People

For years, cross-cultural psychologists have faced a longstanding puzzle: East Asian societies are often seen as more collectivistic, but some surveys have yielded higher collectivism scores for Western societies.A recent study, with Dr. Alexander S. English of Wenzhou-Kean University serving as a core collaborator, published in Nature Human Behavior, suggests that the issue may come from how collectivism is measured.The researchers found that many traditional surveys mix two different things: general warmth toward other people and responsibility within close relationships. Western participants often score higher on general warmth, which can push up their overall collectivism scores.To better explain this difference, the team introduced Responsibilism. Instead of only asking how collectivistic a person is, Responsibilism looks at the responsibilities people feel toward others in different relationships.These responsibilities can change depending on how close the relationship is. This idea is connected to Chinese sociologist Fei Xiaotong’s differential mode of association (chaxu geju).The researchers tested this idea in 45 languages, with 12,247 participants from 100 cultural regions. The results showed clear differences between Eastern and Western cultures. They also suggestedthat relationship-based responsibility may explain some cultural differences better than traditional collectivism measures.The team has also developed a 14-item Responsibilism Scale, which is now available to researchers around the world. Dr. English and his collaborators plan to keep studying how culture and interpersonal relationships shape human behavior.About Dr. Alexander S. EnglishDr. English received his Ph.D. in applied psychology from Zhejiang University. His research focuses on cross-cultural adaptation and intercultural communication.He has published more than 60 peer-reviewed papers in international SSCI journals and has received awards from the International Association for Cross-Cultural Psychology (IACCP) and the Asian Association of Social Psychology (AASP).Besides, he has received support from the National Natural Science Foundation of China under the Foreign Excellent Young Scientists Fund for a project running from 2026 to 2027.Sept 22, translated by Zhengnan Zhang

Open any shopping app and "Recommended for You" seems to know exactly what you want; scroll through a video platform and the algorithm appears to have already read your interests. As recommendation systems grow increasingly attuned to us, how can we ensure they protect our privacy — and resist malicious manipulation?Recently, Dr. Waqar Ali, Associate Professor in the College of Science, Mathematics and Technology at Wenzhou-Kean University (WKU), was awarded funding under the Research Fund for International Young Scientists (RFIS-I) of the National Natural Science Foundation of China (NSFC) for his project, "Responsible Recommendation Services with Attack-Resilient Federated Learning."Focused on the security and governance of artificial intelligence, the project aims to build a line of defense for recommendation systems, making personalized recommendations safer, fairer, and more trustworthy.Waqar Ali教授曾主持四川省科技计划项目，研究基于联邦学习的隐私保护推荐算法。此次国家自然科学基金项目则进一步聚焦攻击与防御，推动研究从“保护用户数据”走向“保障整个推荐系统安全”。多年来，Waqar Ali教授的研究成果发表于 ACM Computing Surveys、IEEE Transactions on Knowledge and Data Engineering、ACM Transactions on Recommender Systems、Information Sciences、IEEE Internet of Things Journal 等国际学术期刊，并拥有3项专利。Understanding you — and protecting youTo learn what users like, recommendation systems typically analyze data such as browsing history, clicks, and purchases. How can we put this data to use while safeguarding personal privacy? Federated learning offers one answer.It allows user data to remain on local devices such as phones and computers. Each device trains the model locally, and the results are aggregated to jointly improve the recommendation system. In short: "data never leaves the device, yet AI can still be trained together."But Dr. Ali has drawn attention to an easily overlooked issue: the fact that data is not shared directly does not mean the resulting model is inherently secure.If a "malicious participant" sneaks into the training process, it can still submit manipulated information that quietly skews the AI's judgment.This is like a group of people jointly "teaching" an AI which products are worth recommending. Most participants provide normal information — but if someone continuously feeds in carefully crafted false content, certain products could gain abnormal exposure, or the entire recommendation system could be undermined."When people use online shopping, entertainment, or travel platforms, they expect high-quality recommendations that genuinely match their needs — not misleading or manipulated results," said Dr. Ali.The impact of this risk goes far beyond "recommending the wrong product." As recommendation technology moves into finance, healthcare, education, and e-commerce, a compromised or severely biased system could interfere with decisions that matter.The project therefore seeks to answer a key question: when multiple participants jointly train a recommendation model, how can we detect malicious behavior in a timely manner and prevent it from affecting the final outcome?Mapping attack types to lay the groundwork for defenseTo counter different kinds of attacks, the first step is understanding how the "adversary" might act.The project plans to systematically review the definitions, characteristics, implementation methods, and potential impacts of various attacks on federated recommendation systems, building a knowledge base for attack identification and defense. This will serve as a reference for researchers to spot potential threats, detect malicious behavior, and develop defense strategies.Building on this, the team will study mechanisms for detecting malicious clients — analyzing data distributions, model updates, and training behavior across clients to identify anomalies and flag participants who may be manipulating the system.The project will also explore more secure federated learning frameworks to strengthen the stability of recommendation systems in complex adversarial environments. In parallel, the team will examine new attack vectors enabled by generative AI, as well as the impact of attacks on recommendation fairness.Popular content, for instance, tends to be recommended more because it attracts more attention. If attackers exploit this mechanism to manipulate outcomes, content that is already less visible could lose even more exposure. The implications extend beyond whether recommendations are accurate, to whether the system can serve different users and content providers fairly.From mapping attack types and identifying malicious participants, to designing defense mechanisms and reducing algorithmic bias, the project forms a fairly complete research pathway — ultimately advancing safer, fairer, and more responsible recommendation services.From privacy protection to trustworthy AIThe project continues a research direction Dr. Ali has pursued for years.About a decade ago, an academic discussion on optimizing search engine performance sparked his interest in recommendation systems. His research has since evolved from context-aware recommendation to privacy protection, federated learning, and responsible recommender systems.He previously led a project under the Sichuan Provincial Science and Technology Program on privacy-preserving recommendation algorithms based on federated learning. The new RFIS-I project sharpens the focus on attacks and defense, moving the research from "protecting user data" to "safeguarding the entire recommendation system."Over the years, Dr. Ali's findings have been published in international journals including ACM Computing Surveys, IEEE Transactions on Knowledge and Data Engineering, ACM Transactions on Recommender Systems, Information Sciences, and IEEE Internet of Things Journal, and he holds three patents."This means a great deal to me," he said of the grant approval. For him, it is both recognition of his research and a new responsibility. He hopes to build on it to help translate AI research into technology that is trustworthy, socially meaningful, and practically impactful.Once the project is underway, WKU students will have the opportunity to participate in the research and engage with cutting-edge AI questions in practice. Dr. Ali also plans to strengthen research collaboration with Kean University in the United States and expand his network of partners with universities and research institutions at home and abroad.As AI grows ever better at understanding us, how can we grow more confident in trusting AI? This inquiry into trustworthy artificial intelligence will continue to find new answers at Wenzhou-Kean University.

