human-centered artiﬁcial intelligenceriedl/talks/yconf.pdf · fortune favors the brave. harrison,...

Human-Centered  Artificial IntelligenceMark Riedl [email protected] @mark_riedl

Alien intelligences

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Alien intelligences• Artificial intelligences are  

inscrutable to most humans

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Alien intelligences• Artificial intelligences are  

inscrutable to most humans

• Humans are inscrutable to  artificial intelligences

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Human-centered artificial intelligence

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Understanding humans


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Helping humans understand them


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Computational creativity


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Challenges & opportunities

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Specifying goals

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Commonsense goal failure• Do what I want…

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… the way I would do it!


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… the way I would do it!

• Knowledge bases?

• Lots of sensors?

• Demonstration?

Learning from stories

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• If computers could comprehend stories then humans can transfer commonsense procedural knowledge to computers by telling stories

Machine enculturation• Human cultural values are implicitly encoded in stories

told by members of a culture

• Allegorical tales

• Fables

• Contemporary fictional  literature, TV, & movies

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Riedl. CHI Workshop on Human-Centered Machine Learning, 2016.

Natural language• Natural language processing is not a solved problem

• Humans are noisy (variable)

• Humans shouldn’t need to know autonomous system capabilities or execution environment

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Quixote• Reinforcement learning: AI devises a “program” for

operating in an environment through trial and error

• Intuition: Reward the agent for  performing actions that mimic  the stories that it has been told

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Harrison & Riedl. AIIDE Conference, 2016.

Quixote

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1015

Model learning

Trajectory tree creation

Reward assignment

Reinforcement learning

Exemplar stories A model A trajectory tree

A trajectory tree with events assigned reward valuesA policy mapping

states to actions

Environment

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choose restaurant

drive to restaurant

walk/go into restaurant

read menu

choose menu item

wait in line

drive to drive-thru

take out wallet place order

pay for food

wait for food

drive to window

get food

find table

sit down

eat food

clear trash

leave restaurant

drive home

Fast food restaurant

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arrive at theatre

wait for ticket

go to ticket booth

buy tickets

choose movie

go to concession stand

order popcorn / soda show tickets

buy popcorn

enter theatre

find seats

turn off cellphone sit down

eat popcorn watch movie

hold handsuse bathroom discard trash

talk about movie

leave movie

drive home

kiss

Going on a date to the

movies

Quixote

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10

1015

Model learning

Trajectory tree creation

Reward assignment


Exemplar stories A model A trajectory tree

A trajectory tree with events assigned reward valuesA policy mapping

states to actions

Environment

• Fill gaps between events


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World state space

Leave House

Go to bank Go to hospital Go to doctor

Don't get prescription hospital Don't get prescription doctor

Get prescription hospital Get prescription doctorWithdraw money

Go to pharmacy

Buy strong drugs Buy weak drugs

Go home




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World state space

Leave House




Go to pharmacy


Go home

leave house




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World state space

Leave House




Go to pharmacy


Go home

leave house

go bank

go hospital

go doctor




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World state space

Leave House




Go to pharmacy


Go home

leave house

go bank

go hospital

go doctor

Drive Main St.

Stairs


Machine enculturation• Social conventions prevent conflict

• Robots that follow the “rules” of society will be safer

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Riedl. CHI Workshop on Human-Centered Machine Learning, 2016.


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Autonomous system failures

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Possible solution: open the black box

AI rationalization

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Harrison, Ehsan, Riedl. arXiv 1702.07826, 2017.

