Ethical Artificial Intelligence for the Future of Education
Artificial intelligence (AI) technology has been rapidly transforming various industries in recent years, and education, of course, is no exception. With the ability to analyze vast amounts of data, personalize learning experiences, and automate administrative tasks, AI technology is changing the way we learn and teach. Nonetheless, as with any technological innovation, AI also raises important ethical questions that must be considered in its implementation.
There are several ways in which AI is transforming education, for example: personalized learning. Educational platforms using vast amounts of collected student data can create specific learning paths for each student, adapting to each specific student’s learning habits, pace and performance, and providing targeted feedback, content and recommendation on specific areas of improvement. This can significantly enhance learning outcomes and make education more accessible to diverse learners.
Another area where AI is making significant contributions to education is in administrative tasks. AI-powered tools can automate grading, attendance tracking, and other routine tasks, freeing up teachers’ time to focus on more meaningful interactions with students. AI chatbots can also assist students in answering frequently asked questions and providing immediate feedback on their work.
However, this use of AI also raises a few ethical concerns. For example, since most of the AI systems today are based on Machine Learning, which means the machine “learns” to generate probabilistic outputs based on the statistical distribution of the data it has learned from, these systems can end up reinforcing biases which already exist in the data used for training, which can perpetuate, and in some cases exacerbate, existing prejudices in areas such as race, gender, and socioeconomic status. We have already seen this happening in systems built for resume selection, which exacerbated gender bias, or in lending systems which generate outputs biased on race or socioeconomic status inferred through geolocation and other factors within the data.
As a thought experiment, if we used historic education data as it has been collected so far to create an AI system to recommend future learning opportunities to young adults, we would probably end up with a heavily biased system which recommends STEM careers more frequently to male students than female students, and might also withhold recommending highly academic careers to people from lower socioeconomic backgrounds. This would happen because statistically, both of the above prejudices have been a reflection of past decisions made by biased individuals in biased societies.
We can face biases in AI by prioritizing transparency and accountability in the development and implementation of AI technology in education. This includes ensuring that algorithms are trained on diverse and unbiased data, making the decision-making process of AI systems understandable and explainable, and providing opportunities for human oversight and intervention, when necessary, amongst other ethical practices.
Another complex ethical concern has to do with the role of teachers in the education system. As more learning resources and experiences become available in a digital world, do we need teachers at all? And if we do: What role should they play? This is the big will machines replace people argument. What we have seen, as technology advances, is that most often, automatizations leads to freeing up people to focus on things that bring more value. In the case of teachers, AI systems can free them from most administrative tasks and some of the more technical teaching tasks to focus more on fostering some of the most important skills in their students like critical thinking, creativity, and emotional intelligence, as well as focus on helping students develop best practices in the use of the AI systems, they will be interacting with all the time. In short, we can free up teachers’ time so they can focus their time and energy in teaching what is most important at this junction in time: socioemotional skills.
The advantages of AI systems in education are many, so many in fact, that we must embrace them. Nonetheless we should do this in an ethical manner, which requires us to prioritize collaboration between stakeholders in the education sector, including educators, policymakers, and technology developers. By involving diverse perspectives in the development and implementation of AI technology in education, we can ensure that it is ethically responsible and aligned with the values of education.
The future of education is much brighter than the possible pitfalls, and to reach it’s full potential we must focus on building safe, trustworthy and ethical AI systems, for students, teachers and everyone involved in it.
Let us build AI for a better future together.
