The module, CSC8611 Human-Artificial Intelligence (AI) Interaction & Futures, offered at Newcastle University, delved into the critical intersection of human experience and artificial intelligence. Designed by Jan Smeddinck and co-taught with Yu Guan, the course challenged traditional AI/ML curricula by emphasizing human impact and user interfaces, rather than solely focusing on algorithms.
A significant portion of the module explored the historical context of AI, tracing its evolution from early concepts like automata and cybernetics through various “AI springs” and “winters.” It highlighted the shift from ambitious promises of general intelligence to more specific, applied AI solutions, and the eventual resurgence of machine learning, particularly deep learning, driven by increased data availability and computational power.
Among the advanced topics, a notable guest lecture was delivered by Viana (Nijia) Zhang, who discussed conversational interfaces. Her insights, even in the GPT-2 / 3 era, foreshadowed considerations about generative AI and Large Language Models in conversational interfaces for sensitive application areas such as mental health of lone working parents, which was the focus of her PhD research at the time.
Key themes of the course included the pervasive nature of AI in daily life, the importance of Human-Data Interaction (HDI), and the ethical considerations surrounding algorithmic bias and fairness. The course encouraged critical thinking about how AI systems were evaluated, moving beyond mere accuracy to consider the societal implications and the need for human oversight and interpretability.