One serious forecast says 2026 is when the jobless boom starts. Another says your job simply gets redesigned. They cannot both be right.
There are five serious scenarios for the future of work, each argued by people with conviction. This site logs the evidence as it lands, tags it to the scenario it feeds, and keeps score.
Vote first, then scroll down and see what the evidence says. One vote per person. Your answer is stored with the country it came from and nothing else, so you can see how the world disagrees with itself.
Not a forecast and not a prediction market. This is a weighted reading of the evidence currently on the table, recomputed every time a signal is added.
A radiologist, a junior copywriter, a payroll clerk and a plumber are living in four different scenarios right now. Pick the work closest to yours and see what the evidence says about your corner of it, including the evidence that cuts the other way.
Each entry states what the source actually claims, with the numbers, and which scenarios it pushes up or down. A statement from a CEO and a payroll dataset both belong here. They do not carry the same weight. The log is deliberately balanced between European and American evidence, because most of this debate is conducted on US data and read as though it were universal.
The whole point of a scoreboard is that you can check the arithmetic. Here is all of it.
Every signal is typed. Payroll and postings data counts fully. Peer-reviewed and institutional research counts nearly as much. A corporate announcement counts a little over half, because naming AI in a layoff release is a communications decision as much as an operational one. A statement from a founder or a CEO counts about a third.
Evidence decays on a twelve-month half-life. A 2024 model and an August 2026 payroll release should not carry equal weight in a debate that moves this fast, so older signals fade rather than being deleted. They stay in the log and keep some pull.
Most of this argument runs on American payroll data and gets read as though it described everywhere. Europe adopts AI at different speeds, hires young people through different doors, and protects jobs under different law. The log is kept deliberately balanced between European and US evidence, and you can filter the feed by either.
Social platforms are where most of this evidence surfaces first, so they are used as a lead, never as a citation. Anything found there is chased back to the report, filing or dataset behind it and logged against that. A post is only recorded as a social signal when the post itself is the primary source, and it carries the lowest weight of anything here.
A signal can support one scenario and undercut another, and many do. The WEF's net gain of 78 million jobs is quoted by optimists and by the people warning about 262 million transitions. Both readings are logged against the same source.
| Evidence type | Weight | Why |
|---|---|---|
| Hard data | 1.00 | Payroll records, official statistics, postings data. It measures what happened. |
| Research | 0.90 | Institutional and peer-reviewed studies. Strong, but usually modelled or lagged. |
| Corporate action | 0.60 | Real decisions with real consequences, and self-reported motives that flatter the teller. |
| Statement | 0.35 | Informed opinion from people with skin in the game. It moves the debate, not the data. |
| Social post | 0.25 | A claim made on X or similar, where the post is the primary source. Chased to a harder source wherever one exists. |
score = Σ ( direction × weight × typeMultiplier × 0.5^(monthsOld / 12) )
Every scenario then starts from a reserve of 3 points before any evidence is counted, because a position argued by serious, well-informed people is never worth zero. Scores below zero fall back to that reserve, and the five are normalised to sum to 100.
share = ( max(score, 0) + 3 ) / Σ ( max(score, 0) + 3 ) × 100
So a scenario sitting near 5% has not been disproven. It means the current evidence does not support it and its case rests on the reserve, which is exactly the position No jobs is in today.
Reserve 3 · half-life 12 months · 30 signals · recomputed in your browser
The dataset is a single file. Every number on this page is computed from it when the page loads, so nothing here is hand-tuned after the fact.
Technology will scale society. The question is whether we still build for the soul.
Three reasons I stay on the optimistic side of this. Young generations always find a way to create new value, and the ones growing up inside AI will find opportunities the rest of us cannot picture yet. People are not a sitting duck: they are already working out where they are still useful and where AI is coming for what they do. And underneath all of it there is a craving for connection that automation does not touch. People are buying vinyl again. People are buying old cameras again.
So we will scale. The harder question, and the one worth building a career around, is how we scale and still go deep: how we keep connection, depth in relationships, and the parts of work that only mean something because a human did them.
Every week: the new signals, what moved in the index, and what it means for the people doing the work. And if you spot something this log is missing, send it.
The week's signals and any movement in the index. No noise, no takes without receipts.
A study, a dataset, an announcement, a statement worth logging. It goes into the review queue, and if it holds up it gets added with your credit.