It’s no surprise that educators have an uneasy relationship with generative AI. They fear the impact of plagiarism and machine-generated essays and the “hallucinations” — where the system confidently asserts something is true that isn’t simply because it doesn’t know any better — of tools like ChatGPT and Bard. There’s a palpable concern that generative AI will become a substitute for authentic learning: something that will help a person pass a test without the need to absorb and internalize the material.

While there is no doubt that AI has been used to circumvent the learning process, ChatGPT has already assumed the role of an ad hoc personal tutor for millions, changing learning consumption patterns and enhancing our relationship with education. The possibility of an AI-powered teaching assistant — one that mentors, encourages, and guides learners through the material in a one-to-one relationship — is within grasp. And the scalability of AI means that anyone can benefit from it.

AI can make — and, for many, already has made — learning addictive. The reasons why have little to do with cutting-edge advancements in AI and computer science and more to do with the fundamentals of what makes a learner engaged, motivated, and excited.

Growing up in Armenia, I was enthralled by the fiercely competitive math Olympiads, and my desire to win drove me to spend hours studying and practicing. Yet, as an adult, I couldn’t find that same motivation while studying math at MIT. I’ve spent a great deal of my life researching and understanding the motivations behind learning, some of which I’ve distilled into this piece and much of which led to me founding CodeSignal.

What do we mean by addictive?

When I talk about AI making learning addictive, I’m talking about a sense of excitement and eagerness — instilling a voracious appetite for self-improvement and growth within a learner. But, more importantly, it continues long after they’ve accomplished what started their journey. Essentially, this boils down to sustained, long-term motivation. Creating self-motivated learners is a challenge that most educators face, and a mountain of educational research touches on this topic.

It’s hard to overstate the importance of motivation. Whether you’re learning to speak a new language or taking the first steps to a career in programming, learning is inherently iterative, where the learner gradually builds confidence and fluency over time. The prolific programming educator Zed Shaw once described this as “climbing a mountain of ignorance.” Those first few months — when you aren’t confident and don’t understand the subject — are the hardest, and it’s all too easy to give up. And that’s why you need an external force to encourage the learner to keep going. Confidence, ability, and perhaps even greatness are just around the corner.