The Prague Post - AI's blind spot: tools fail to detect their own fakes

EUR -
AED 4.294721
AFN 76.01227
ALL 96.967353
AMD 445.749312
ANG 2.093746
AOA 1072.364952
ARS 1712.860023
AUD 1.743797
AWG 2.082458
AZN 1.985389
BAM 1.962197
BBD 2.353292
BDT 142.775442
BGN 1.949078
BHD 0.44081
BIF 3458.13602
BMD 1.169427
BND 1.503071
BOB 8.091308
BRL 6.279585
BSD 1.168519
BTN 105.230698
BWP 15.677577
BYN 3.421282
BYR 22920.774763
BZD 2.349881
CAD 1.622504
CDF 2642.905475
CHF 0.930501
CLF 0.026744
CLP 1049.140261
CNY 8.159504
CNH 8.149803
COP 4343.135989
CRC 581.013955
CUC 1.169427
CUP 30.989823
CVE 110.624686
CZK 24.282689
DJF 208.070079
DKK 7.472839
DOP 74.395069
DZD 151.957694
EGP 55.102943
ERN 17.541409
ETB 181.667773
FJD 2.668166
FKP 0.872356
GBP 0.868802
GEL 3.151629
GGP 0.872356
GHS 12.525726
GIP 0.872356
GMD 86.537239
GNF 10227.823305
GTQ 8.959091
GYD 244.414692
HKD 9.117966
HNL 30.814033
HRK 7.538714
HTG 153.036089
HUF 386.170035
IDR 19694.324887
ILS 3.694741
IMP 0.872356
INR 105.477488
IQD 1530.683419
IRR 49262.124516
ISK 147.219119
JEP 0.872356
JMD 185.042726
JOD 0.82913
JPY 184.47832
KES 150.797365
KGS 102.258815
KHR 4692.518108
KMF 495.837212
KPW 1052.48516
KRW 1716.509011
KWD 0.359692
KYD 0.973682
KZT 596.880911
LAK 25257.554549
LBP 104631.890296
LKR 361.220653
LRD 209.731024
LSL 19.337705
LTL 3.453014
LVL 0.707375
LYD 6.337715
MAD 10.790183
MDL 19.804647
MGA 5417.82403
MKD 61.588042
MMK 2455.810692
MNT 4161.065013
MOP 9.382145
MRU 46.939051
MUR 54.577248
MVR 18.079527
MWK 2026.091601
MXN 20.948417
MYR 4.750797
MZN 74.724764
NAD 19.337705
NGN 1665.229517
NIO 43.002208
NOK 11.764825
NPR 168.378827
NZD 2.031324
OMR 0.449644
PAB 1.168399
PEN 3.92961
PGK 4.985487
PHP 69.302612
PKR 327.071133
PLN 4.208839
PYG 7732.273005
QAR 4.259449
RON 5.092158
RSD 117.367208
RUB 92.319574
RWF 1703.024603
SAR 4.38559
SBD 9.507696
SCR 17.416544
SDG 703.408654
SEK 10.723754
SGD 1.503445
SHP 0.877373
SLE 28.212395
SLL 24522.309714
SOS 666.607314
SRD 44.661593
STD 24204.783711
STN 24.58129
SVC 10.223415
SYP 12933.36863
SZL 19.33227
THB 36.520007
TJS 10.877721
TMT 4.092995
TND 3.420622
TOP 2.815701
TRY 50.437983
TTD 7.930922
TWD 36.98349
TZS 2923.141326
UAH 50.398104
UGX 4206.67762
USD 1.169427
UYU 45.487705
UZS 14148.061595
VES 380.043589
VND 30717.931178
VUV 140.67703
WST 3.255662
XAF 658.130617
XAG 0.013886
XAU 0.000255
XCD 3.160436
XCG 2.105783
XDR 0.818493
XOF 658.108032
XPF 119.331742
YER 278.850097
ZAR 19.191647
ZMK 10526.250031
ZMW 22.637992
ZWL 376.555108
  • RBGPF

