首页|New Findings from Carl von Ossietzky University Oldenburg in the Area of Androids Reported (Gender Stereotyping of Robotic Systems In Eldercare: an Exploratory Analysis of Ethical Problems and Possible Solutions)

New Findings from Carl von Ossietzky University Oldenburg in the Area of Androids Reported (Gender Stereotyping of Robotic Systems In Eldercare: an Exploratory Analysis of Ethical Problems and Possible Solutions)

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New research on Robotics - Androids is the subject of a report. According to news reporting out of Oldenburg, Germany, by NewsRx editors, research stated, “Socio psychological studies show that gender stereotypes play an important role in human-robot interaction. However, they may have various morally problematic implications and consequences that need ethical consideration, especially in a sensitive field like eldercare.” Financial support for this research came from Projekt DEAL. Our news journalists obtained a quote from the research from Carl von Ossietzky University Oldenburg, “Against this backdrop, we conduct an exploratory ethical analysis of moral issues of gender stereotyping in robotics for eldercare. The leading question is what moral problems and conflicts can arise from gender stereotypes in care robots for older people and how we should deal with them. We first provide an overview on the state of empirical research regarding gender stereotyping in human-robot interaction and the special field of care robotics for older people. Starting from a principlist approach, we then map possible moral problems and conflicts with regard to common ethical principles of autonomy, care, and justice. We subsequently consider possible solutions for the development and implementation of morally acceptable robots for eldercare, focusing on three different strategies: explanation, neutralization, and queering of care robots.”

OldenburgGermanyEuropeAndroidsEmerging TechnologiesHuman-Robot InteractionMachine LearningNano-robotRobotRoboticsRobotsCarl von Ossietzky University Oldenburg

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Feb.19)
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