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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.

0. Can an entity E be considered a "peer" even if it does not have a physical body ?

1. Can AI ever be a "peer" to a human being or is it a fallacy to believe so ?

2. Should an AI communicate what it is doing (e.g. showing 👂 when listening) or what it expects the human peer to do (e.g. show 👄 when H should speak) ?

3. Can You imagine a competence X which is being simultaneously acquired by a human H and a machine M within the context of their common mutual encounter ?

4. Can You imagine a competence A transmitted from H to M during the same encounter whereby competence B is transferred from M to H ?

5. What other question concerning the human-machine education should also be asked ?

Someone willing to join me on a journey towards
"Encounter": a journal on human-machine education

daniel@udk-berlin.de


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 ?
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