Your Professor Will Not Be Robot Maria, Robbie, or Sophia: Reminders of Human Need and Basic Equity Planning

Abstract

Pro-innovation biases are common reactions to novelty and the promise to solve problems (Dearing & Cox). Some may see a future where robot teachers are normative and cheap, alongside robots that deliver packages. Dismantling the U.S. Dept. Education weakens policies, abilities to inform, bring knowledge to, and lift up common citizenry. More than a mouthpiece attached to a body, human educators have made use of technological innovations, over generations, to bring curriculum to many students/learners. The instructor, building from pedagogical knowledge and experience, chooses area content and teaching-learning tools most suitable, available, affordable (Stuyniski). Machines (tablets, laptops, etc), apps, media, were invaluable during COVID. World communities learned that electricity, internet, and equipment ownership are necessary to join a parallel education system online. The U.S. “least educated” states suffer low incomes (World Population Review) and experience compounded problems. Non-white ethnic/racial neighborhoods experience lower incomes and related issues. Elite neighborhoods and developed metropolitan cities take advantage of innovations for any purpose, thus perpetuating gaps (World Monetary Fund). U.S. educational inequities will not be solved by AI tutor apps created by venture capital investors. Innovations are tools, to be selected, put to work by instructors, professors. Innovations are not “replacements” for planning curriculum and learning modules for student-learners. Robotics of popular imagination, and products from private development laboratories, are intriguing. And, human educators, public good policies, are still greatly needed across educational realms (Labor Projections). Finally, basic human needs and economic inequalities are persistent battles to be won.

Presenters

Diana Rios
Faculty Communication and EL Instituto: Latino-Latin American Caribbean Studies, Department of Communication, University of Connecticut, Connecticut, United States

Mary Helen Millham
Contributing Faculty, School of Communication, University of Hartford, United States

Details

Presentation Type

Poster Session

Theme

2025 Special Focus: Human Learning and Machine Learning—Challenges and Opportunities for Artificial Intelligence in Education.

KEYWORDS

ROBOT, INSTRUCTORS, PROFESSORS, PRO-INNOVATION BIAS, INCOME AND RACIAL INEQUITIES, TRENDS