Daniel S. Schiff
@dschiff.bsky.social
Assist. Professor @purduepolsci & Co-Director of Governance & Responsible AI Lab (GRAIL). Studying #AI policy and #AIEthics. Secretary for @IEEE 7010 standard.
Mathematics
19%
Computer science
13%
'Darkfakes,' 'Foefakes,' 'Fanfakes,' and 'Glowfakes': Morgan Wack, Christina Walker, Alena Birrer, Kaylyn Jackson Schiff, Daniel Schiff, and JP Messina systematically analyzed political deepfakes and developed a classification that categorizes them along key dimensions.
Scrutinizing the Many Faces of Political Deepfakes | TechPolicy.Press
Morgan Wack, Christina Walker, Alena Birrer, Kaylyn Jackson Schiff, Daniel Schiff, and JP Messina systematically analyzed political deepfakes.
www.techpolicy.press
We've been following deepfakes for the last 7 years. This article aims to shed additional light on the topic by:
1) creating a conceptual typology of deepfakes
2) coining new concepts like 'glowfakes' and 'fanfakes'
3) & analyzing deepfakes from the 2024 elections
@grailcenter.bsky.social
1) creating a conceptual typology of deepfakes
2) coining new concepts like 'glowfakes' and 'fanfakes'
3) & analyzing deepfakes from the 2024 elections
@grailcenter.bsky.social
Reposted by Daniel Schiff
Scrutinizing the Many Faces of Political Deepfakes | TechPolicy.Press
Morgan Wack, Christina Walker, Alena Birrer, Kaylyn Jackson Schiff, Daniel Schiff, and JP Messina systematically analyzed political deepfakes.
www.techpolicy.press
'Darkfakes,' 'Foefakes,' 'Fanfakes,' and 'Glowfakes': Morgan Wack, Christina Walker, Alena Birrer, Kaylyn Jackson Schiff, Daniel Schiff, and JP Messina systematically analyzed political deepfakes and developed a classification that categorizes them along key dimensions.
Reposted by Daniel Schiff
GRAIL
@grailcenter.bsky.social
· Aug 20
AI Policy Corner: U.S. Copyright Guidance on Works Created with AI | Montreal AI Ethics Institute
✍️ By Tejasvi Nallagundla. Tejasvi is an Undergraduate Student in Computer Science, Artificial Intelligence and Global Studies and an Undergraduate Affiliate at the Governance and Responsible AI Lab…
montrealethics.ai
Tejasvi Nallagundla (@GRAILatPurdue) explores new U.S. Copyright Office guidance in the AI Policy Corner. The update makes clear: only human creative input can earn copyright prompt-only AI output isn’t protected. #AIpolicy #ResponsibleAI #DigitalPolicy
🔗 montrealethics.ai/ai-policy-co...
🔗 montrealethics.ai/ai-policy-co...
Daniel S. Schiff
@dschiff.bsky.social
· Aug 4
7/7 I hope you've found this thread helpful. Follow me @dschiff.bsky.social for more research on AI governance and public opinion.
This paper is for anyone in #TechPolicy, #PoliticalScience, and #PublicEngagement.
Link: doi.org/10.1093/pol...
#AIpolicy #AgendaSetting
This paper is for anyone in #TechPolicy, #PoliticalScience, and #PublicEngagement.
Link: doi.org/10.1093/pol...
#AIpolicy #AgendaSetting
Daniel S. Schiff
@dschiff.bsky.social
· Aug 4
6/7 🤔 Implications: There's broad consensus that we need more public participation to guide AI. But results suggest these calls may be underrealized. Policymakers may engage in a form of confirmation bias, amplifying public discourse only when it aligns with economic priorities.
Daniel S. Schiff
@dschiff.bsky.social
· Aug 4
5/7 📈 Finding 2 (The Catch): This public influence ONLY holds for the innovation frame. When the public discusses AI's economic potential, policymakers listen. When the public discusses AI ethics or security, we see no statistically significant influence on policymakers.
Daniel S. Schiff
@dschiff.bsky.social
· Aug 4
4/7 📈 Finding 1: Public attention does predict policymaker attention.
The time-series analysis (ARIMA + VAR) shows that a one standard deviation increase in public tweets about AI is associated with a 22.4% increase in Congressional messaging on AI that same week.
The time-series analysis (ARIMA + VAR) shows that a one standard deviation increase in public tweets about AI is associated with a 22.4% increase in Congressional messaging on AI that same week.
Daniel S. Schiff
@dschiff.bsky.social
· Aug 4
3/7 🔧 Methods: My text-as-data approach involved analyzing a dataset of ~5 million tweets using the #AI hashtag and comparing them to all AI-related tweets from the 115th and 116th U.S. Congresses (2017–2019).
This research was conducted at @GRAILcenter.bsky.social and @purduepolsci.bsky.social.
This research was conducted at @GRAILcenter.bsky.social and @purduepolsci.bsky.social.
Daniel S. Schiff
@dschiff.bsky.social
· Aug 4
2/7 I focused on three dominant ways people frame AI:
📈 Innovation: AI as a driver of economic growth & productivity.
🙏 Ethics: AI's impact on fairness, rights, bias, and safety.
⚔️ Competition: AI in the context of the US-China race.
📈 Innovation: AI as a driver of economic growth & productivity.
🙏 Ethics: AI's impact on fairness, rights, bias, and safety.
⚔️ Competition: AI in the context of the US-China race.