http://crowdtruth.org
Processing real-world data with the crowd leaves one thing absolutely clear - there is no single notion of truth, but rather a spectrum that has to account for context, opinions, perspectives and shades of grey. CrowdTruth is a new framework for processing of human semantics drawn more from the notion of consensus then from set theory.
Truth is a Lie: Rules & Semantics from Crowd Perspectives (RR'2015 Keynote)
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Truth is a Lie
Rules & Semantics from Crowd Perspectives
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“in embracing the diversity of human
beings, we will find a surer way to true
happiness”
Malcolm Gladwell, 2006
in his TED talk “Choice, happiness and spaghetti sauce”
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“If we treat human brains as
processors in a distributed system,
each can perform a small part of a
massive computation”
Luis von Ahn, 2006
“Games with a Purpose”, Computer Magazine
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“The challenge for Watson was to answer questions
posed in every nuance of natural language. The
first step in accomplishing this was to have a lot of
questions and their correct answers. Any cognitive
system must take this first step.”
Chris Welty, 2014
“Cognitive Computing and the Future”, 1st Cognitive Computing Forum
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Take Home Message
True
and
False
is
not
enough,
There
is
diversity
in
human
interpreta3on
CrowdTruth
introduces
a
spa3al
representa3on
of
meaning
that
through
crowdsourcing
harnesses
disagreement
Using
CrowdTruth
untrained
workers
can
be
just
as
reliable
as
highly
trained
experts
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Is this song ….
Passionate
Rousing
Confident
Boisterous
Rowdy
Literate
Poignant
Wistful
Bittersweet
Autumnal
Brooding
Rollicking
Cheerful
Fun
Sweet
Amiable
Good-natured
Humorous
Silly
Campy
Whimsical
Witty
Wry
Aggressive
Fiery
Tense
Anxious
Intense
Volatile
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?Passionate
Rousing
Confident
Boisterous
Rowdy
Literate
Poignant
Wistful
Bittersweet
Autumnal
Brooding
Rollicking
Cheerful
Fun
Sweet
Amiable
Good-natured
Humorous
Silly
Campy
Whimsical
Witty
Wry
Aggressive
Fiery
Tense
Anxious
Intense
Volatile
Is this song ….
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?- category(“That’s not my name”, x)
?Passionate
Rousing
Confident
Boisterous
Rowdy
Literate
Poignant
Wistful
Bittersweet
Autumnal
Brooding
Rollicking
Cheerful
Fun
Sweet
Amiable
Good-natured
Humorous
Silly
Campy
Whimsical
Witty
Wry
Aggressive
Fiery
Tense
Anxious
Intense
Volatile
(Lee and Hu 2012)
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Patients with TYPHUS who were given
ANTIBIOTICS exhibited several side-effects.
With ANTIBIOTICS in short supply,
DDT was used during World War II to
control the insect vectors of TYPHUS.
ANTIBIOTICS are the first line treatment for
indications of TYPHUS.
Does this sentence express
TREATS(Antibiotics, Typhus)?
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TREATS(Antibiotics, Typhus)
Is this True?
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What is the treatment for typhus?
Antibiotic therapy is recommended for both endemic and epidemic
typhus infections because early treatment with antibiotics (for
example, azithromycin, doxycycline, tetracycline, or
chloramphenicol) can cure most people infected with the bacteria.
Consultation with an infectious-disease expert is advised especially
if epidemic typhus or typhus in pregnant females is diagnosed.
Delays in treatment may allow renal, lung, or nervous system
problems to develop. Some patients, especially the elderly, may die.
TREATS(Antibiotics, Typhus)
Is this True?
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TREATS(Corticosteroids, Lupus)
Is this True?
What is the treatment for lupus?
In more severe cases of Lupus, medications that modulate the
immune system (mainly corticosteroids, immunosuppressants) are
used to control the disease and prevent recurrence of symptoms
(known as flares). Depending on the dosage, people who require
steroids may develop Cushing's syndrome. This may subside if and
when the large initial dosage is reduced, but long-term use of even
low doses can cause elevated blood pressure and cataracts.
Numerous new immunosuppressive drugs are being actively tested.
Rather than suppressing the immune system nonspecifically, as
corticosteroids do, they target the responses of individual [types of]
immune cells.
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Human Interpretation
“I will never understand people” “They are the worst”
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human subjectivity, ambiguity & uncertainty of
expression are part of human semantics
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current practices in
computer science (AI)
are based on
fallacies
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single
truth
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experts
rule
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disagreement
is bad
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simplification of context
this all results in
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this means our systems
understand only
simplified
black & white
world
problem ..
