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I was recently recognized by , as an .

I put forth an agenda of - that are designed to model, reason, and learn about their human partners -supporting them in their goals and pursuits.

It is , research but extremely . We start with studying what is the human trying to do and what intelligent support do they need.

A thread below -

In our intro to we have been told that this is what an , an is.

But this is not the correct picture.

In any reasonable deployment, there is going to be humans involved.

Humans are the MAIN decision makers in an deployment. We can't ignore them. We can't pretend they don't exist. We can't pretend that thinking about the humans doesn't matter and that that is everything.

Shiwali Mohan | शिवाली मोहन

studies 3 questions:

1. How do we model a human so that an can reason with it? How to find a _prescriptive_ model? Human-centered sciences have a starting point.

2. How do we design an ?

3. How to we measure progress? THE most critical question. As people, we are enamored byaccuracy, scale etc. But, in research, we have to study what humans care about.

The potential is interdisciplinary.

3: , , - how can complex learn from humans? is large part of that puzzle.

Focus on , - what does it mean to 'understand' language for communication, collaboration, & teaching.

Not which research studies.

2021: arxiv.org/abs/2102.06755
2020: arxiv.org/abs/2006.01962
2014: arxiv.org/abs/1604.02509

Most , research assumes the first configuration in the figure below. We take it for granted that a human will fully delegate a task to the

That couldn't be further from reality. For a long time, humans and /#ML systems will have to work together in various configurations.

looks at what is typically overlooked in , - how do we bring humans in the loop.