Human Generated Data

Title

Untitled (nine photographs: Cuban revolutionaries)

Date

c. 1950, printed later

People

Artist: Lester Cole, American

Classification

Photographs

Credit Line

Harvard Art Museums/Fogg Museum, Transfer from the Carpenter Center for the Visual Arts, American Professional Photographers Collection, 4.2002.12259

Human Generated Data

Title

Untitled (nine photographs: Cuban revolutionaries)

People

Artist: Lester Cole, American

Date

c. 1950, printed later

Classification

Photographs

Machine Generated Data

Tags

Amazon
created on 2022-02-25

Poster 99.8
Advertisement 99.8
Collage 99.8
Person 99.3
Human 99.3
Person 99.1
Person 99
Person 98.3
Person 98.3
Person 97.4
Person 92.3
Person 90.8
Person 88.9
Machine 85.9
Wheel 85.9
Person 85.3
Person 83.5
Wheel 78.1
Person 73.2
Person 72.8
Person 63.8
Person 60.7
Head 58.3
Vehicle 55.1
Transportation 55.1

Imagga
created on 2022-02-25

equipment 30.5
cassette tape 25.1
device 24.9
magnetic tape 21.9
old 20.9
electronic equipment 19.4
technology 19.3
case 17.2
memory device 17.2
radio 14.7
cassette 14.4
business 13.3
retro 13.1
metal 12.9
finance 12.7
safe 12.7
wealth 11.7
vintage 11.6
electrical 11.5
system 11.4
television 11.2
money 11
close 10.8
black 10.8
computer 10.7
box 10.6
audio 10.5
loudspeaker 10.5
detail 10.4
sound 10.3
wall 10.3
church 10.2
architecture 10.1
amplifier 10.1
power 10.1
door 10
currency 9.9
religion 9.8
bank 9.8
art 9.7
texture 9.7
container 9.7
object 9.5
antique 9.5
storage 9.5
grunge 9.4
light 9.3
safety 9.2
security 9.2
stereo 9.2
music 9
digital 8.9
information 8.8
industry 8.5
design 8.4
electric 8.4
network 8.3
sign 8.3
banking 8.3
cash 8.2
financial 8
market 8
interior 8
lock 7.9
broadcasting 7.8
dollars 7.7
cable 7.6
electronics 7.6
pattern 7.5
savings 7.4
monitor 7.4
plastic 7.3
connection 7.3
data 7.3
film 7.2
science 7.1
modern 7

Google
created on 2022-02-25

Microsoft
created on 2022-02-25

text 96.4
land vehicle 95.7
vehicle 92.6
wheel 91.6
bunch 70
car 67.2
tire 55.2
black and white 52.8
different 44.9
several 12.4

Face analysis

Amazon

Google

AWS Rekognition

Age 33-41
Gender Female, 93.2%
Calm 99.6%
Surprised 0.3%
Sad 0%
Disgusted 0%
Angry 0%
Happy 0%
Fear 0%
Confused 0%

AWS Rekognition

Age 24-34
Gender Female, 99.8%
Happy 94.3%
Calm 2.9%
Sad 1.4%
Surprised 0.3%
Angry 0.3%
Disgusted 0.3%
Confused 0.3%
Fear 0.2%

AWS Rekognition

Age 25-35
Gender Female, 72.6%
Calm 72.1%
Fear 16.1%
Happy 8.8%
Sad 1%
Disgusted 0.7%
Surprised 0.6%
Confused 0.5%
Angry 0.2%

AWS Rekognition

Age 21-29
Gender Male, 99.9%
Happy 100%
Calm 0%
Surprised 0%
Sad 0%
Angry 0%
Confused 0%
Disgusted 0%
Fear 0%

AWS Rekognition

Age 24-34
Gender Male, 99.8%
Calm 49.3%
Sad 32%
Happy 4.8%
Confused 4.7%
Angry 3.2%
Fear 2.1%
Disgusted 2.1%
Surprised 1.8%