AI rationalization• Creating an explanation comparable to what a human

would say if he or she were controlling the robot in the same situation

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• Takes inspiration from what humans do

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• Human understandable

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• Human understandable

• Helps build trust; useful in time-critical situations

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Neural machine translation

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4 10 3 0 3 0 3 0 3 3 3 2 2 2 3 3 -1 -1 -1 -1 -1 -1 -1 2 3 3 2 3 2 3 2 2 2 3 3 3 3 2 2 3 2 3 2 2 0 0 0 0 0 0 0 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 0 0 0 0 1 1 1 1 0 0 0 1 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 3 10 -1 -1 -1 -1 -1 -1 -1 2 3 3 2 2 2 3 3 2 2 3 3 3 2 3 2 3 3 2 3 2 -1 -1 -1 -1 -1 -1 -1 3 2 2 3 2 3 2 0 0 0 0 0 0 0 0 0 1 0 1 0 1 0 0 0 1 1 1 0 0 0 0 0 0 1 1 0 0 0 1 1 0 0 1 0 0 0 1 1 0 -1 -1 -1 -1 -1 -1 -1

Woah! Car beside me and a gap above. Fortune favors the brave.



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4 10 3 0 3 0 3 0 3 3 3 2 2 2 3 3 -1 -1 -1 -1 -1 -1 -1 2 3 3 2 3 2 3 2 2 2 3 3 3 3 2 2 3 2 3 2 2 0 0 0 0 0 0 0 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 0 0 0 0 1 1 1 1 0 0 0 1 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 3 10 -1 -1 -1 -1 -1 -1 -1 2 3 3 2 2 2 3 3 2 2 3 3 3 2 3 2 3 3 2 3 2 -1 -1 -1 -1 -1 -1 -1 3 2 2 3 2 3 2 0 0 0 0 0 0 0 0 0 1 0 1 0 1 0 0 0 1 1 1 0 0 0 0 0 0 1 1 0 0 0 1 1 0 0 1 0 0 0 1 1 0 -1 -1 -1 -1 -1 -1 -1



AI Rationalization

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AI Rationalization• Target users are those without technical backgrounds

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• Meant to convey fast, approximate explanations

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• Meant to foster rapport and trust

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• Meant to foster rapport and trust

• Coupled with more thorough explanations & visualizations

25Work by Alex Endert,

Georgia Tech


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Understanding helps AI

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4 10 3 0 3 0 3 0 3 3 3 2 2 2 3 3 -1 -1 -1 -1 -1 -1 -1 2 3 3 2 3 2 3 2 2 2 3 3 3 3 2 2 3 2 3 2 2 0 0 0 0 0 0 0 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 0 0 0 0 1 1 1 1 0 0 0 1 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 3 10 -1 -1 -1 -1 -1 -1 -1 2 3 3 2 2 2 3 3 2 2 3 3 3 2 3 2 3 3 2 3 2 -1 -1 -1 -1 -1 -1 -1 3 2 2 3 2 3 2 0 0 0 0 0 0 0 0 0 1 0 1 0 1 0 0 0 1 1 1 0 0 0 0 0 0 1 1 0 0 0 1 1 0 0 1 0 0 0 1 1 0 -1 -1 -1 -1 -1 -1 -1


Punchline

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Training iterations (x100)

Aver

age

rew

ard

Punchline

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Aver

age

rew

ard

Standard Q-learning

Punchline

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Aver

age

rew

ard

Standard Q-learning

Learning from demonstration

Punchline

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Aver

age

rew

ard

Standard Q-learning

Learning from demonstration

Language-based guidance

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Computational creativity

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Computational creativity

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Computational creativity• Most computational creativity is learning a pattern from

data and trying to make new inputs fit the pattern

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• AI can’t reach human-level creativity without making intuitive leaps

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• AI can’t augment human creativity if AI can’t keep up with human collaborator’s intuitive leaps

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• AI can’t augment human creativity if AI can’t keep up with human collaborator’s intuitive leaps

• Computational creativity is about making AI gracefully handle novel situations it was never trained for

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+ = ?

Concluding thoughts• AI appears less “alien”

• Maybe safer?

• Computational creativity to  handle contingencies  very different from input

• Human-centered AI is an  essential mix of capabilities for robots in the human world

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human-centered artiﬁcial intelligenceriedl/talks/yconf.pdf · fortune favors the brave. harrison,...

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