AI’s Imperativeness in the Future of Education

From the moment we wake up each day, AI knocks on our gadgets and daily routine, multiple times through the day. AI is omnipresent. May it be the GPS, facial recognition on phones, Snapchat filters, Spotify playlists, product recommendations on e-commerce sites, it is everywhere and it is here to stay.

In education, AI has stepped into enabling better school and university pedagogy and while the response has been a mix of appreciation and queries, we cannot but agree that AI has been effective, and intuitive in charting a new course of EdTech. While the question of ethics, the looming clouds on deep learning and the lashing of assistive technology demeriting knowledge systems exists, we need to understand that this is the same that happened each time a new chapter of technology stepped up. So, the question here is not about how to eliminate AI from education but how to ethically and mindfully use the same in bettering knowledge dissemination. Which makes it imperative to engage teachers, leaders, researchers, product innovators, service providers and policy makers in understanding and regulating how AI may shape the future of education.

Move aside one-size-fits all

The traditional education system views students with a unifocal lens. Everyone is taught at the same pace and rare attempts are made to understand individual students’ needs and styles. AI has the potential to cater to a vast number of styles, speed and requirements. Adaptive learning platforms can help shape this. ML algorithm empowers students to learn the way that is best by analysing their pace of understanding, offering extra practice and reinforcing conceptual clarity. Students are motivated, they learn at their own pace, have tailor made experiences, are able to access lessons at ease, their understanding is enhanced, skills develop faster and engagement is better. For educators AI cuts out the human bias and helps analyse the strengths and weaknesses of each student through an objective lens.

Future of AI in education

A report by IDC indicated that the global market of AI-enabled education technology is expected to exceed $150 billion by 2027. A study by McKinsey has confirmed that Machine Learning technologies were boosting students’ academic performance, with 71% of them citing ML powered teaching as a positive innovation. AI could be a potent weapon in the framework of Universal Design of Learning, propelling students to enhance higher level thinking while affirming foundational skills.

AI brings in flexibility, accessibility and customisation.  In the near future Generative will disrupt EdTech even further. From absorbing large amount of curriculum relevant data and resources, and grading styles; to identifying subject matter depth, teaching methods, assessment structures, it can create a contextual and individual centric curriculum that will cater to each student differently. AR and VR will provide immersive learning experiences by turning the abstract into easy bite sized realities. This will make complex concepts more tangible. From learning about minute cells in Biology Labs to understand the vastness of space, AI will make learning more meaningful. Through NLP and ML, it can also help bring accuracy and cut bias in assessments. This is the closest AI can attempt to mimic a human like behaviour but with more accuracy embedded.

Challenges down the way

The path ahead is not easy because AI has for long been marred with ethical considerations. From data privacy concerns, biases in algorithms to accessibility issues, there are issues aplenty. AI needs to be programmed for equity, addressing disparities between genders, social and economic boundaries and public and private. It needs to be built to enhance human led pedagogy and not overtake or replace them. Designing AI for education need to be with the participation of all relevant stakeholders with inputs from teachers, students to experts. Economics viability and access is also a major key point to consider; to prevent deepening the existing digital divide and avoid creating new disparities in education. Using AI to learn about AI and making better decisions is also important, an AI Ethicist is no longer a job of the future but is as relevant in the now. Making policies that merge technology with humanities would be a fine way to pave a future that is deeply human, innovate and inclusive.