@Niloufar Right!

Experimentation in #AI #ML is limited. The field doesn't even know how to evaluate intelligent systems with people. Worse, the development approach starts with data and not from understanding what humans do & what it means to support them.

At #PARC, drawing inspiration from #HCI, we are exploring a design process #CollaborativeHumanAISystems and human participant evaluation is a significant part of it.

But, socializing this research has been a challenge in our hype-y world.

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

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

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

#CollaborativeHumanAISystems 3: #ITL, #InteractiveTaskLearning, #HumanRobotInteraction - how can complex #agents learn from humans? #language is large part of that puzzle.

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

Not #InformationRetrieval #IR which #NLP research studies.

#IEEE #ROMAN 2021: https://arxiv.org/abs/2102.06755
#ACS 2020: https://arxiv.org/abs/2006.01962
#ACS 2014: https://arxiv.org/abs/1604.02509

#CollaborativeHumanAISystems 2: #Sustainability #Transportation #BehaviorInfluence, #CognitiveAI

#JAIR 2019: https://www.jair.org/index.php/jair/article/view/11352
#AIES 2019: https://dl.acm.org/doi/abs/10.1145/3306618.3314271
#ACM #IUI #Humanize 2019:

https://ceur-ws.org/Vol-2327/IUI19WS-HUMANIZE-2.pdf

#CollaborativeHumanAISystems 1: #HealthBehaviorChange, #AICoaching for #Health, #CognitiveAI

AAAI 2017: https://ojs.aaai.org/index.php/AAAI/article/view/19101
ACM TiiS 2020: https://arxiv.org/abs/1910.04836
ACM TiiS 2021: https://arxiv.org/abs/1910.07728

JMIR 2017: https://www.jmir.org/2017/11/e397/
IEEE EMBC 2016: https://ieeexplore.ieee.org/abstract/document/7591428

#CollaborativeHumanAISystems studies 3 questions:

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

2. How do we design an #intelligent #collaborator #agent?

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

The potential #impact is interdisciplinary.

My work was recently recognized with #MichiganAI, #UMichCSE as #AI #RisingStar.

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

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

A thread below -

I am a principal at #Xerox #PARC - yes - the famed place that invented all of personal computing and had it stolen ;)

Currently, studying the frontier of #CollaborativeHumanAISystems or often fondly called #HumanAwareAI.