DeepSeek's Efficiency Sparks Jevons Paradox Debate in AI Industry

Jevons Paradox Does Not Support a Bullish Thesis for AI Tech Stocks | Investing.com UK

Many technology sector analysts believe that the stock market price declines within the tech sector (and the overall market), that occurred in the aftermath of DeepSeek's recent product releases represented an "over-reaction". The most common argument made in favor of this "bullish" narrative is that computing efficiencies (in software and hardware) and associated cost reductions made possible by DeepSeek innovations will increase the demand for AI applications, and therefore increase the demand for the same set of AI inputs (e.g. computer chips, data centers, and cloud computing software) produced by the same companies. Those pursuing this line of argumentation claim that an economic concept called the "Jevons Paradox" supports their bullish thesis. The Jevons Paradox refers to a microeconomic phenomenon whereby efficiency-enhancing technological innovations that lower the number of resource inputs required to produce a unit of output, "paradoxically" leading to an increase in the total demand for that resource that rises above and beyond the level that existed prior to the introduction of the efficiency-enhancing innovations. According to this line of argument promoted by bullish pundits, the more economical use of AI inputs enabled by DeepSeek will actually increase demand for those same inputs. In this article, I am going to analyze whether this bullish conjecture is supported by the Jevons Paradox when analyzed in its proper historical context. My thesis is that Jevon Paradox and associated historical experience do not support a bullish thesis for AI-oriented US tech stocks and that it actually suggests very bearish implications. In 1865, William Stanley Jevons published The Coal Question: An Inquiry Concerning the Progress of the Nation and the Probable Exhaustion of Our Coal Mines. Jevons, who was one of the most important economists of the 19th century, wrote this book because he was deeply concerned about the potential depletion of Britain's coal reserves and the impact that this would have on the nation's economic and geopolitical future. At the time, many in Britain were optimistic regarding the long-term sustainability of the nation's coal supplies, largely because of technological advancements -- such as the Watt steam engine -- that had significantly reduced the amount of coal that was needed to produce a given amount of economic output. In Chapter VII, titled Of the Economy of Fuel, Jevons warned against complacency regarding technological improvements that reduced coal consumption per unit of economic output. He famously stated: "It is wholly a confusion of ideas to suppose that the economical use of fuel is equivalent to a diminished consumption. The very contrary is the truth." Jevons explained what has become known as the Jevons Paradox. Jevons argued that technological innovations that enabled less coal to be consumed per unit of output would increase the gross consumption of coal. Jevons explained that this somewhat counter-intuitive outcome will tend to occur because, "The reduction of the consumption of coal, per unit of work, will enable us to do more work for the same amount of coal. This is the key to the paradox that the more economical the use of coal becomes, the more its consumption increases." Jevons summarized the phenomenon thusly: "Whatever, therefore, conduces to greater efficiency in fuel consumption will accelerate rather than retard the exhaustion of coal mines." Several examples of the operation of the "efficiency paradox," have been offered in support of the existence of the Jevons Paradox. While the Jevons Paradox presents an intriguing argument, and statistics such as those cited above are quite alluring, it is not at all clear whether and to what extent the Jevons Paradox is actually a real microeconomic phenomenon. It is certainly not a universally applicable law of microeconomics, nor it is a hypothesis that can be scientifically verified. Notwithstanding these empirical and conceptual shortcomings, since it was created, the Jevons Paradox has been repeatedly employed as a foil to argue that technological developments that enable lesser quantities of inputs to be used in the production of a given unit of output, may actually lead to an increase in the total consumption of that input. Historically, the Jevons Paradox has been most frequently employed in discussions about fuel consumption. For example, in recent times, some climate change activists have argued that measures aimed at improving fuel efficiency will not cause a decline in the consumption of fossil fuels nor help to reduce carbon-dioxide emissions, due to Jevons Paradox. More recently, in the aftermath of recently announced efficiencies in computational resource usage and associated declines in the market values of several high-tech companies in the US -- e.g. NVIDIA (NASDAQ:NVDA), Microsoft (NASDAQ:MSFT), Google (GOOG) (NASDAQ:GOOGL) - several financial markets commentators have sought to employ the Jevons Paradox to argue that market participants were "over-reacting.". They argue that despite the revolutionary computational efficiencies enabled by innovations introduced by DeepSeek, the consumption of inputs used in the production of AI applications will actually increase. In other words, even though AI applications using the DeepSeek LLM are expected to utilize 90%+ less computational resources (software and hardware), it is argued based on the Jevons Paradox that the consumption of computational resources (e.g. computer chips, data centers and cloud software) will increase. In my next article, I am going to perform an in-depth analysis of whether the application of the Jevons Paradox to arguments about the profitability and valuations of certain US tech companies is even logically coherent. However, for the remainder of this article, I will only focus on the validity of the implicit historical analogy between coal as