In the age dominated by fingertip entertainment, how would you explain the value of boredom? At the grand final of the 30th “21st Century Cup” National English Speaking Competition, Wu Yichen, a senior Finance major at WKU, delivered a compelling answer. With a sharp take on a contemporary issue and fluent expression, he stood out among 200,000 competitors nationwide to win the national first prize.Three Hours Without a Phone Leads to One Key Insight“This topic felt extremely real,” Wu recalled. “Almost everyone today is inseparable from their phones.”In the finals, contestants drew topics on site and were given just 30 minutes to prepare a two-minute impromptu speech, without access to any external information.A personal experience proved crucial. As an afternoon-session contestant, Wu spent three to four hours waiting with all electronic devices confiscated. “That period of complete disconnection felt boring at first,” he said, “but it gave me a genuine understanding of what boredom means in the age of constant digital stimulation.”Drawing on prior research, Wu cited data from the China Internet Audiovisual Development Research Report, noting that people spend an average of 2.6 hours a day watching short videos. Combining data with personal experience, he argued that boredom is not meaningless, but a necessary space for deeper thinking—an idea that resonated with judges and audience alike.The grand final of the "21st Century" CupCritical Thinking Matters More Than Perfect English“21st Century Cup” is one of China’s most influential English-speaking contests since its launch in 1996. Wu was no stranger to the competition. Two years ago, he won second prize at the provincial level but failed to advance to the national stage. This year, he made the breakthrough and reached the top stage.“Fluency and correct grammar are just the basics,” Wu said. “What really matters is how you interpret the topic and whether your ideas are thoughtful and original.” In his view, language is ultimately a tool for communication. Clear thinking and meaningful content outweigh accent or stylistic perfection.Beyond competition, the event also became a space for learning and friendship. Contestants shared rooms, exchanged drafts, practiced together and offered feedback. “It felt less like a rivalry and more like growing together,” Wu said.Attending the national English competitionsGrowth Beyond the CompetitionWu’s success reflects years of preparation beyond the contest itself. WKU’s all-English environment laid a strong foundation, while training with the university’s English competition team helped sharpen his speaking skills.He also serves as an English guide at WKU’s Museum, receiving visiting delegations from both China and abroad. One memorable experience involved hosting a delegation from Kean University in the United States, where he had to adapt on the spot to schedule changes and compressed timeframes. “Those moments taught me that deep preparation is what allows you to stay calm and flexible under pressure,” he said.Receiving delegations at the WKU MuseumNow an academically outstanding student, Wu has received offers from several leading universities, including Duke University. As the graduation approaches, he is planning his next steps in graduate study.“The competition strengthened my language skills and critical thinking,” he said. “More importantly, it connected me with people who share the same passion. These experiences will stay with me for a long time.”Translator: Wenwei Xiang, Yihui Cai