From Algorithm Worship to the Art of Human Learning: Insights from 50-year journey of AI in Education

Over the past decade, there have been increasing proclama5ons from diverse stakeholders that humanity is at an inflec5on point due to advances in Ar5ficial Intelligence (AI) technologies (e.g., Crawford, 2017). The general public are condi5oned by this messaging to expect both big (though so far largely non-descript) changes to our lives, including to the way that we learn and teach. Warnings have been also ar5culated regarding whether and how AI might fundamentally change the way we perceive reality, how we form our beliefs, or interact with one another (Bostrom, 2017). More recently, ques5ons started to emerge about AI's transforma5ve poten5al (for beLer or worse) for our func5oning at neurocogni5ve, socio-emo5onal, individual and collec5ve levels (UNESCO, 2022; Pedro, et al., 2019, Porayska-Pomsta, 2023), along with concerns regarding the ethical implica5ons of using AI for suppor5ng human decision-making in contexts that are both high-stakes (e.g., for medical diagnoses or for student assessment) and rela5vely low-stakes, e.g., selec5ng movies on streaming sites. Such hope-fear rhetoric is also present in the context of AI applica5ons to suppor5ng human learning in formal and informal contexts. Recent hopes for AI in educa5on (AIED) largely relate to delivering learning at scale across different geographical and cultural contexts, especially in light of growing global teacher shortages and diminishing funding for educa5on in many countries (UNESCO, 2023). These hopes are increasingly used to fuel poli5cally and market mo5vated discourse about the need to'release teachers from tedious tasks' such as standardised assessments to allow them to focus on the'things that maLer' (Gen5le et al., 2023), or to jus5fy the narrowing of the formal educa5on curricula mainly to STEM subjects.