AWS Rekognition

Age 21-29
Gender Male, 99.7%
Happy 82.7%
Calm 16.8%
Disgusted 0.1%
Surprised 0.1%
Angry 0.1%
Confused 0.1%
Sad 0.1%
Fear 0.1%

AWS Rekognition

Age 35-43
Gender Male, 99.9%
Happy 87.2%
Calm 4.6%
Fear 4%
Surprised 1.5%
Sad 1.2%
Disgusted 0.6%
Angry 0.5%
Confused 0.3%

AWS Rekognition

Age 37-45
Gender Male, 94.3%
Happy 84.4%
Calm 15%
Surprised 0.2%
Sad 0.2%
Angry 0.1%
Confused 0.1%
Disgusted 0.1%
Fear 0%

AWS Rekognition

Age 22-30
Gender Female, 86.9%
Fear 30.8%
Happy 26.7%
Surprised 18.9%
Calm 11.8%
Angry 5.9%
Disgusted 2%
Confused 2%
Sad 1.7%

AWS Rekognition

Age 27-37
Gender Male, 99.9%
Happy 96.4%
Calm 1.1%
Sad 0.9%
Angry 0.7%
Surprised 0.4%
Confused 0.3%
Disgusted 0.2%
Fear 0.1%

AWS Rekognition

Age 19-27
Gender Male, 99.9%
Calm 93.3%
Confused 4.9%
Surprised 0.7%
Angry 0.3%
Fear 0.3%
Happy 0.2%
Disgusted 0.2%
Sad 0.2%

AWS Rekognition

Age 26-36
Gender Female, 57.1%
Fear 54.5%
Calm 17.9%
Happy 15.7%
Surprised 4%
Sad 4%
Confused 1.6%
Disgusted 1.3%
Angry 0.9%

AWS Rekognition

Age 16-22
Gender Male, 77.5%
Calm 74.5%
Fear 23.7%
Surprised 0.6%
Happy 0.5%
Confused 0.3%
Sad 0.2%
Disgusted 0.2%
Angry 0.1%

AWS Rekognition

Age 31-41
Gender Male, 51.7%
Angry 31.1%
Happy 28.8%
Calm 14.6%
Fear 9.2%
Sad 7.6%
Confused 5.7%
Disgusted 1.5%
Surprised 1.5%

AWS Rekognition

Age 12-20
Gender Male, 99.8%
Calm 37.8%
Fear 27.4%
Angry 18.8%
Disgusted 5.5%
Surprised 3.1%
Sad 3%
Happy 2.8%
Confused 1.6%

AWS Rekognition

Age 14-22
Gender Female, 79.3%
Fear 40.6%
Calm 19.6%
Confused 17%
Sad 10.1%
Surprised 5.9%
Disgusted 3.9%
Happy 1.5%
Angry 1.4%

AWS Rekognition

Age 18-26
Gender Male, 99.3%
Angry 46.2%
Calm 44.1%
Sad 4%
Confused 3.6%
Disgusted 0.7%
Fear 0.6%
Surprised 0.5%
Happy 0.3%

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Unlikely
Headwear Unlikely
Blurred Very unlikely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very likely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Unlikely
Headwear Very unlikely
Blurred Very unlikely

Google Vision

Surprise Very unlikely
Anger Very unlikely
Sorrow Very unlikely
Joy Very unlikely
Headwear Very unlikely
Blurred Very likely

Feature analysis

Amazon

Person 99.3%
Wheel 85.9%

Text analysis

Amazon

CAMILLO
4
FILM
2
BA
&
3
7
CU BA
CU
SAFETY FILM
6
MR226
SAFETY
"CHÊ" & CAMILLO CIENFULEGOS
KODAK
CIENFULEGOS
"CHÊ"
LoM
LODAR
JUKNNIE
ERIFICI
PASSPORT 4
CHIENTE
PASSPORT

Google

"
CHẾ
KODAK
SAFETY
" CHẾ CAMlo CIENFUEGO SAFETY FILM KODAK SAFETY FILM
CAMlo
FILM
CIENFUEGO