Course on Artificial Intelligence and Education

Objectives

1. Develop a critical understanding of AI
2. Explore possible role for AI in school education
3. Assess challenges and risks from AI in education

Agenda

Why AI in education?

Jose Van Dyjck - “real-time data about individual learning processes help instructors monitor students’ progress and allow for corrective feedback. Personalized data allegedly provide unprecedented insights into how individual students learn and what kind of tutoring they need. And aggregated data about learning behavior provide the input for individual ‘adaptive learning’ schemes (Higher Education in a Networked World: European Responses to U.S. MOOCs)

AI is seen as having the potential to assist teachers in efficiently and effectively managing multi-level/multi-grade classrooms, by judging learning levels of individual students, and allowing automated development of customised educational content adapted to each student’s class and learning level. Assessing work done by a student on each part/page of the learning material, for example, would allow real-time feedback on student performance to help the teacher appropriately tailor her guidance to the child. (Making AI work for Indian Education, IT for Change)

Challenges to education

Data

Who owns the data? Who controls decisions of collecting, storing, processing, accessing and sharing of data?

Issue of privacy and surveillance.

Additional complexity of students being minors

Collector's keepers

individual ownership’ of data suggested by NITI Aayog paper

Community ownership

Algorithms

Who owns the algorithms? Who certifies algorithms as being fair and ethical?

Can proprietary algorithms be trusted?

In their AI avatar, digital technologies are not merely ‘tools’ that teachers and learners ‘use’, but ‘platforms’ on which they interact. Tools can be subject to the control of the users, while platforms retain control of interactions. As van Dijck says, “These emerging digital policy instruments transfer the assessment of didactic and pedagogical values from teachers and classrooms to (commercial) online platforms deploying real-time and predictive analytics techniques. Control over the algorithms with the platform would subordinate the pedagogical aspirations of teachers and learners to the commercial ambitions of the provider. Proprietary platforms are hence far more dangerous than proprietary software applications.

A report from IDRC identifies five types of short-to medium-term risks associated with the application of AI. Biases, Lack of transparency in decision-making, increased surveillance and loss of privacy, automation leading to job loss, and targeted misinformation. In addition, predictive analytics pose a special threat to the primary purpose of education, which is to develop human agency.

Actors

Private sector providers - Education Initiatives, Byjus, Google, Microsoft and IBM.

MHRD, NCERT

State Governments

Resources

Burt, Andrew, and Samuel Volchenboum. "How Health Care Changes When Algorithms Start Making Diagnoses." Harvard Business Review. May 08, 2018.

Bruner, Jerome. The Culture of Education. Cambridge: Harvard University Press, 1996.

Carnoy, Martin. “School Choice? Or Is It Privatization?” Educational Researcher 29, no. 7 (October 2000).

Cave, Stephen. "To save Us from a Kafkaesque Future, We Must Democratise AI." The Guardian. January 04, 2019.

Chang, Lulu. “Mark Zuckerberg Wants to Share His Daughter Via VR.” Digital Trends. December 11, 2015.

Dewey, John. Democracy and Education. New York: Macmillan Company, 1916.

Dijck, José Van, and Thomas Poell. “Higher Education in a Networked World: European Responses to U.S. MOOCs.” International Journal of Communication9, no. 2015 (September 2015).

Dijck, José Van, and Thomas Poell. “Social Media Platforms and Education.” Edited by Jean Burgess, Alice Marwick, and Thomas Poell. The SAGE Handbook of Social Media: 579-91.

European Commision. “Ethics guidelines for trustworthy AI” December 2018.

Evans, Barbara J. “Much Ado about Data Ownership.” Harvard Journal of Law & Technology 25, no. 1 (Fall 2011).

Loble, Leslie. “Learning to Live in the Time of AI.” UNESCO Courier. August 17, 2018.

Martin, Kirsten. “Ethical Implications and Accountability of Algorithms.” Journal of Business Ethics, 2018.

Muralidharan, Karthik. "Disrupting Education? Experimental Evidence on Technology ..." December 2016.

Nambissan, Geetha B. "Low-Cost Private Schools for the Poor in India: Some Reflections." In India Infrastructure Report 2012. New Delhi: Routledge, 2013.

“National Focus Group on Aims of Education.” NCERT. March 2006.

NITI Aayog. “Discussion Paper: National Strategy for Artificial Intelligence.” June 2016.

Sharma, Yogima. "Niti Aayog Bats for Ending Data Monopoly - ETtech." ET Tech. May 17, 2019.

Smith, Matthew, and Sujaya Neupane. "Artificial Intelligence and Human Development: Toward a Research Agenda." IDRC. April 2018.

Srikrishna, B. N., and Data Protection Committee. “A Free and Fair Digital Economy Protecting Privacy ...”Government of India. July 27, 2018.