Harry Yan
@harryyan.bsky.social
Postdoc at Stanford Social Media Lab, Cyber Policy Center. Incoming AP @TAMUComm. PhD*2 in Informatics @IULuddy + Media Sciences @IUMediaSchool. @KnightFdn @OsoMe_IU Fellow. @ICR_IU Researcher. #PublicOpinion #Tech #GenAI #Bots #MediaEffects
💡 But there’s hope.
Two factors helped:
🧠 Actively Open-Minded Thinking (AOT):
A cognitive tendency to consider evidence that challenges one’s prior beliefs.
📚 GenAI knowledge:
Factual understanding of generative AI.
AOT especially helped restore trust in real images—not just spot synthetics(8/)
Two factors helped:
🧠 Actively Open-Minded Thinking (AOT):
A cognitive tendency to consider evidence that challenges one’s prior beliefs.
📚 GenAI knowledge:
Factual understanding of generative AI.
AOT especially helped restore trust in real images—not just spot synthetics(8/)
April 18, 2025 at 9:23 PM
💡 But there’s hope.
Two factors helped:
🧠 Actively Open-Minded Thinking (AOT):
A cognitive tendency to consider evidence that challenges one’s prior beliefs.
📚 GenAI knowledge:
Factual understanding of generative AI.
AOT especially helped restore trust in real images—not just spot synthetics(8/)
Two factors helped:
🧠 Actively Open-Minded Thinking (AOT):
A cognitive tendency to consider evidence that challenges one’s prior beliefs.
📚 GenAI knowledge:
Factual understanding of generative AI.
AOT especially helped restore trust in real images—not just spot synthetics(8/)
👥 Who’s most vulnerable?
Older adults: more likely to doubt authentic images
Women: showed a larger accuracy gap than men
Partisans: more likely to doubt real images that conflict with their beliefs
#GenAI is amplifying existing digital and partisan divides. (7/)
Older adults: more likely to doubt authentic images
Women: showed a larger accuracy gap than men
Partisans: more likely to doubt real images that conflict with their beliefs
#GenAI is amplifying existing digital and partisan divides. (7/)
April 18, 2025 at 9:21 PM
👥 Who’s most vulnerable?
Older adults: more likely to doubt authentic images
Women: showed a larger accuracy gap than men
Partisans: more likely to doubt real images that conflict with their beliefs
#GenAI is amplifying existing digital and partisan divides. (7/)
Older adults: more likely to doubt authentic images
Women: showed a larger accuracy gap than men
Partisans: more likely to doubt real images that conflict with their beliefs
#GenAI is amplifying existing digital and partisan divides. (7/)
📊 Key finding:
Participants over-attributed AI generation, labeling nearly 60% of all images as synthetic—even though only half were.
This "AI attribution bias" leads to:
✅ Higher accuracy detecting synthetic images
❌ Lower accuracy recognizing authentic images (5/)
Participants over-attributed AI generation, labeling nearly 60% of all images as synthetic—even though only half were.
This "AI attribution bias" leads to:
✅ Higher accuracy detecting synthetic images
❌ Lower accuracy recognizing authentic images (5/)
April 18, 2025 at 9:18 PM
📊 Key finding:
Participants over-attributed AI generation, labeling nearly 60% of all images as synthetic—even though only half were.
This "AI attribution bias" leads to:
✅ Higher accuracy detecting synthetic images
❌ Lower accuracy recognizing authentic images (5/)
Participants over-attributed AI generation, labeling nearly 60% of all images as synthetic—even though only half were.
This "AI attribution bias" leads to:
✅ Higher accuracy detecting synthetic images
❌ Lower accuracy recognizing authentic images (5/)
👁️ We ran a large pre-registered experiment with 1,800 U.S. adults.
Participants evaluated political images balanced by party lean (pro-Dem vs. pro-Rep) and image type (authentic vs. AI-generated)— using actual images that circulated online during the election. (4/)
Participants evaluated political images balanced by party lean (pro-Dem vs. pro-Rep) and image type (authentic vs. AI-generated)— using actual images that circulated online during the election. (4/)
April 18, 2025 at 9:16 PM
👁️ We ran a large pre-registered experiment with 1,800 U.S. adults.
Participants evaluated political images balanced by party lean (pro-Dem vs. pro-Rep) and image type (authentic vs. AI-generated)— using actual images that circulated online during the election. (4/)
Participants evaluated political images balanced by party lean (pro-Dem vs. pro-Rep) and image type (authentic vs. AI-generated)— using actual images that circulated online during the election. (4/)
“Detecting Synthetic, Doubting Authentic: AI Attribution Bias for Political Imagery”
📍 Full preprint: osf.io/preprints/os...
🧵 Here’s what we found about how #GenAI is reshaping trust in political visuals during elections: (1/)
📍 Full preprint: osf.io/preprints/os...
🧵 Here’s what we found about how #GenAI is reshaping trust in political visuals during elections: (1/)
April 18, 2025 at 9:11 PM
“Detecting Synthetic, Doubting Authentic: AI Attribution Bias for Political Imagery”
📍 Full preprint: osf.io/preprints/os...
🧵 Here’s what we found about how #GenAI is reshaping trust in political visuals during elections: (1/)
📍 Full preprint: osf.io/preprints/os...
🧵 Here’s what we found about how #GenAI is reshaping trust in political visuals during elections: (1/)
One downside of submitting articles to multiple divisions is ending up with a lot more reviews to handle... Looking forward to seeing everyone in Denver next year! #ICA
December 5, 2024 at 9:34 PM
One downside of submitting articles to multiple divisions is ending up with a lot more reviews to handle... Looking forward to seeing everyone in Denver next year! #ICA