    0.0000

    81.57

    0%

  • SCS

    0.0200

    16.14

    +0.12%

  • RYCEF

    0.3300

    17.45

    +1.89%

  • CMSC

    0.2800

    23.27

    +1.2%

  • NGG

    1.8600

    80.12

    +2.32%

  • CMSD

    0.0400

    23.69

    +0.17%

  • BCE

    0.0200

    23.74

    +0.08%

  • BCC

    7.4500

    83.05

    +8.97%

  • RIO

    -2.0800

    81.13

    -2.56%

  • RELX

    1.0300

    43.14

    +2.39%

  • GSK

    1.3700

    50.39

    +2.72%

  • VOD

    -0.3200

    13.5

    -2.37%

  • BTI

    -0.3100

    55.19

    -0.56%

  • JRI

    0.0600

    13.8

    +0.43%

  • AZN

    0.6400

    94.65

    +0.68%

  • BP

    -1.8300

    34.29

    -5.34%

AI's blind spot: tools fail to detect their own fakes
AI's blind spot: tools fail to detect their own fakes / Photo: Chris Delmas - AFP

AI's blind spot: tools fail to detect their own fakes

When outraged Filipinos turned to an AI-powered chatbot to verify a viral photograph of a lawmaker embroiled in a corruption scandal, the tool failed to detect it was fabricated -- even though it had generated the image itself.

Text size:

Internet users are increasingly turning to chatbots to verify images in real time, but the tools often fail, raising questions about their visual debunking capabilities at a time when major tech platforms are scaling back human fact-checking.

In many cases, the tools wrongly identify images as real even when they are generated using the same generative models, further muddying an online information landscape awash with AI-generated fakes.

Among them is a fabricated image circulating on social media of Elizaldy Co, a former Philippine lawmaker charged by prosecutors in a multibillion-dollar flood-control corruption scam that sparked massive protests in the disaster-prone country.

The image of Co, whose whereabouts has been unknown since the official probe began, appeared to show him in Portugal.

When online sleuths tracking him asked Google's new AI mode whether the image was real, it incorrectly said it was authentic.

AFP's fact-checkers tracked down its creator and determined that the image was generated using Google AI.

"These models are trained primarily on language patterns and lack the specialized visual understanding needed to accurately identify AI-generated or manipulated imagery," Alon Yamin, chief executive of AI content detection platform Copyleaks, told AFP.

"With AI chatbots, even when an image originates from a similar generative model, the chatbot often provides inconsistent or overly generalized assessments, making them unreliable for tasks like fact-checking or verifying authenticity."

Google did not respond to AFP’s request for comment.

- 'Distinguishable from reality' -

AFP found similar examples of AI tools failing to verify their own creations.

During last month's deadly protests over lucrative benefits for senior officials in Pakistan-administered Kashmir, social media users shared a fabricated image purportedly showing men marching with flags and torches.

An AFP analysis found it was created using Google's Gemini AI model.

But Gemini and Microsoft's Copilot falsely identified it as a genuine image of the protest.

"This inability to correctly identify AI images stems from the fact that they (AI models) are programmed only to mimic well," Rossine Fallorina, from the nonprofit Sigla Research Center, told AFP.

"In a sense, they can only generate things to resemble. They cannot ascertain whether the resemblance is actually distinguishable from reality."

Earlier this year, Columbia University's Tow Center for Digital Journalism tested the ability of seven AI chatbots -- including ChatGPT, Perplexity, Grok, and Gemini -- to verify 10 images from photojournalists of news events.

All seven models failed to correctly identify the provenance of the photos, the study said.

- 'Shocked' -

AFP tracked down the source of Co's photo that garnered over a million views across social media -- a middle-aged web developer in the Philippines, who said he created it "for fun" using Nano Banana, Gemini's AI image generator.

"Sadly, a lot of people believed it," he told AFP, requesting anonymity to avoid a backlash.

"I edited my post -- and added 'AI generated' to stop the spread -- because I was shocked at how many shares it got."

Such cases show how AI-generated photos flooding social platforms can look virtually identical to real imagery.

The trend has fueled concerns as surveys show online users are increasingly shifting from traditional search engines to AI tools for information gathering and verifying information.

The shift comes as Meta announced earlier this year it was ending its third-party fact-checking program in the United States, turning over the task of debunking falsehoods to ordinary users under a model known as "Community Notes."

Human fact-checking has long been a flashpoint in hyperpolarized societies, where conservative advocates accuse professional fact-checkers of liberal bias, a charge they reject.

AFP currently works in 26 languages with Meta's fact-checking program, including in Asia, Latin America, and the European Union.

Researchers say AI models can be useful to professional fact-checkers, helping to quickly geolocate images and spot visual clues to establish authenticity. But they caution that they cannot replace the work of trained human fact-checkers.

"We can't rely on AI tools to combat AI in the long run," Fallorina said.

burs-ac/sla/sms

G.Kucera--TPP