In this Boardroom Dialogue we will discuss the possibility of humans and AIs becoming "peers" in helping each other to acquire skills and competences.
The dialogue will start with introducing the concept of Human-Machine Peer Learning (HMPL) and exploring its potential to provide a paradigm for constructing human-machine learning curricula from which both humans as well as machines benefit.
Participants will acquire both the theoretical concept of human-machine peer learning and concrete insights into how HMPL is implemented through the illustration of two prototypical learning scenarios where HMPL is already deployed.
Note that HMPL is more than a theoretical concept. It is happening. Here. Now.
Humanity teaches the big & mighty ones (e.g. GPT4, DALL-e 3) and big & mighty ones provide educational & cognitive services in return.
But what about the "small" ones, the "adaptive" ones, the "personalized" ones, the embedded (or embooked ?) ones ?
Human–Machine Peer Learning (HMPL) is a proposal that is positioned at the very frontier between educational, cognitive, and computer sciences. HMPL's core precepts which I introduced in my 2022 and 2023 papers are simple:
Humans and machines can learn together.
Humans and machines can learn from each other.