Did The Every come true?
Partly. The Every (2021) has a P(n) of 54% on Nearfi's P(n) Board, our estimate of the chance its future arrives within 20 years. Of its 4 tracked predictions, 1 have arrived and 1 are arriving. Its central premise, 'Large numbers of ordinary people voluntarily use services that measure and score their bodies and habits, supplying the data to the firm that runs them', has arrived. The next prediction is estimated to arrive around 2030.
The Every is most accurate about people: large numbers voluntarily wear and use services that measure and score them, and employers already lean on automated management. It is least accurate about machinery and corporate structure. Reliable lie detection does not exist, and the retailer-plus-social-network merger that the plot rests on has not happened.
Read the review · 5.0/10 →
How this P(n) was calculated
P(n) is the chance that this work's future arrives within 20 years, by 2046. For each prediction we turn our estimate into a probability: arrived is 100%, diverged is 0%, and otherwise the low end of our 80% range counts as a 10% chance, the median year 50% and the high end 90%. Each prediction is weighted 1–5 by how pivotal it is to the story, and P(n) is the weighted average. P50 does the same by 2076. P(n), explained.
| Claim | Prediction · why this weight | Weight | Status · estimate | By 2046 | By 2076 |
|---|---|---|---|---|---|
| EVERY-1 | Large numbers of ordinary people voluntarily use services that measure and score their bodies and habits, supplying the data to the firm that runs them. Core premise: the Every's power rests on a public that adopts each new tracking and scoring product willingly. |
5 | ARRIVED arrived 2019 | 100% | 100% |
| EVERY-2 | A consumer app reliably detects whether a person is lying, and employers and others rely on it to expose people. Major: the truth-detecting app opens the plot and is used to expose the heroine's intent. |
4 | FAR 2100 (2060–2200) | 6% | 26% |
| EVERY-3 | Employers use continuous worker data to trigger promotions, warnings and dismissals through automated systems. Supporting: the company's data programme for promotion and firing is a real part of its workplace but not the plot. |
3 | ARRIVING 2030 (2027–2040) | 96% | 100% |
| EVERY-4 | The world's biggest online retailer and the biggest social and search platform merge into a single company. Supporting: the merger is the setting and Delaney's motive for revenge but not the story itself. |
3 | DIVERGED — | 0% | 0% |
| P(n) = P20 = Σ(weight × chance by 2046) ÷ Σ weight = 8.1 ÷ 15 = 54% | |||||
| P50 = 9.0 ÷ 15 = 60% | |||||
Already here today (arrived 1, arriving ½, weighted): 43%.
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EVERY-1
Large numbers of ordinary people voluntarily use services that measure and score their bodies and habits, supplying the data to the firm that runs them.
Weight 5/5 · Core premise: the Every's power rests on a public that adopts each new tracking and scoring product willingly.
By mid-2019 about one in five American adults regularly wore a smartwatch or fitness tracker, and the share has presumably grown since. The same research centre found that most Americans say they feel little control over what companies collect and think the risks outweigh the benefits, so the adoption is willing but uneasy. The novel's version is more total than anything real, since no single company scores friendships and meals, but the behaviour it relies on is documented. 12
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EVERY-2
A consumer app reliably detects whether a person is lying, and employers and others rely on it to expose people.
Weight 4/5 · Major: the truth-detecting app opens the plot and is used to expose the heroine's intent.
Experimental algorithms can beat human guessing at spotting false statements but are far from reliable, at about two correct calls in three in one 2024 study. Studies of polygraph accuracy have a longer history of dispute, and the EU has banned AI that infers emotions in workplaces, though whether this covers lie detection is unsettled. Real use is also the opposite of the novel's: few people choose to use such tools, and those who do accuse more. The range assumes reliable detection is possible at all, which is uncertain. 345
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EVERY-3
Employers use continuous worker data to trigger promotions, warnings and dismissals through automated systems.
Weight 3/5 · Supporting: the company's data programme for promotion and firing is a real part of its workplace but not the plot.
Warehouse and platform work already runs on productivity metrics, and a 2019 report based on a letter from an Amazon lawyer said a system generated warnings and terminations at one site. Amazon disputed that employees were fired by an automatic system. The EU is meanwhile requiring human oversight and review of such decisions for platform workers, with national laws due by 2 December 2026. Regulation slows the fully automatic version and does not stop the metric-driven one, which is why the status is ARRIVING. 678
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EVERY-4
The world's biggest online retailer and the biggest social and search platform merge into a single company.
Weight 3/5 · Supporting: the merger is the setting and Delaney's motive for revenge but not the story itself.
No such merger has happened, and regulators have shown themselves willing to stop even much smaller deals, such as Amazon's abandoned purchase of iRobot. US courts have not been quick to break companies up either: a judge ruled in November 2025 that Meta is not an illegal monopoly. The platforms have concentrated power by expanding into each other's markets, so the effect has arrived by another route. 910
- FOR About one-in-five Americans use a smart watch or fitness tracker. Pew Research Center, 2020-01-09. 21% of US adults regularly wear a smartwatch or fitness tracker, per a June 2019 survey of 4,272 adults.
- AGAINST Americans and Privacy: Concerned, Confused and Feeling Lack of Control Over Their Personal Information. Pew Research Center, 2019-11-15. 81% say the risks of company data collection outweigh the benefits and 81% say they have little or no control, so the adoption is reluctant.
- AGAINST Lie detection algorithms disrupt the social dynamics of accusation behavior (summary of the iScience study). ScienceDaily, 2024-06-27. An algorithm was about 66% accurate against 46% for humans, only about a third of judges asked for it, and a "false" prediction sharply raised accusations.
- CONTEXT Red Lines under EU AI Act: Unpacking the prohibition of emotion recognition in the workplace and education institutions. Future of Privacy Forum, 2025. Article 5(1)(f) bans AI that infers emotions in workplaces and schools, with medical and safety exceptions. It does not settle whether lie detection counts.
- CONTEXT The Polygraph and Lie Detection. National Research Council (National Academies Press), 2003. The 2003 report addresses the difficulty of measuring polygraph accuracy and surveys alternatives such as voice-stress analysis and brain measurement.
- FOR How Amazon automatically tracks and fires warehouse workers for 'productivity'. The Verge, 2019-04-25. Reports on a letter from an Amazon attorney describing automated warnings and terminations for low productivity at a Baltimore site.
- AGAINST Amazon denies report that it fires workers by robot. KUOW, 2019-04-26. Amazon says employees are not terminated through an automatic system, so what the system does remains disputed.
- CONTEXT Directive (EU) 2024/2831 on improving working conditions in platform work. EU-OSHA, 2024-12-20. Requires human oversight of automated decision systems, bars processing of workers' emotional or psychological state, and sets a transposition deadline of 2 December 2026.
- AGAINST Amazon Abandons $1.4bn iRobot Buy Amidst EU Opposition. Silicon UK, 2024-01-29. Amazon called off a $1.4bn deal after the European Commission raised competition concerns.
- CONTEXT Federal Judge Says Meta Is Not a Monopoly, Ending FTC's Long-Running Antitrust Case. Hogan Lovells, 2025-12-02. Law-firm analysis of the ruling, which also notes that the FTC's monopolisation case against Amazon is due for trial in early 2027.
Ledger updated 6 Nov 2026. All works on the P(n) Board · Method