Essay: Understanding the Slippery Slope Fallacy
The slippery slope fallacy is an informal fallacy. In terms of formal logic, it belongs to the hypothetical syllogism, using a series of causal inferences but exaggerating the causal strength at each step, turning “possibility” into “inevitability,” and thus reaching an unreasonable conclusion. In reality, things do not always unfold in a linear fashion as the inference suggests; there are other possibilities1.
The typical form of the slippery slope fallacy is:
- If \(A_1\) happens, then \(A_2\) will happen, then \(A_3\) will happen, then \(A_4\) will happen, and so on until \(A_n\).
- Usually, it is then explicitly or implicitly concluded: since \(A_n\) should not happen, we should not allow \(A_1\).
The causal relationships from \(A_1\) to \(A_2\), \(A_2\) to \(A_3\), etc., are like a series of “slopes.” The process of inferring from \(A_1\) to \(A_n\) is like sliding down a slope.
The problem with the slippery slope fallacy is that the causal strength of each “slope” varies. Some causal links are merely possible, not inevitable; some are very weak; some are even unknown or lack evidence. If there is sufficient evidence showing that each “slope” has a reasonable and strong causal connection, then it is not a slippery slope fallacy.
For example, in the Douyin (TikTok China) comment section, various people’s reactions to my comments can be analyzed in the typical form of the slippery slope fallacy:
- \(A_1\): I post a comment in the Douyin comment section, pointing out a bias in the video: although Huawei’s AI chips have made progress, they have not fully surpassed NVIDIA.
- \(A_2\): Some groups interpret this comment as me being biased against domestic products.
- \(A_3\): These groups then infer that I do not support Huawei or even China’s technological progress.
- \(A_4\): They further infer that this bias means I support foreign products or foreign viewpoints.
- \(A_n\): Ultimately, these people label you as a “public intellectual,” “traitor,” or “slanderer of national industry,” seeing me as someone who opposes the interests of the country and the nation.
In this example, at each stage from \(A_1\) to \(A_n\), the causal relationship weakens and is full of assumptions and misinterpretations. These assumptions lack evidential support and are often based on emotional reactions rather than factual analysis.
- The causal link from \(A_1\) to \(A_2\) assumes that all criticism is negative, ignoring the possibility of constructive criticism.
- The links from \(A_2\) to \(A_3\) and from \(A_3\) to \(A_4\) are based on assumptions about your personal stance, rather than the content of your comment.
- Reaching \(A_n\), that is, completely viewing you as anti-national, is a huge logical leap with no actual evidence to support this final negative label.
The challenge of the slippery slope fallacy is that it often hides within seemingly reasonable logical coherence, making it difficult to immediately identify or refute. Here are a few examples worth discussing in depth:
- If we continue to develop and rely on artificial intelligence to perform daily tasks, human decision-making abilities will soon deteriorate. Over time, humans will become completely dependent on machines for every choice in life, ultimately leading to a loss of autonomy.
- If inflammatory speech on the internet is not restricted, it may gradually erode social values, eventually resulting in the complete collapse of social morality.
The slippery slope fallacy is subtle and challenging; it silently leads us to make excessive or erroneous inferences. Even when expressing professional opinions, I may inadvertently adopt the “if…then…” reasoning pattern, which often ignores the multiple possibilities and complexities of how events unfold. I have always believed that it is crucial to continuously reflect on and critique my own way of thinking. Therefore, I am recording the above content to remind myself that by understanding the slippery slope fallacy, I can more clearly identify and avoid this cognitive pitfall.