106 citations · 346 across the 9 of their papers we have counts for
10 papers
Blaming Humans and Machines: What Shapes People's Reactions to Algorithmic Harm
Gabriel Lima, Nina Grgić-Hlača, Meeyoung Cha
Artificial intelligence (AI) systems can cause harm to people. This research examines how individuals react to such harm through the lens of blame. Building upon research suggestin…
The Conflict Between Explainable and Accountable Decision-Making Algorithms
Gabriel Lima, Nina Grgić-Hlača, Jin Keun Jeong +1
Decision-making algorithms are being used in important decisions, such as who should be enrolled in health care programs and be hired. Even though these systems are currently deplo…
Misinformation, Believability, and Vaccine Acceptance Over 40 Countries: Takeaways From the Initial Phase of The COVID-19 Infodemic
Karandeep Singh, Gabriel Lima, Meeyoung Cha +4
The COVID-19 pandemic has been damaging to the lives of people all around the world. Accompanied by the pandemic is an infodemic, an abundant and uncontrolled spreading of potentia…
Human Perceptions on Moral Responsibility of AI: A Case Study in AI-Assisted Bail Decision-Making
Gabriel Lima, Nina Grgić-Hlača, Meeyoung Cha
How to attribute responsibility for autonomous artificial intelligence (AI) systems' actions has been widely debated across the humanities and social science disciplines. This work…
Descriptive AI Ethics: Collecting and Understanding the Public Opinion
Gabriel Lima, Meeyoung Cha
There is a growing need for data-driven research efforts on how the public perceives the ethical, moral, and legal issues of autonomous AI systems. The current debate on the respon…
Collecting the Public Perception of AI and Robot Rights
Gabriel Lima, Changyeon Kim, Seungho Ryu +2
Whether to give rights to artificial intelligence (AI) and robots has been a sensitive topic since the European Parliament proposed advanced robots could be granted "electronic per…