The China Mail - Online images reinforce gender stereotypes more than text: study

USD -
AED 3.672504
AFN 65.503991
ALL 80.193613
AMD 365.443623
ANG 1.789783
AOA 918.000367
ARS 1475.150612
AUD 1.415829
AWG 1.80125
AZN 1.70397
BAM 1.690479
BBD 2.011669
BDT 122.606854
BGN 1.696366
BHD 0.37668
BIF 2985.954449
BMD 1
BND 1.277583
BOB 11.640953
BRL 5.222404
BSD 0.998833
BTN 95.261679
BWP 13.45607
BYN 3.037988
BYR 19600
BZD 2.008816
CAD 1.38765
CDF 2273.000362
CHF 0.813662
CLF 0.023213
CLP 913.600415
CNY 6.743204
CNH 6.74452
COP 3115.519253
CRC 449.371191
CUC 1
CUP 26.5
CVE 95.306625
CZK 20.930304
DJF 177.864212
DKK 6.460604
DOP 58.464065
DZD 131.663425
EGP 49.854358
ERN 15
ETB 161.573793
EUR 0.864504
FJD 2.234204
FKP 0.739036
GBP 0.73929
GEL 2.610391
GGP 0.739036
GHS 10.937378
GIP 0.739036
GMD 73.503851
GNF 8773.931458
GTQ 7.6209
GYD 208.928649
HKD 7.84715
HNL 26.775574
HRK 6.512304
HTG 130.645231
HUF 313.830388
IDR 17828.1
ILS 2.955104
IMP 0.739036
INR 95.450504
IQD 1308.440296
IRR 1374587.503816
ISK 122.903814
JEP 0.739036
JMD 158.174511
JOD 0.70904
JPY 159.30404
KES 129.09806
KGS 87.450384
KHR 4041.661265
KMF 427.00035
KPW 900.000294
KRW 1416.470383
KWD 0.30868
KYD 0.832361
KZT 463.468603
LAK 22542.892951
LBP 89443.536886
LKR 332.365271
LRD 181.287005
LSL 16.158607
LTL 2.95274
LVL 0.60489
LYD 6.359825
MAD 9.264013
MDL 17.319677
MGA 4300.099399
MKD 53.178616
MMK 2099.791609
MNT 3596.010349
MOP 8.073123
MRU 40.112364
MUR 47.103741
MVR 15.450378
MWK 1731.967674
MXN 17.023504
MYR 4.085904
MZN 63.910377
NAD 16.158607
NGN 1359.570377
NIO 36.760448
NOK 9.442604
NPR 152.41886
NZD 1.677149
OMR 0.381252
PAB 0.998833
PEN 3.368858
PGK 4.486797
PHP 61.465038
PKR 277.41994
PLN 3.72275
PYG 5995.073253
QAR 3.641125
RON 4.526704
RSD 101.421842
RUB 83.996716
RWF 1468.77566
SAR 3.752773
SBD 8.048583
SCR 13.755996
SDG 600.503676
SEK 9.527038
SGD 1.279604
SHP 0.740866
SLE 24.503667
SLL 20969.499227
SOS 570.811185
SRD 37.974504
STD 20697.981008
STN 21.176369
SVC 8.739358
SYP 13001.999906
SZL 16.156273
THB 33.143038
TJS 9.223994
TMT 3.51
TND 2.928476
TOP 2.40776
TRY 47.867504
TTD 6.76693
TWD 32.021604
TZS 2646.873244
UAH 44.681879
UGX 3710.618436
UYU 40.019016
UZS 11890.747223
VES 770.109104
VND 26148.5
VUV 117.940389
WST 2.73449
XAF 566.970915
XAG 0.015456
XAU 0.000229
XCD 2.70255
XCG 1.800078
XDR 0.707052
XOF 566.970915
XPF 103.081378
YER 237.203589
ZAR 16.16923
ZMK 9001.203584
ZMW 18.87722
ZWL 321.999592
  • CMSC

    -0.0250

    21.45

    -0.12%

  • CMSD

    -0.0100

    21.58

    -0.05%

  • BCC

    -0.8900

    83.24

    -1.07%

  • RBGPF

    0.0000

    71.34

    0%

  • BCE

    0.1500

    23.47

    +0.64%

  • GSK

    -0.4785

    49.52

    -0.97%

  • NGG

    -0.1500

    81.05

    -0.19%

  • RIO

    -0.4100

    95.68

    -0.43%

  • AZN

    -0.7900

    156.45

    -0.5%

  • JRI

    0.0635

    12.61

    +0.5%

  • RELX

    -0.2400

    34.43

    -0.7%

  • VOD

    0.2000

    16.42

    +1.22%

  • BTI

    -0.2900

    57.06

    -0.51%

  • RYCEF

    0.1300

    20.84

    +0.62%

  • BP

    0.2196

    42.53

    +0.52%

Online images reinforce gender stereotypes more than text: study
Online images reinforce gender stereotypes more than text: study / Photo: © AFP/File

Online images reinforce gender stereotypes more than text: study

Images on the internet reinforce gender stereotypes -- such as doctors being men or nurses women -- more than text, contributing to a lasting bias against women, a US-based study said Wednesday.

Text size:

The importance of images has soared as much of the world's media, communication and even social interactions have moved online.

But this rising dominance of the image "exacerbates gender bias" by significantly under-representing women, according to the study in the journal Nature.

Lead author Douglas Guilbeault, a researcher at the business school of the University of California, Berkeley, told AFP that this was an "alarming" trend.

He warned of "the potential consequences this can have on reinforcing stereotypes that are harmful, mostly to women, but also to men."

Study co-author Solene Delecourt, also from UC Berkeley, said an example would be if a child was trying to find out more about a profession online but only saw images of one gender.

"They may feel like they don't belong," she said.

Images are also "often more memorable and emotionally evocative than text," the study said.

- 'Really concerning' -

For the study, the researchers sifted through more than one million images from Google, Wikipedia and the IMDb film database, as well as billions of words on those platforms.

They looked for potential bias in nearly 3,000 social categories, including jobs such as doctor or lawyer, or roles such as neighbour or colleague.

Both over-represented men, but the images displayed even more gender bias than the words, the researchers found.

For example, the stereotype that women are nurses was "consistently stronger" in the images than the text, Guilbeault said.

This bias was not limited to the United States -- the researchers used many images from websites around the world -- nor was it confined to a particular platform.

The gender bias is also larger than what the general public broadly think, according to an opinion poll carried out by the researchers.

The team also used US census data to show that the under-representation of women for these jobs seen in online images does not match reality.

Finally, they looked into what psychological impact this bias has on people using the internet.

They had 450 people search online for specific jobs -- such as astronaut, poet or neurobiologist -- some reading text while others looked at images.

Afterwards, the participants carried out a test designed to measure their bias.

The group that looked up images had a more pronounced gender bias -- and the effect was still present during another test three days later, the researchers said.

"Images influence people in ways that they may not consciously realise," Guilbeault said.

He also lamented that there has been so little attention paid to "this shift towards image-based communication".

The researchers pointed to the role of online platforms in amplifying gender bias through their images, calling for more to be done.

They also warned that new image generators driven by artificial intelligence algorithms draw heavily on existing online images.

"It's not a surprise that the images these algorithms generate reflect all kinds of biases," Guilbeault said.

U.Feng--ThChM