an energy input and the sorts of inputs that are utilized in the development of AI applications - e.g. computer chips, data centers and cloud computing software. The key question is: Do computer chips, data centers, and cloud computing services play a similar role in the value creation chain for AI applications that coal did for locomotives and steam ships in the 19th century? If not, then the analogy breaks down and the Jevons Paradox must be considered to be of questionable relevance in the debate regarding the demand for products and services provided by companies in the US tech sector. Superficial-minded tech analysts recently enamored with the Jevons Paradox, tend to misleadingly speak about the inputs consumed in the production of AI applications as if they were a singular resource and an undifferentiated commodity that can be analogously compared to coal that was used as a fuel in the 19th century. For example, in discussing the Jevons Paradox they carelessly use terms such as "GPUs" and "compute" as if they were a singular and undifferentiated commodity. This is a fundamental error. The inputs that generate AI (e.g. computer chips, data centers, and cloud computing software) are multiple and highly differentiated. Furthermore, simple-minded tech analysts have failed to recognize the fact that the technological innovations introduced by DeepSeek are not merely enabling efficiencies in the use of a singular resource or a set of resources - it is enabling total and/or partial substitution of one set of inputs (and configurations of inputs) for another new set of inputs (and configurations). This isa critical distinction, because the historical technological innovations in engines (e.g. from Watt to Newcomen steam engines) merely enabled more efficient consumption of coal; they did not prompt the substitution of coal for another source of fuel. The significance of this erroneous historical analogy being made by tech industry commentators can be illustrated with a historical hypothetical counterfactual example. Imagine that in 1865, technological innovations had caused a shift from coal-powered engines to more energy-efficient diesel-powered engines. Now imagine a stock market analyst at that time claiming that because of the fuel efficiencies made possible by diesel engines, the demand for coal was going to increase and coal mining companies were going to increase their profits. This would be absurd! The companies that produced coal in the 19th century were (and still are) fundamentally different from the ones that produced and refined petroleum products. The switch from coal to diesel would have helped the new producers of crude oil and refined petroleum products and would have devasted the producers of coal. This serves to illustrate the intellectual poverty of the argument that stock market analysts are presently making when they say that the profits and valuations of incumbent producers of inputs -- e.g. NVIDIA, Microsoft, Google and Oracle (NYSE:ORCL) -- used in the production of AI applications (e.g. computer chips, data centers, and cloud software) will benefit from the efficiencies enabled by DeepSeek. The innovations enabled by DeepSeek will change the types and mix of inputs used in the development of AI applications. As will be discussed in my next article, the producers of the computer chips, data centers, and cloud software of today will be different from the producers of the key inputs in the post-DeepSeek world of AI applications development. As such the profits and valuations of many tech companies will be devasted. Indeed, history has shown, time and time again, that major technological innovations rarely help the profitability or market valuations of incumbent firms. The forces of "creative destruction," famously described by Joseph Schumpeter, tend to destroy the competitive position of incumbent firms and lead to the emergence of new leaders. Furthermore, history has shown that the "first movers" in a technological transition are rarely the ones that ultimately emerge as winners. For example, the first manufacturers of automobiles were not ultimately the winners in the automotive industry and the first manufacturers of airplanes were not ultimately the winners in the aviation industry. In this article, I have demonstrated that the bullish narrative for US tech stocks that is based on the Jevons Paradox is premised on a false historical analogy. When this historical analogy subjected to careful scrutiny, it completely breaks down. In fact, the historical analogy between coal producers of the 19th century and today's tech companies that produce AI inputs suggests quite the opposite conclusion: Innovations enabled by DeepSeek (and soon others) will be extremely bearish for the profitability of many incumbent US AI tech companies. Nobody should get the impression that I am bearish on AI, nor "pessimistic" about future economic developments just because the Jevons Paradox cannot be used to support conjectures about the profitability or valuations of US AI tech companies. To the contrary, I believe that the sorts of innovations introduced by DeepSeek (which will be exponentially enhanced by many others) will be extremely bullish for consumers and the economy as a whole. The decimation of the business models of many incumbent tech companies that I have described in this essay are simply classic examples of Schumpeterian "creative destruction". I fully expect that the overall impacts of AI innovations on the economy will be very positive, but the effects on many specific companies will be bearish. We are extremely bullish on the transformational power of AI in the global economy. Indeed, we are highly focused on investing in companies - most of which are not in the tech sector - that we believe will greatly benefit from the AI revolution. Furthermore, we believe that developments in AI at the microeconomic level will soon have massive impacts on a macroeconomic level, and our portfolios will be positioned for the associated macroeconomic and geopolitical shifts.

