content generation. Moreover, the sheer dependency on machines raises concerns. More reliance on AI could lead to cognitive stagnation in students, thwarting the very purpose of education. Additionally, the scalability of these models, given their intensive processing power and data requirements, is an area of concern. Ethically, the canvas of GenAI is mottled with grey. AI models, reflecting the data they are trained on, can inadvertently perpetuate societal biases. Ensuring these models are equitable and do not further deepen societal divides is crucial. The potential job displacement due to the widespread adoption of GenAI is a looming concern. GenAI takes over tasks once reserved for humans, so we must ensure a just transition for those affected. Lastly, the issue of authenticity remains salient. In a world where distinguishing between human and AI-generated content becomes increasingly challenging, ensuring trust and transparency is paramount. In conclusion, the future illuminated by Generative Artificial Intelligence is both promising and perplexing. As GenAI continues to reshape teaching, learning, and communication paradigms, our collective responsibility is to ensure that its journey is anchored in ethics, equity, and excellence