你遇到的“AI”是人工智能吗？从“AI”泛用到概念滑坡

Core Viewpoint - The article discusses the dual nature of the current AI era, highlighting both the excitement and the potential pitfalls associated with the overuse and misapplication of the term "AI" in various contexts [1][2]. Group 1: AI Ubiquity and Misapplication - AI has become a ubiquitous term, often used inappropriately to label various technologies and systems, leading to a phenomenon known as "AI washing" [2][3]. - The misuse of the term "AI" is not unique to one region; it is a global trend where traditional software is rebranded as AI to attract investment and policy support [3][4]. Group 2: Naming Fallacy and Its Implications - The concept of "naming fallacy" suggests that simply labeling something as "intelligent" does not equate to a true understanding of its capabilities [4][5]. - The simplification of complex AI concepts into general terms like "intelligence" leads to a disconnect between public expectations and the actual technological capabilities [4][6]. Group 3: Historical Context and Lessons - Historical examples, such as the "expert systems" of the 1980s, illustrate the dangers of overhyping technology, which can result in a loss of public trust and innovation stagnation [8][9]. - The article warns that the current AI hype could lead to similar pitfalls, where the mislabeling of products as AI may undermine genuine advancements in the field [8][9]. Group 4: Resource Misallocation and Innovation Stifling - The rush to label technologies as AI can lead to a misallocation of resources, as seen in the focus on humanoid robots at the expense of other potentially more effective intelligent systems [9][10]. - This narrow focus on specific AI applications can limit the exploration of diverse technological possibilities, posing systemic risks at a national strategy level [9][10]. Group 5: Conceptual Limitations and Public Perception - The article highlights a paradox where the public's high expectations for AI are often based on misconceptions, leading to a narrow view of what AI can achieve [10][11]. - The media's emphasis on visually appealing AI technologies can create cognitive barriers, restricting broader understanding and exploration of AI's potential [11][12]. Group 6: Call for Clarity and Responsibility - The article emphasizes the need for clarity in language and definitions within the AI field to maintain semantic hygiene and ensure that AI technologies are accurately represented [12][13]. - It advocates for a balanced approach to AI, focusing on practical applications and realistic expectations rather than sensationalized narratives [12][13].