In this information age, algorithms are everywhere and touch almost every corner of our working life. We seem to be surrounded by algorithms, and many people worry that the operation of society will be "algorithms king" and humans will become "cloud slaves". In fact, despite the wide influence of algorithms, they are not everything. Algorithms are essentially a tool, and they exist in human intelligence and decision-making systems. In terms of technical attributes, the algorithm itself cannot be king; From a socio-ethical point of view, humans will not allow algorithms to be king.
Algorithms can tailor information and services for us based on data, such as analyzing behavioral data such as users' historical searches, and content that users may be interested in; **The learning platform provides customized lessons and review materials by analyzing students' learning progress, test scores, and learning styles; Through integrated image recognition algorithms, the monitoring system analyzes the stream in real time, detects abnormal behavior, and even automatically identifies and tracks specific individuals; The algorithm of the smart grid optimizes the efficiency of power generation and the rational allocation of resources by optimizing energy demand; Algorithms for autonomous vehicles and drones process massive amounts of data from countless sensors, learn and adapt to changing road and flight conditions, provide safe and efficient driving decisions, and more.
Algorithms have technical limitations, and their "decision-making" is based on pattern recognition and probability calculations, rather than autonomous awareness, and there is still a lot to be strengthened. First, the performance of an algorithm is highly dependent on the quality and quantity of data, and if the data is biased or insufficient, the output of the algorithm may not be accurate. Many powerful algorithms, such as deep learning models and large language models, are still "black box" systems, and their decision-making processes lack transparency and explainability. In areas that require the explainability of decisions, such as medical diagnoses, judicial decisions, etc., if we cannot understand the decision-making process of algorithms, then it is difficult to fully trust their decision-making results. Second, algorithms are often trained on specific datasets with the expectation that they will generalize to new scene data. However, the generalization ability of the algorithm is limited, especially when the data distribution changes significantly, and the algorithm may not be able to adapt to the new data distribution, resulting in a sharp decline in performance. Further, the real world is dynamic, so algorithms need to constantly adapt to this change, which requires the algorithm to have some form of learning ability or be updated regularly. However, dynamic adaptation itself is a very big technical challenge. In addition, the algorithm exists in the form of coding, and it can be subject to various attacks, including data poisoning, adversarial attacks, etc. These attacks can mislead the algorithm, resulting in erroneous outputs. While there is research dedicated to enhancing the robustness of algorithms, so far, there is no foolproof solution.
From the perspective of human sociology, human society cannot allow algorithms to be king, and will be constrained by corresponding laws and regulations. First of all, autonomy is a core principle of modern ethics and an important embodiment of human dignity, individuals should have the right to choose their own decisions, if algorithms are king, it will destroy the basic ethical structure of human society. For example, when an algorithm collects and uses user data, if the algorithm is left to its own claims, this will involve the basic issue of the autonomy of personal privacy information. Second, algorithms introduce bias and injustice, and since algorithms are often trained on pre-existing data, if that data contains biases, algorithms will inherit or even amplify those biases. This not only affects the fairness of decision-making, but can also lead to social inequality and discrimination. For example, if a large language model used in recruitment services has a much higher success rate of male candidates than women in its training data, the output of the model may be more skewed towards male candidates, leading to gender discrimination in the workplace. In addition, algorithms will bring about an "information cocoon", limiting the type of information people are exposed to, affecting individuals' worldview and decision-making, which is not conducive to the innovation and progress of human society. In addition, the opacity of algorithm design may affect the public, such as shaping or manipulating public opinion, affecting the guidance and control of the public, and even affecting major events related to the country's political economy such as elections and transactions. Finally, algorithms are incapable of possessing human moral judgment and empathy, and may not be able to make decisions that best align with human values when dealing with situations that contain ethical dilemmas and emotional disputes.
In this era of dancing with algorithms, we are not only the beneficiaries of technological progress and enjoy the many conveniences brought by algorithms, but we must also be highly vigilant about the risks that may be caused by algorithms, and seek a dynamic balance in this symbiotic relationship. With the development of society and technology, we have the opportunity to build an algorithm ecosystem that is both safe and explainable, and in line with human social ethics.