Annotated Bibliography - AI and education, a guidance for policymakers (Miao et al, 2021)

Miao, Fengchun, et al. AI and education: A guidance for policymakers. UNESCO Publishing, 2021.

The book “AI and education: A guidance for policymakers”, written by Mian et al (2021) and published by UNESCO, is a very interesting publication about what artificial intelligence is and how it has impacted education thus far. 

The book really starts on chapter 2, where it gives an overview on the history of A.I., its different techniques (Machine Learning, Neural Networks, Deep Learning), some of the biggest players in the industry (Alibaba, Amazon, Baidu, Google, IBM, Microsoft and Tecent), and its current biggest applications (Journalism, Legal Services, Weather Forecasting, Fraud Detection, Robotics, autonomous warfare and etc).   The chapter also presents the main technologies concerning A.I., which is reproduced below: 

On Chapter three, the book recalls the history of the use of AI in educational contexts, which can be traced back to 1970. More recently, A.I. in education has been developing in multiple directions, may it be student-facing A.I (for support to learning and assessment), teacher-facing A.I. (to support teaching) and system-facing A.I. (to help in the management of educational institutions). The field of A.I. and education is even evolving in the direction to teaching humans to better understand and deal with A.I., its techniques, and to live in an era empowered by A.I. 

Chapter three also raised consideration to ensure the ethical, inclusive and equitable use of A.I. in education. Many possible issues are based on the use of data and algorithms, the digital divide and the student's right to privacy, and the equality in regards to gender, disability, social and economic status, ethnic and cultural background. UNESCO developed a framework for the ethical application of A.I. in education called ROAM (“Rights, Openness, Access and Multi-stakeholder”). 

The third chapter continues by analyzing how the education system could better be prepared to live and work in the age of A.I. The authors start by recognizing that there are tasks that computers can perform better, like recalling data, recognizing patterns and statistical reasoning. And there are tasks that humans can perform better, like empathy, self direction, common sense and value judgements. Therefore, the pedagogy of the era of A.I. puts emphasis on human skills, like critical thinking, communication, collaboration and creativity, and also to collaborate with ubiquitous A.I. tools that will transform life, learning and work. In fact, in the same way that today's professionals require “computer literacy” to work in the age of the ubiquitous internet, tomorrow´s workers will have to have “A.I. literacy” so they can build their agency, employability and their ability to contribute to society. Professionals in the age of A.I. will have to be life-long learners and understand how the A.I. technologies work, in particular how data is selected, manipulated and interpreted. 

The following chapter, the fourth, analyzes the biggest challenges in using A.I. to achieve educational outcomes. It starts by mentioning the importance of data ethics and algorithmic biases. It continues by mentioning the impact that A.I. will have on the teacher role (allowing them to focus on the human aspect of teaching, rather than the burdens of monitoring progress of the students). The chapter 4 also mentions how A.I. is expected to impact the learners´ agency, like their resourcefulness, critical thinking, independent thought and other 21st  century skills. 

Then, chapter five continues by discussing different policy approaches by governments around the world, such as in Argentina, China, Estonia, Europe, UAE and USA. It focuses primarily on the areas of concern that should be addressed in legislation, such as governance over data and privacy, the financing of A.I. development and international cooperation and finishes up by proposing that policy makers should have a systems-wise vision of A.I. and education, ensuring that it is inclusive, equitable and allows the safe and auditable use of educational data of students.