Europe's AI bulls pin hopes on 'Jevons Paradox' after DeepSeek rout

LONDON (Reuters) - Artificial intelligence bulls in Europe are dusting off a 160-year-old economic theory to explain why the boom in the sector's stocks may have further to run, despite the emergence of China's cheap AI model DeepSeek. Tech stocks worldwide plunged on Jan. 27 after the launch of DeepSeek - apparently costing a fraction of rival AI models and requiring less sophisticated chips - raised questions over the West's huge investments in chipmakers and data centres. At the heart of the selloff was U.S. advanced chipmaker and AI poster-child Nvidia, which lost 17% of its value, or close to $600 billion, in the largest one-day drop in market capitalisation for any company on record. Since then, tech stocks have rebounded, with European markets hitting new highs, and a 19th century economic theory is suddenly on everyone's lips: the Jevons Paradox. Named after English economist William Stanley Jevons, it posits that when a resource becomes more efficient to use, demand can increase - rather than decrease - as the price to use the resource drops. "I hadn't discussed it until Monday (last week), and then suddenly it's everywhere," said Helen Jewell, Chief Investment Officer at BlackRock Fundamental Equities, EMEA. "This paradox highlights one of the uncertainties at the moment," said Jewell, flagging that a key question for European stock-pickers is whether data centres and their suppliers will be less in demand. "One of the big question marks from (last) Monday's news is how much energy is going to be needed for the AI revolution?" The selloff hit direct and indirect AI plays alike. Dutch semiconductor equipment maker ASML, and sector peers ASMI and BE Semi all fell 7%-12% on Jan. 27, before recouping losses later in the week, as did Siemens Energy, which provides hardware for AI infrastructure. "Jevons Paradox strikes again!" Microsoft chief executive Satya Nadella said in a post on X. "As AI gets more efficient and accessible, we will see its use skyrocket, turning it into a commodity we just can't get enough of." THE NEW BUZZWORD On Friday, Tomasz Godziek, portfolio manager of the Tech Disruptors fund at J. Safra Sarasin Sustainable Asset Management, said lower AI costs could exemplify the Jevons Paradox. "Ultimately, this could fuel a new wave of AI investment, creating fresh opportunities, particularly in software and inference technologies," Godziek said. Portfolio managers at Thematics Asset Management, an affiliate of Natixis IM, cited Jevons Paradox as one reason they believe demand for AI chips may remain healthy. Mark Hawtin, head of the Liontrust global equities team, also said his investment thesis on AI was reinforced by the news on Jan. 27, flagging the paradox. "Everyone has become an expert on Jevons Paradox," said Aviva Investors portfolio manager Kunal Kothari, who manages a UK equity income fund with around 2 billion pounds ($2.5 billion) in assets. "The falling cost of improved productivity through GenAI will likely benefit companies in the UK market generally, as they will predominantly be consumers of these technologies," he added, pointing to data and software names like RELX, LSEG, Experian and Sage as likely beneficiaries. DATA CENTRE NEEDS IN FOCUS The need for data centres and the vast amounts of power required to run them has driven a lot of AI investing in Europe already, given that there aren't any homegrown rivals to the likes of Nvidia, whose shares have rocketed by about 200% in under two years. "There is an implicit assumption that the adoption and usage of AI would require increasingly more chips, and more data centre capacity and power consumption," said Kasper Elmgreen, CIO of fixed income and equities at Nordea Asset Management. "What DeepSeek has done is to question what is required from that route and what can be delivered by making much better software." Not everyone is convinced of the new rationale, including Jordan Rochester, head of FICC strategy at Mizuho EMEA. "Whilst many Nvidia optimists pointed to Jevons Paradox to help them sleep better at night ... it was less convincing in the short term after what has been a meteoric rise in Nvidia shares," he wrote in a note. (Reporting by Lucy Raitano. Editing by Amanda Cooper and Mark Potter)

DeepSeek and the Jevons Paradox: What It Means for AI Infra Spending, Efficiency | Investing.com UK

Nvidia's (NASDAQ:NVDA) market cap dropped, DeepSeek continues to disrupt, and European banks outperformed the Mag 7. Here are the last seven days in seven charts. On Monday, Nvidia experienced the largest single-day market cap drop in stock market history. In fact, it holds the top spot for the six biggest single-day losses ever recorded. However, the stock managed to recover part of these losses over the course of the week. Source: Deutsche Bank thru Ali Dhanji @DhanjiatRJ on X Following DeepSeek's industry-shaking debut, which erased nearly $600 billion from Nvidia's market cap in a single day, one phrase has become essential in the DeepSeek discourse: Jevons Paradox. Interest in the concept has surged, with traffic to its Wikipedia page skyrocketing this week. As that very page explains: "the Jevons paradox occurs when technological advancements make a resource more efficient to use (thereby reducing the amount needed for a single application), however, as the cost of using the resource drops, overall demand increases causing total resource consumption to rise." Can you believe it? While technology grabs many headlines, European banks have outperformed the Mag 7 over the past two years. Source: Goldman Sachs (NYSE:GS) Germany and France saw their GDP shrink by 0.2% and 0.1%, respectively, in Q4 2024, while Italy's GDP remained flat for the second straight quarter. As a result, the Euro-area economy failed to grow in the final quarter of 2024. It is worth noting that Germany has now contracted for two consecutive years in 2023 and 2024. The United Arab Emirates (UAE) tops the list, attracting 6,700 millionaires, followed by the United States with 3,800 and Singapore with 3,500. Canada welcomed 3,200, while Australia saw 2,500 arrivals. Italy drew in 2,200, Switzerland 1,500, and Greece 1,200. Portugal brought in 800, with Japan closing out the top ten at 400. Wealth migration underscores the UAE as a prime destination, with other nations vying for a share of the world's affluent movers. While the world debates artificial intelligence and races to plant a flag on Mars, vast parts of Africa still lack access to something as basic as electricity. Over 600 million people across the continent remain without power.