Tuesday, January 2, 2018

A.I. and Big Data Are Not the Answer in Education

Today I came across an article in the NY Times entitled A.I. and Big Data Could Power a New War on Poverty. Since the implications of Artificial Intelligence and other technological advances in the 4th Industrial Revolution on education is a topic I've been delving into quite a bit lately, I was curious to see the perspective of the author.

Let me start by saying that I think the author, Elisabeth A. Mason, has a solid premise; we should look beyond the disruptions and chaos that new technologies like artificial intelligence will have on our lives and instead look to the benefits that they can provide society. On this I agree. There are many exciting applications for new technologies that can help alleviate human suffering and can potentially even combat poverty. 

However, I have to take issue with her second main point in the piece that connect directly to education. For reference, here are the three paragraphs that relating to education: 

Second, we can bring what is known as differentiated education — based on the idea that students master skills in different ways and at different speeds — to every student in the country. A 2013 study by the National Institutes of Health found that nearly 40 percent of medical students held a strong preference for one mode of learning: Some were listeners; others were visual learners; still others learned best by doing.

Our school system effectively assumes precisely the opposite. We bundle students into a room, use the same method of instruction and hope for the best. A.I. can improve this state of affairs. Even within the context of a standardized curriculum, A.I. “tutors” can home in on and correct for each student’s weaknesses, adapt coursework to his or her learning style and keep the student engaged.
Today’s dominant type of A.I., also known as machine learning, permits computer programs to become more accurate — to learn, if you will — as they absorb data and correlate it with known examples from other data sets. In this way, the A.I. “tutor” becomes increasingly effective at matching a student’s needs as it spends more time seeing what works to improve performance.

Those of us who are teaching actual children can see some problems here. Let's take them one at a time.

First, the idea that people learn better through different learning styles is a myth (Pashler, et. al.). It has been debunked (Association for Psychological Science). There is no credible evidence to support it (letter to The Guardian from 30 prominent researchers). Even if A.I. was going to lead to an incredible revolution in education, basing that revolution in learning styles is akin to having A.I. teach children differently based on their zodiac signs.

Second, the criticism in the second paragraph that our schools are overly standardized is both harsh and somewhat accurate. For almost two decades now, our education systems have increasingly become driven by big data - generated by mass-produced standardized tests and compiled with the processing power available due to technological advances. This has led to misuse of educational technology, the narrowing of curricula, and a lack of compassion in schools. Children are seen as numbers on a spreadsheet rather than unique individuals with wonderful potential.

Artificial intelligence may be able to adapt to a child's curricular needs, but this is but a small part of what it means to be an effective teacher. Every day, teachers make 1,500 educational decisions. I would bet that the majority of those educational decisions are not curricular in nature and are based in relationships, empathy, and emotional intelligence. This is what makes teachers effective.

Machines may be able to crunch a child's data, but they will never be able to love a student the way a teacher can love a student.

Understanding a student's needs will always be more complex than simply analyzing answers on an assessment. Anyone who has taught understands this. If students in one of my science classes fail a test, I have a responsibility to figure out why. It may be because they didn't study. It may be because they didn't have breakfast that morning. It may be because they misunderstood the lesson. It may be because their baby brother cried all night and they didn't sleep. It may be because they are stressed over a parent's substance abuse. It may be because I did a lousy job of teaching. Each reason demands a different and nuanced response that fits both the child's academic and emotional needs. This is what teaching is.
Graphic from
Teaching in the 4th Industrial Revolution:
 Standing at the Precipice

Assuming that education is only about the transfer of content from teacher to student is a recipe for disaster, especially in our increasingly complex world.

Third, this article is focused upon the ability for artificial intelligence to help alleviate poverty. Our children in poverty are the ones who are most in need of the compassion that robots will never be able to provide. According to the American Psychological Association the psychosocial outcomes associated with children living in poverty include:
  • Children living in poverty are at greater risk of behavioral and emotional problems. 
  • Some behavioral problems may include impulsiveness, difficulty getting along with peers, aggression, attention-deficit/hyperactivity disorder (ADHD) and conduct disorder. 
  • Some emotional problems may include feelings of anxiety, depression and low self-esteem. 
  • Poverty and economic hardship is particularly difficult for parents who may experience chronic stress, depression, marital distress and exhibit harsher parenting behaviors. These are all linked to poor social and emotional outcomes for children. 
  • Unsafe neighborhoods may expose low-income children to violence which can cause a number of psychosocial difficulties. Violence exposure can also predict future violent behavior in youth which places them at greater risk of injury and mortality and entry into the juvenile justice system.
There are important ways that the technological explosion can have a positive impact on education. We must make sure, however, not to repeat the mistakes of the past by believing that technology is the answer to our problems. It is not. Teachers are, and will remain, the most important in-school factor in helping children learn. 

If we really want to overcome poverty, we need to stop looking for easy fixes and cheap solutions. Along with addressing the societal problems that lead to so many of our children living in poverty, we must focus on recruiting, retaining, and supporting excellent teachers so that every child, in every location, receives a quality education.

Michael Soskil is co-author of "Teaching in the 4th Industrial Revolution: Standing at the Precipice." All profits from the book are being donated to promote teacher education, development, and collaboration around the globe.