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reality is
complex
diverse
but …
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current
gold standard practices
are not adequate any more
so...
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there is a gap
we need to bridge
and …
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interestingly …
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in humanities …
diversity is well accepted
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in sciences …
diversity is taboo
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despite numerous examples …
string theory debate
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global warming debate
and …
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evolutionary bio. debate
gradualismpunctuated equilibrium
and …
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What can we do?
so …
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• collective decisions of large groups
of people
• a group of error-prone decision-
makers can be surprisingly good at
picking the best choice
• when thumbs up or thumbs down - the
chance of picking the right answer
needs to be > 50%
• the odds that a most of them will pick
the right answer is greater than any of
them will pick it on their own
• performance gets better as size grows
1785
Marquis de Condorcet
“wisdom of crowds”
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• asked 787 people to
guess the weight of
an ox
• none got the right
answer
• their collective
guess was almost
perfect
1906
Sir Francis Galton
“wisdom of crowds”
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WWII Math Rosies
1942: Ballistics calculations and flight trajectories
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NASA’s Computer Room
transcribe raw flight data from celluloid film & oscillograph paper
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“Who Wants to Be a Millionaire?”
• help from individual expert or
audience poll
• majority of the audience right
91% of the time
• individuals right only 65% of
the time
“wisdom of crowds”
2004
James Surowiecki
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Crowdsourcing
Human Computing
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the wise crowd
diversity of opinion
independent perspectives
multitude of contexts
gives the big picture
James Surowiecki
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current practices in
computer science (AI)
are based on fallacies
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today’s real-world
complex problem solving
needs understanding of
multiple
perspectives
current practices in
computer science (AI)
are based on fallacies
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single
truth
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multiple
truths
single
truth
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experts
rule
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wisdom
of crowds
experts
rule
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disagreement
is bad
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disagreement
is bad
disagreement
as signal
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“best collective decisions are
result of disagreement,
not consensus or compromise”
James Surowiecki
because …
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can we harness it?
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Is this song ….
?
Passionate
Rousing
Confident
Boisterous
Rowdy
Literate
Poignant
Wistful
Bittersweet
Autumnal
Brooding
Rollicking
Cheerful
Fun
Sweet
Amiable
Good-natured
Humorous
Silly
Campy
Whimsical
Witty
Wry
Aggressive
Fiery
Tense
Anxious
Intense
Volatile
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can indicate
alternative interpretations
Worker Mood-C1 Mood-C2 Mood-C3 Mood-C4 Mood-C5 Other
W10 1 1 1 1 1
Totals 3 5 6 5 2 8
Disagreement as Signal
can indicate
ambiguity in the
categorisation
can indicate
low quality workers
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Does this sentence express
TREATS(Antibiotics, Typhus)?
Patients with TYPHUS who were given
ANTIBIOTICS exhibited several side-effects.
With ANTIBIOTICS in short supply, DDT was
used during World War II to control the insect
vectors of TYPHUS.
ANTIBIOTICS are the first line treatment for
indications of TYPHUS. 95%
75%
50%
Disagreement is signal here too
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Sentence Treat Prevent Cause Side Effect Diagnose
S1 2
S2 2
S3 2
S4 2
S5 1 1
S6 2
S7 2
S8 1 1
S9 2
S10 2
If “One Truth”, “No Disagreement”
& “Experts”
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• we rejected 3 fallacies: one truth, experts rule
and disagreement is bad
• by encouraging disagreement
• we exposed a richer set of possibilities
• that help in identifying, processing &
understanding context
so …
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• One truth: data collection efforts assume
one correct interpretation for every example
• All examples are created equal: ground
truth treats all examples the same – either
match the correct result or not
• Detailed guidelines help: if examples
cause disagreement - add instructions to
limit interpretations
• Disagreement is bad: increase quality of
annotation data by reducing disagreement
among the annotators
• One is enough: most of the annotated
examples are evaluated by one person
• Experts are better: annotators with domain
knowledge provide better annotations
• Once done, forever valid: annotations are
not updated; new data not aligned with old
7 Myths
myths directly influence the
practice of collecting human
annotated data; Need to be
revised with a new theory of
truth (CrowdTruth)
Lora Aroyo, Chris Welty: Truth is a Lie: 7 Myths about Human Annotation,
AI Magazine 2014.
