Hi everyone. I am Matt Wallace, and I am glad to be here today to talk about the exciting topic of artificial intelligence in language learning. In this article, I want to challenge the traditional ways of thinking about this issue and explore the frameworks that can help us navigate this challenge.
Firstly, let me confess that I wrote this presentation myself, and I believe it’s important to address some of the issues that were brought up in the conference. While AI is a buzzword that means many different things, in this context, I am specifically referring to large language models, such as ChatGPT, which are built on the prediction machine concept.
Large language models, like ChatGPT, are powerful tools that can predict the next word based on the combinations of words in a prompt. However, they are arguably incapable of fresh new innovation. This lack of entrepreneurial spirit is a concern, but it doesn’t mean that these models are not useful. They are turning our assumptions about value creation in market economies upside down.
To explore the possibilities of AI in language learning, we conducted three experiments using a prototype AI bot called Busy. In the first experiment, we delivered a specific curriculum with individualized learning outcomes. Each person had a different experience, but the learning outcomes were the same. In the second experiment, we focused on building business models with Busy, helping participants design their value propositions and understand how to approach customers. The third experiment involved providing an ‘ask me anything’ coach, who could provide guidance on various business-related questions.
These experiments have shown that when we put tensions into play, we can achieve dynamic delivery, ecosystem-level impact, and supercharged mentorship. By combining AI technology with human touch, we can create individualized experiences that are both useful and innovative.
However, I must express my concern about the current state of AI tools that claim to eliminate loneliness or provide generic business advice. Instead, we should focus on serving entrepreneurs through networks and mentorship, leveraging AI to enhance the mentorship experience. This approach can have a profound impact on entire ecosystems, as demonstrated by the Galley data on acceleration programs.
In conclusion, I invite you to join us on this journey of exploring the tensions and possibilities of AI in language learning. By embracing individualized experiences, focusing on ecosystem-level impact, and combining technology with human touch, we can create sustainable and impactful solutions. Scan the QR code and share your email address to stay updated on our progress. Thank you for your time and let’s embark on this exciting adventure together!
