Artificial intelligence in educational leadership: a symbiotic role of human-artificial intelligence decision-making

Abstract

PurposeArtificial intelligence (AI) refers to a type of algorithms or computerized systems that resemble human mental processes of decision-making. This position paper looks beyond the sensational hyperbole of AI in teaching and learning. Instead, this paper aims to explore the role of AI in educational leadership.Design/methodology/approachTo explore the role of AI in educational leadership, I synthesized the literature that intersects AI, decision-making, and educational leadership from multiple disciplines such as computer science, educational leadership, administrative science, judgment and decision-making and neuroscience. Grounded in the intellectual interrelationships between AI and educational leadership since the 1950s, this paper starts with conceptualizing decision-making, including both individual decision-making and organizational decision-making, as the foundation of educational leadership. Next, I elaborated on the symbiotic role of human-AI decision-making.FindingsWith its efficiency in collecting, processing, analyzing data and providing real-time or near real-time results, AI can bring in analytical efficiency to assist educational leaders in making data-driven, evidence-informed decisions. However, AI-assisted data-driven decision-making may run against value-based moral decision-making. Taken together, both leaders' individual decision-making and organizational decision-making are best handled by using a blend of data-driven, evidence-informed decision-making and value-based moral decision-making. AI can function as an extended brain in making data-driven, evidence-informed decisions. The shortcomings of AI-assisted data-driven decision-making can be overcome by human judgment guided by moral values.Practical implicationsThe paper concludes with two recommendations for educational leadership practitioners' decision-making and future scholarly inquiry: keeping a watchful eye on biases and minding ethically-compromised decisions.Originality/valueThis paper brings together two fields of educational leadership and AI that have been growing up together since the 1950s and mostly growing apart till the late 2010s. To explore the role of AI in educational leadership, this paper starts with the foundation of leadership—decision-making, both leaders' individual decisions and collective organizational decisions. The paper then synthesizes the literature that intersects AI, decision-making and educational leadership from multiple disciplines to delineate the role of AI in educational leadership.

Integrating artificial intelligence into a talent management model to increase the work engagement and performance of enterprises

“…Table 2 shows that the most important role of AI supported leadership is to developed a clear vision for what was going to be achieved by department, followed by strong leadership to support artificial intelligence initiatives. According to Wang (2021), leaders are an essential part of any enterprise's success. Leaders provide the vision that drives other enterprise employees to realize their goals (Niehueser and Boak, 2020;Wang, 2021).…”

“…According to Wang (2021), leaders are an essential part of any enterprise's success. Leaders provide the vision that drives other enterprise employees to realize their goals (Niehueser and Boak, 2020;Wang, 2021). Technology has strongly interfered with existing ways of working, especially in routine and repetitive tasks.…”

“…This leads to an increase in employees' work performance and employee engagement (Wijayati et al, 2022). According to Bushweller (2020) and Wang (2021), artificial intelligence could help employees in repetitive and time-consuming tasks, which, in turn, would reduce their workload and increase their productivity. Thus, artificial intelligence significantly decreases workplace stress and workload (Dhamija and Bag, 2020;Saxena and Kumar, 2020;Okhifun, 2022).…”

“…Such a task is extremely difficult for humans but easy for artificial intelligence. The use of technology significantly reduces the lead time and eliminates errors (Bushweller, 2020;Sari et al, 2020;Wang, 2021). Thus, we proposed hypotheses: H13: Employee engagement has an effect on performance of the enterprise.…”

Learning design to support student-AI collaboration: perspectives of leading teachers for AI in education

“…In this regard, Utterberg and colleagues (2021) describe teachers as gatekeepers for AI adoption in the classroom, arguing that if teachers do not allow students to interact with AI in the classroom learning activity, AI is not likely to be embedded into the teaching curricula of school. In addition, although some anticipate that AIassisted data-driven, evidence-informed decisions based on the collection and analysis of students' real-time learning data may diminish teachers' leadership, most literature argues that human teachers will remain the masterminds behind AI algorithms, considering the drawbacks of AI-assisted data-driven decision-making in intuition and value consideration (Wang, 2021). Taken together, teachers' pedagogical decision-making is best managed by reviewing and embracing a blend of data-driven, evidence-informed decision-making by AI and value-based moral decision-making by teachers to provide more effective instructional strategies (Zheng, 2020).…”