significant positive impact
Multi-stakeholder Perspective on Responsible Artificial Intelligence and Acceptability in Education
Karran, A. J., Charland, P., Martineau, J-T., de Arana, A. Ortiz de Guinea Lopez, Lesage, AM., Senecal, S., Leger, P-M.
This study investigates the acceptability of different artificial intelligence (AI) applications in education from a multi-stakeholder perspective, including students, teachers, and parents. Acknowledging the transformative potential of AI in education, it addresses concerns related to data privacy, AI agency, transparency, explainability and the ethical deployment of AI. Through a vignette methodology, participants were presented with four scenarios where AI's agency, transparency, explainability, and privacy were manipulated. After each scenario, participants completed a survey that captured their perceptions of AI's global utility, individual usefulness, justice, confidence, risk, and intention to use each scenario's AI if available. The data collection comprising a final sample of 1198 multi-stakeholder participants was distributed through a partner institution and social media campaigns and focused on individual responses to four AI use cases. A mediation analysis of the data indicated that acceptance and trust in AI varies significantly across stakeholder groups. We found that the key mediators between high and low levels of AI's agency, transparency, and explainability, as well as the intention to use the different educational AI, included perceived global utility, justice, and confidence. The study highlights that the acceptance of AI in education is a nuanced and multifaceted issue that requires careful consideration of specific AI applications and their characteristics, in addition to the diverse stakeholders' perceptions.
Artificial Intelligence to Help Curb Poaching: Study
As the world celebrated Earth Day on Friday, a team led by an Indian-origin researcher has found a way to use artificial intelligence (AI) to protect the Earth's endangered animals and forests by outwitting poachers with technology. With support from the US National Science Foundation (NSF) and the US Army Research Office, researchers are using AI and game theory to solve poaching, illegal logging and other problems worldwide, in collaboration with researchers and conservationists in the US, Singapore, the Netherlands and Malaysia. "This research is a step in demonstrating that AI can have a really significant positive impact on society and allow us to assist humanity in solving some of the major challenges we face," said Milind Tambe, professor of computer science and industrial and systems engineering at the University of Southern California (USC). "In most parks, ranger patrols are poorly planned, reactive rather than pro-active and habitual," said Fei Fang, PhD candidate from the University of Southern California (USC). Fang is part of an NSF-funded team at USC led by Tambe who is also director of the Teamcore Research Group on Agents and Multiagent Systems.
Artificial intelligence to Curb Poaching Soon
As the world celebrated Earth Day on Friday, a team led by an Indian-origin researcher has found a way to use artificial intelligence (AI) to protect the Earth's endangered animals and forests by outwitting poachers with technology. With support from the US National Science Foundation (NSF) and the US Army Research Office, researchers are using AI and game theory to solve poaching, illegal logging and other problems worldwide, in collaboration with researchers and conservationists in the US, Singapore, the Netherlands and Malaysia. "This research is a step in demonstrating that AI can have a really significant positive impact on society and allow us to assist humanity in solving some of the major challenges we face," said Milind Tambe, professor of computer science and industrial and systems engineering at the University of Southern California (USC). "In most parks, ranger patrols are poorly planned, reactive rather than pro-active and habitual," said Fei Fang, PhD candidate from the University of Southern California (USC). Fang is part of an NSF-funded team at USC led by Tambe who is also director of the Teamcore Research Group on Agents and Multiagent Systems.