Jevons Paradox
An economic principle proposed by British economist William Stanley Jevons in 1865, stating that improvements in technological efficiency lead to an overall increase in resource consumption. The efficiency gains make related activities more economically viable, thereby stimulating demand expansion at a greater scale than the efficiency savings offset.
Core Facts
Jevons' paradox was first proposed by British economist William Stanley Jevons in 1865 in his book 'The Coal Question.'
Improvements in steam engine efficiency not only failed to reduce coal consumption in Britain, but actually stimulated larger-scale industrial expansion by lowering operating costs.
AI programming tools often experience a decline in code quality after prolonged use due to context overload.
Timeline (last 90 days)
For AI of a fixed capability level, running costs have become extremely low, and total enterprise AI spending is still growing rapidly with no sign of decline, which is a classic manifestation of Jevons paradox.
In AI scenarios, inferring a decline in total cost from a decline in unit cost is logically invalid, and in resource economics there is no law that efficiency improvements necessarily lead to reduced total consumption.
Jevons paradox is classified in economics under the rebound effect, divided into direct rebound (more consumption for the same use) and indirect rebound (saved resources shifting to other uses), and in AI scenarios both occur simultaneously.
Jevons' Paradox states that when resource use efficiency improves and unit costs decline, total consumption actually increases, and is used to explain how token price reductions drive multiplicative growth in AI usage volume.
Jev's name is taken from the Jevons Paradox, hinting at the business logic that demand increases as costs approach zero
Jevons' Paradox refers to the phenomenon whereby improved efficiency lowers the per-unit cost, but the resulting lower barrier stimulates demand at a larger scale, potentially causing total consumption to rise rather than fall.
Jevons' paradox states that total consumption does not necessarily decline after efficiency improves, and therefore Jalapeño's improved energy efficiency will not mean OpenAI will no longer face compute shortages.
The name Jev comes from the Jevons Paradox in economics, and is pronounced 'gev'.
The Jevons paradox states that improvements in technological efficiency often do not reduce resource consumption; instead, as the cost of use falls and the scope of application expands, total consumption rises.
Jevons' Paradox was proposed by British economist William Stanley Jevons in 1865, observing that improvements in steam engine efficiency actually led to an increase in total coal consumption.
4 more timeline events
All Facts (18)
Jevons' paradox was first proposed by British economist William Stanley Jevons in 1865 in his book 'The Coal Question.'
90%VerifiedImprovements in steam engine efficiency not only failed to reduce coal consumption in Britain, but actually stimulated larger-scale industrial expansion by lowering operating costs.
85%VerifiedAI programming tools often experience a decline in code quality after prolonged use due to context overload.
80%VerifiedJevons' paradox was systematically elaborated by economist William Stanley Jevons in his 1865 work The Coal Question, and refers to the phenomenon whereby increased efficiency leads to greater total consumption.
70%VerifiedJevons' paradox holds that improvements in technological efficiency tend to lead to growth rather than contraction in total demand, and was first proposed by British economist William Stanley Jevons in 1865.
65%Unverified杰文斯悖论指出技术进步带来的效率提升往往会刺激更多需求而非减少就业
95%UnverifiedJevons' Paradox was proposed by British economist William Stanley Jevons in 1865, observing that improvements in steam engine efficiency actually led to an increase in total coal consumption.
60%UnverifiedThe Jevons Paradox refers to William Stanley Jevons's observation that improvements in steam engine efficiency not only failed to reduce coal consumption but actually led to a significant increase in total consumption by lowering the cost of use.
60%UnverifiedFor AI of a fixed capability level, running costs have become extremely low, and total enterprise AI spending is still growing rapidly with no sign of decline, which is a classic manifestation of Jevons paradox.
50%UnverifiedJevons paradox is classified in economics under the rebound effect, divided into direct rebound (more consumption for the same use) and indirect rebound (saved resources shifting to other uses), and in AI scenarios both occur simultaneously.
50%UnverifiedIn AI scenarios, inferring a decline in total cost from a decline in unit cost is logically invalid, and in resource economics there is no law that efficiency improvements necessarily lead to reduced total consumption.
50%UnverifiedJevons' Paradox states that when resource use efficiency improves and unit costs decline, total consumption actually increases, and is used to explain how token price reductions drive multiplicative growth in AI usage volume.
50%UnverifiedJev's name is taken from the Jevons Paradox, hinting at the business logic that demand increases as costs approach zero
50%UnverifiedJevons' Paradox refers to the phenomenon whereby improved efficiency lowers the per-unit cost, but the resulting lower barrier stimulates demand at a larger scale, potentially causing total consumption to rise rather than fall.
50%UnverifiedJevons' paradox states that total consumption does not necessarily decline after efficiency improves, and therefore Jalapeño's improved energy efficiency will not mean OpenAI will no longer face compute shortages.
50%UnverifiedThe name Jev comes from the Jevons Paradox in economics, and is pronounced 'gev'.
50%UnverifiedThe Jevons paradox states that improvements in technological efficiency often do not reduce resource consumption; instead, as the cost of use falls and the scope of application expands, total consumption rises.
50%UnverifiedJevons悖论指技术效率提升往往反而刺激需求总量增长，2023年ChatGPT引发的推理成本暴降并未减少GPU需求
50%