#HitAI Background

Explicit Human-in-the-loop (HITL) Articficial Intelligence - Machine Learning

Similar approches are called human-in-the-loop (HITL) Artificial Intelligence or human-in-the-loop Machine Learning. The major difference between #HitAI and HITL is that HITL aims to pursue models that explicitly put humans in the loop of AI/ML systems by giving them a way to control the behavior of these systems. On the contrary, #HitAI assumes that any AI/ML system has humans in the loop.

Workshops

Ecosystems

Interpretable/Explainable Machine Learning

Generally, interpretable/explainable machine learning is strongly connected to the idea that we should know exactly why systems take decisions. In addition to that, #HitAI aims to trace back the decision to the exact knowledge that justified that decision.

Workshops

Interest Groups

Data Protection and Identity-aware Ecosystems

Workshops

Interest Groups

Protocols