As AI recruiters increasingly appear in interviews at large factories, when the optimal route determined by algorithms becomes the driving command for delivery riders, and when "digital HR" begins to decide whether employees stay or leave... Algorithms, a term that was slightly unfamiliar a few years ago, have now become an existence that some workers find difficult to ignore. On one hand, it is a useful tool for liberating manpower and improving efficiency, and on the other hand, it is a cold and inhumane machine. With the increasing presence of algorithms in people's production and life, the contradictions they generate are also receiving more attention: how can algorithms in the workplace seek a balance between efficiency and equality? In the increasingly frequent interaction between humans and machines, how can workers and algorithms coexist harmoniously? At the recently concluded 2025 Summer Davos Forum, Associate Professor Sun Ping from the School of Journalism and Communication at the University of Chinese Academy of Social Sciences shared a recent incident on an interactive forum called "Algorithms in the Workplace": when she was discussing with friends about going to eat roast duck at night and opening a mobile app to choose a restaurant, several roast duck restaurants appeared directly on the homepage before she could search. This kind of experience is actually not new for young people today. When going out to take a taxi, the algorithm will plan the shortest distance and shortest travel path for people; When ordering takeout, the algorithm will prioritize the restaurants that have been frequently eaten recently; Opening the music software, personalized "daily playlists" generated by algorithms based on personal preferences appear in the most prominent position on the page... These common clips from daily life repeatedly prove a fact: algorithms are becoming important participants in people's lives in a seemingly gentle and friendly way. If algorithms in daily life can be called "saviors of choice difficulties" and "efficiency optimizers", algorithms in the workplace seem less popular. The HR (Human Resources Management) of a leading company said that using algorithms to screen resumes is no longer a new thing. Although algorithms directly improved her work efficiency, they also made her feel horrified: "This means that when I need to find my next job, it may also be algorithms that decide whether I can participate in the interview." From a global perspective, algorithms have even entered a more brutal process of layoffs. In 2022, a news story about Facebook firing 60 employees sparked widespread discussion. The usual personnel adjustment has become less common due to the way layoffs are carried out - the person in charge of this layoff is not humans, but algorithms. In addition to serving as HR and "layoff officers", algorithm "supervisors" have secretly recorded whether employees are slacking off at work. As early as 2015, Amazon developed an efficiency detection and evaluation system for its warehouse management, which can monitor the work status of employees in real time. If someone is found to have been picking up goods for too long or not taking breaks during their break time, the system will automatically label them as "inefficient" and give them corresponding warnings and penalties. The efficiency and bias of algorithms "can be considered as a" closed loop "after being screened by algorithms and recruited into companies, monitored by algorithms in the workplace, and then laid off by algorithms. ”Behind this' joke 'is people's lament and helplessness towards the gradual infiltration of algorithms into the workplace. Algorithmic labor has been the area of focus for Sun Ping's research for many years. She summarized the impact of algorithms in the workplace as the "three E's", namely "Efficiency," "Evaluation," and "Evolution. Specifically, the efficiency improvement brought by algorithms has unprecedentedly restructured people's work. The autonomous evolution of algorithms requires people to engage in more digital labor to provide data, and the evaluation system reconstructed by algorithms has begun to make people consider competing with algorithms. This means that algorithms are not just a technology, they have been effectively embedded in current human relationships, "said Sun Ping. This kind of embedding gives people a complex and contradictory feeling, and the algorithm "supervisor" is a typical case of it. On the one hand, algorithms score employees' performance based on quantifiable standards such as computer activity time and clock in time, which seems to be a more efficient evaluation and management tool. On the other hand, the constantly informed supervision and inhumane machine management have exacerbated the inequality in employment relations and undermined the existing corporate culture. More importantly, algorithms are difficult to operate completely according to the developer's intentions, and may generate unpredictable biases in order to maximize efficiency and revenue. Grab Group is a platform company headquartered in Singapore that provides ride hailing and food delivery services to nearly 200 million people in eight Southeast Asian countries. Grab Group's executive director, Lin Youxing, previously noted that without feeding relevant data to the algorithm, the algorithm will try to match ride hailing orders for student passengers as little as possible because it believes that students "have no money". This is a situation we are very unwilling to see, and we hope that all consumers can enjoy our services equally, "said Lin Youxing. How algorithms can coexist harmoniously with migrant workers has been addressed to a certain extent as the integration of algorithms with daily life becomes increasingly close, including issues such as big data murder and information cocoons. But the problems brought by the use of algorithms in the workplace seem to be more hidden - companies certainly have the power to hire, supervise, and dismiss employees, but they still need to take people-oriented as the fundamental principle to grasp the scale. Ethics is a high-frequency term for algorithmic governance. Workplace algorithmic ethics should focus on whether it infringes upon the personal dignity and individual rights of employees. Imagine that when a person turns on their computer to start their day's work, the supervision from algorithms also begins at the same time. Will this create the tension and anxiety of being constantly in a "digital prison" or "digital prisoner"? This experience is a personal injury for many people, and the accumulation of negative emotions it leads to will inevitably have an impact on their physical and mental health. From a technical perspective, countless experiences have proven that algorithmic black boxes can lead to output results that even developers cannot imagine. To avoid risks, companies that use algorithm assisted management need to be clear and transparent in at least two aspects: first, employees need to be informed and agree, and second, preventive evaluation of algorithm output results should be conducted, and reasonable explanations, judgments, and corrections should be made. In Lin Youxing's opinion, some of the algorithm's judgments are reasonable and pleasing to see. When algorithms distribute ride hailing orders, they tend to assign more orders to more reliable drivers. So, the important thing is that we must confirm the judgment of the algorithm, and after confirmation, we also need to explain it to customers and drivers. From a more macro perspective, the ability of algorithms to break through ethics in the workplace is essentially due to the imbalance of interests between some employers and employees. The key to achieving harmonious coexistence between algorithms and workers lies in creating a more equal labor management relationship and working environment. When companies can truly treat their employees equally and use harmonious coexistence as the "baton" for algorithm applications, algorithms will truly become efficient and fair "work assistants" and "management partners". (New Society)