Search Results for author:
Found 10 papers, 1 papers with code
Blaming Humans and Machines: What Shapes People's Reactions to Algorithmic Harm
Building upon research suggesting that people blame AI systems, we investigated how several factors influence people's reactive attitudes towards machines, designers, and users.
The Conflict Between Explainable and Accountable Decision-Making Algorithms
Furthermore, we argue that XAI could result in incorrect attributions of responsibility to vulnerable stakeholders, such as those who are subjected to algorithmic decisions (i. e., patients), due to a misguided perception that they have control over explainable algorithms.
Human Perceptions on Moral Responsibility of AI: A Case Study in AI-Assisted Bail Decision-Making
How to attribute responsibility for autonomous artificial intelligence (AI) systems' actions has been widely debated across the humanities and social science disciplines.
Descriptive AI Ethics: Collecting and Understanding the Public Opinion
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.
Collecting the Public Perception of AI and Robot Rights
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 personalities."
COVID-19 Vaccine Acceptance in the US and UK in the Early Phase of the Pandemic: AI-Generated Vaccines Hesitancy for Minors, and the Role of Governments
This study presents survey results of the public's willingness to get vaccinated against COVID-19 during an early phase of the pandemic and examines factors that could influence vaccine acceptance based on a between-subjects design.
Dimensions of Diversity in Human Perceptions of Algorithmic Fairness
A growing number of oversight boards and regulatory bodies seek to monitor and govern algorithms that make decisions about people's lives.
Responsible AI and Its Stakeholders
Responsible Artificial Intelligence (AI) proposes a framework that holds all stakeholders involved in the development of AI to be responsible for their systems.
The Conflict Between People's Urge to Punish AI and Legal Systems
Regulating artificial intelligence (AI) has become necessary in light of its deployment in high-risk scenarios.
Rhetorical Move Detection in English Abstracts: Multi-label Sentence Classifiers and their Annotated Corpora
Here, we present MAZEA (Multi-label Argumentative Zoning for English Abstracts), a multi-label classifier which automatically identifies rhetorical moves in abstracts but allows for a given sentence to be assigned as many labels as appropriate.
