Slippery Slope
Also known as: domino fallacy
Claiming that a first step will inevitably trigger a chain of events ending in disaster, without showing each link is likely.
Examples
A team proposes a modest scheduling change.
Maya: “Could we try optional remote work on Fridays?” Owen: “If we allow that, next it’ll be remote Mondays too, then people stop coming in at all, and the office culture just dies.”
Owen jumps from one flexible day to the total collapse of office culture without showing why any of the middle steps would actually happen.
At home, the same shape appears in smaller stakes.
Kid: “Can I play one game before homework?” Guardian: “One game becomes an hour, an hour becomes the whole evening, and you’ll never do homework again.”
Maybe that has happened before — but stated this way, it’s an assumption, not a demonstrated pattern.
Online, a modest proposal gets the same treatment.
Comment: “Could we add one more off-topic channel for movie chat?” Reply: “Add one and soon it’s five off-topic channels, nobody talks about the game anymore, the mods give up, and the whole server dies within a month.”
Nothing in the reply shows why one channel would multiply into five, let alone why that would end the server — the chain is asserted, not argued.
Why the reasoning fails
A slippery slope argument claims that a small first step makes a chain of increasingly extreme consequences inevitable, without showing that each link in the chain actually follows from the one before it. The reasoning fails at the connective tissue: it asserts the chain rather than arguing it, skipping past the question of what mechanism would actually push things from step one to step five.
This isn’t the same as a genuine causal chain. If someone lays out why each step leads to the next — citing precedent, incentives, or a documented pattern — and shows the chain is likely rather than merely possible, that’s a legitimate argument about consequences, even if it reaches an alarming conclusion. The fallacy is in skipping that work, not in discussing consequences at all.
How to respond
- Ask for the missing links: “Why would remote Fridays lead to nobody coming in? What’s the mechanism?”
- Separate the proposal from the extreme case: “Can we evaluate remote Fridays on their own, rather than assuming where it ends?”
- Suggest a checkpoint: “What if we try it for a month and review, instead of assuming the worst outcome now?”
- Take it seriously if there’s evidence — if similar policies really have escalated elsewhere in a documented way, that’s worth discussing on its merits, not dismissed as “just” a slippery slope.