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crowdtruth.org
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crowdtruth.org
a new approach to understanding semantics
harnessing the power & diversity of the crowd
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crowdtruth.org
informs a vector space model of truth
instead of a boolean, fuzzy or statistical model
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observerreferent
sign
has
triangle of
reference
(Ogden & Richards, 1923)
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crowd
annotatorannotation
example
annotation
choices
Lora Aroyo, Chris Welty: The Three Sides of CrowdTruth. J. Human Computation. 1(1). 2014.
triangle of
reference
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crowd
annotatorannotation
example
annotation
choices
passionate,
rollicking,
literate,
humorous,
silly,
aggressive,
fiery,
does
not
fit
into
rousing,
cheerful,
fun,
poignant,
wis9ul,
campy,
quirky,
tense,
anxious,
any
of
the
5
confident,
sweet,
amiable,
bi>ersweet,
whimsical,
wi>y,
intense,
vola?le,
clusters
boisterous,
good-‐natured
autumnal,
wry
visceral
rowdy
brooding
Category 1
Category 3
Category 5
Lora Aroyo, Chris Welty: The Three Sides of CrowdTruth. J. Human Computation. 1(1). 2014.
triangle of
reference
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crowd
annotatorannotation
example
annotation
choices
treat
prevent
side
effect
diagnose
cause
other
Treat
Cause
Prevent
Lora Aroyo, Chris Welty: The Three Sides of CrowdTruth. J. Human Computation. 1(1). 2014.
ANTIBIOTICS are the first line
treatment for indications of TYPHUS.
triangle of
reference
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1 1 1
Worker Vector
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1 1 1
1 1
1
1 1
1 1
1 1
1
1
1
0 1 1 0 0 4 3 0 0 5 1 0
Sentence Vector
OUR
NEW THEORY OF
TRUTH
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Unclear relationship between the two arguments
reflected in the disagreement
Sentence Clarity
Feeling the way the CHEST expands (PALPATION), can identify areas of
the lung that are full of fluid.
?PALPATIONIs CHEST related to
diagnose location associated
with
is_a otherpart_of
0 0 02 3 0 0 0 1 0 0 44 1
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Clearly expressed relation between the two
arguments reflected in the agreement
Sentence Clarity
?CONJUNCTIVITISHYPERAEMIA related toIs
0 0 0 1 0 0 0 013 0 0 0 0 0
symptomcause
Redness (HYPERAEMIA), irritation (chemosis) and watering (epiphora)
of the eyes are symptoms common to all forms of CONJUNCTIVITIS.
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Measures how clearly a sentence expresses a relation
0 1 1 0 0 4 3 0 0 5 1 0
Unit vector
for relation R6
Sentence
Vector
Cosine = .55 confidence
Sentence-Relation Score
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Measured per worker averaged over all sentences
(whether worker consistently disagrees with everyone else)
Worker-Sentence Disagreement
0 1 1 0 0 4 3 0 0 5 1 0
Worker’s
sentence vector
Sentence
Vector
AVG (Cosine)
Worker Quality
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Measured for pairs of workers / sentence
averaged over all sentences
(identify communities of though)
Worker-Worker Disagreement
0 1 1 0 0 1 0 0 0 0 1 0
Worker 1
sentence vector
Worker 2
Vector
AVG (Cosine)
Worker Similarity
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Example Results
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Example Results
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Example Results
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crowdtruth.org
experimental results show that
CrowdTruth is a better way of capturing context
a more accurate way to predict & explain truth
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Training a Relation Extraction Classifier
F1
Cost per
sentence
CrowdTruth 0.642 $0.66
Expert Annotator 0.638 $2.00
Single Annotator 0.492 $0.08
“wisdom of the crowd”
provides training data that is at least as good
if not better than experts
only with proper analytic framework for
harnessing disagreement from the crowd
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Learning Curves
(crowd with pos./neg. threshold at 0.5
above 400 sent.: crowd consistently over baseline & single
above 600 sent.: crowd out-performs experts
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Learning Curves
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Take Home Message
True
and
False
is
not
enough,
There
is
diversity
in
human
interpreta3on
CrowdTruth
introduces
a
spa3al
representa3on
of
meaning
that
through
crowdsourcing
harnesses
disagreement
Using
CrowdTruth
untrained
workers
can
be
just
as
reliable
as
highly
trained
experts
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https://www.youtube.com/watch?v=CyAI_lVUdzM
To be AND not to be: quantum
intelligence?
Lora Aroyo & Chris Welty