The Potential and Limitations of AI Chatbots as Learning Assistants in Education
Can AI chatbots be helpful for education? The idea is intriguing, considering that most children worldwide have direct or indirect access to a smartphone. Imagine opening WhatsApp to find your personal tutor that can answer "all" your questions. This vision drives many pilot projects and digital learning platforms like Duolingo, the Khan Academy, and Squirrel, which I wrote about some time ago. Can the human-like conversation we are now getting used to from ChatGPT lead to such a personal tutor in your pocket?
The intricacy of learning is frequently underestimated when new AI initiatives are lauded.
Breaking Down the Potential and Challenges of AI Chatbots in Education
To understand the potential and challenges, one must break down the topic into different pieces. What subjects could they train on? A chatbot for highly standardized subjects like math or natural science differs from one teaching the interpretation of a novel. Although grammar rules of a language can be taught through quizzes and tests, online learning already contributes significantly to education. However, learning to deal with complex situations and scenarios, critical in many life and business situations, is very difficult to teach when communicating with a machine. No technology can replicate the engaging, interactive atmosphere created by a live instructor and learning in a group of students. Therefore AI chatbots can only be used for a limited set of subjects and tasks.
From Tangible to Intangible: The Evolution of Global E-commerce in the Digital Age
Ecommerce: The Difference between Physical and Digital Goods
As the digital economy continues to grow, so do non-tangible products. Often, when discussing ecommerce online, the focus is solely on selling physical goods. However, it is important to distinguish between the two domains of selling physical products and digital products or services because they have entirely different business models. Physical products require inventory and storage, as well as relying on certain logistics. Platforms like Shopify have built a whole ecosystem to support small business owners in selling their products, while Etsy offers a platform for selling artisanal products from the comfort of one's own home. Physical products also face geographical challenges when sold internationally; the recent example of Brexit causing complicated customs regulations has significantly impacted many small online retailers' businesses. I have written more about this issue here.
Selling digital products and services has become much easier online. In the past, during the early 2000s, not many people would have been willing to pay for online courses, excel templates, or ebooks because payment systems were not available and these types of digital products were not widely offered. However, over the last decade, there has been a significant shift in this trend as online courses and templates for various services (such as Notion) have emerged as potential sources of revenue.
The End of Abundance? The Unsustainable Hunger of Large Language Models
Artificial intelligence models are like insatiable giants, constantly needing to grow in size in order to produce better results. This is particularly true for large language models (LLM) such as ChatGPT, Claude, or LLama. While not all AI models need to be large, these language models require billions of lines of text to function effectively. Openai has not disclosed the exact source material used for their ChatGPT models, but experts speculate that it includes a vast amount of publicly available information from the internet as well as books and news articles. This has led to legal disputes, such as the New York Times suing Openai. The larger and more diverse the input of text, the stronger the model will be. This is why ChatGPT excels in broader topics with extensive content available, but may struggle in more specialized subjects. Additionally, much of human knowledge cannot be readily, if at all, codified or documented, which is frequently overlooked amidst the excitement surrounding large language models.