New Releases by Erik Brynjolfsson

Rapid advances in AI are reshaping how we govern ourselves. Inspired by The Federalist Papers, which promoted the idea of a nation designed by intent rather than by accident, The Digitalist Papers series delves into the critical intersection of AI and democracy. This volume brings together scholars and industry leaders to explore the opportunities and challenges AI presents, offering a range of strategies for a democratic future. Instead of a one-size-fits-all solution, it champions a pluralistic, interdisciplinary approach to navigating this transformative era. Authors include Greg Beato, Laura Bisesto, John Cochrane, Sarah Friar, Mona Hamdy, Reid Hoffman, Saffron Huang, Lawrence Lessig, James Manyika, Johnnie Moore, Jennifer Pahlka, Alex Pentland, Nathaniel Persily, Eric Schmidt, Divya Siddarth, Audrey Tang, Lily L. Tsai, Eugene Volokh, and E. Glen Weyl.

Remote work surged during the Covid pandemic but there is disagreement about the extent of the change. To address this question, we field a new, nationally-representative survey: the Remote Life Survey (RLS). We find that in October 2020, 31.6 percent of the continuously employed workforce always worked from home (WFH) and 21.9 percent sometimes or rarely WFH, totaling 53.5 percent. We compare our results with alternative measurement approaches, with a focus on government surveys and provide estimates on the impact of four factors: (a) differences among mail versus web-based survey respondents, (b) differences in the inclusion of self-employed workers, (c) the industry mix of the sample, and (d) the exclusion of people who were already remote pre-pandemic. We find that the last explanation (d) explains the bulk of the difference in estimates between the Current Population Survey (CPS) and other measures of remote work. Policymakers and researchers who turn to the BLS-CPS data series for an estimate of remote work prevalence in the American economy should note that it might be underestimating WFH levels by up to 25 percentage points. Under our preferred estimates, we find that about half of the U.S. workforce worked remotely at least one day each week as of December 2020.

Information flows, and thus information technology (IT) are central to the structure of firms and markets. Using data from the U.S. Census Bureau, we provide firm-level evidence that increases in IT intensity are associated with increases in firm size and concentration in both employment and sales. Results from instrumental variables and long-difference models suggest that the effect is likely causal. The effect of IT on size is more pronounced for sales than employment, which leads to a decline in the labor share, consistent with the "scale without mass" theory of digitization. Furthermore, we find that IT provides greater benefits to larger firms by increasing their capability to replicate their operations across establishments, markets, and industries. Our findings provide empirical evidence suggesting that the substantial rise in IT investment is one of the main driving forces for the increase in firm size, decline of labor share, the growth of superstar firms, and increased market concentration in recent years.

We use data from the Annual Survey of Manufactures to study the characteristics and geography of investments in robots across U.S. manufacturing establishments. We find that robotics adoption and robot intensity (the number of robots per employee) is much more strongly related to establishment size than age. We find that establishments that report having robotics have higher capital expenditures, including higher information technology (IT) capital expenditures. Also, establishments are more likely to have robotics if other establishments in the same Core-Based Statistical Area (CBSA) and industry also report having robotics. The distribution of robots is highly skewed across establishments'' locations. Some locations, which we call Robot Hubs, have far more robots than one would expect even after accounting for industry and manufacturing employment. We characterize these Robot Hubs along several industry, demographic, and institutional dimensions. The presence of robot integrators and higher levels of union membership are positively correlated with being a Robot Hub.

This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work is in the "public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.

This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work is in the "public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.

This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work is in the "public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.

General purpose technologies like information technology typically require complementary firm-specific investments to create value. These complementary investments produce a form of capital, which is typically intangible and which we call digital capital. We create an extended firm-level panel on IT labor investments (1990-2016) using data from LinkedIn. We then apply Hall''s Quantity Revelation Theorem to compute both prices and quantities of digital capital over recent decades. We find that 1) digital capital prices vary significantly over time, peaking around the dot-com boom in 2000, 2) significant digital capital quantities have accumulated since the 1990s, with digital capital accounting for at least 25% of firms'' assets by the end of our panel, 3) that digital capital has disproportionately accumulated in a small subset of “superstar” firms and its concentration is much greater than the concentration of other assets, and 4) that digital capital accumulation predicts firm-level productivity about three years in the future.

E-commerce sales have grown rapidly worldwide, massively increasing the availability of new products. We examine data from the largest digital platform in China and find that the number of book titles almost doubled, prices fell somewhat, and most new books are sold to consumers with unusual tastes. Demand for these niche products was significantly more inelastic than that of mass products. Embedding the estimates of demand elasticity into a two-segment CES framework, we find the welfare gain from increased variety was about 40 times the gain from lower prices and that rural consumers enjoyed the largest gains.

Digital technologies may make some tasks, jobs and firms more resilient to unanticipated shocks. We extract data from over 200 million U.S. job postings to construct an index for firms'' resilience to the Covid-19 pandemic by assessing the work-from-home (WFH) feasibility of their labor demand. Using a difference-in-differences framework, we find that public firms with high pre-pandemic WFH index values had significantly higher sales, net incomes, and stock returns than their peers during the pandemic. Our results indicate that firms with higher digital resilience, as measured through our pre-pandemic WFH index, performed significantly better in general, and in non-essential industries in particular, where WFH feasibility was necessary to continue operation. The ability to use digital technologies to work remotely also mattered more in non-high-tech industries than in high-tech ones. Lastly, we find evidence that firms with lower pre-pandemic WFH feasibility attempted to catch up to their more resilient competitors via greater software investment. This is consistent with a complementarity between digital technologies and WFH practices. Our study''s results are robust to a variety of empirical specifications and provide a first look at how WFH practices improved resilience to a major, unanticipated social and economic shock.

Facebook, il social network più popolare al mondo, non crea contenuti. Uber, la più grande compagnia di taxi del mondo, non possiede vetture. Alibaba, il più grande rivenditore online, non ha scorte in magazzino. E Airbnb, il più celebre intermediario di case, non ha alcuna proprietà immobiliare. Il successo di queste aziende non è legato alla vendita di un prodotto: piuttosto, sono piattaforme capaci di raggiungere moltissimi utenti in tutto il mondo. Per crescere hanno bisogno di raggiungere la moltitudine della folla, di allontanarsi dal proprio centro e conquistare la periferia. Come fanno? Si servono delle macchine, cioè dell’intelligenza artificiale, capace di crescere ed espandersi rapidamente, con un solo obiettivo: raccogliere dati. Il nuovo mondo che McAfee e Brynjolfsson descrivono è questo: mentre un computer impara a giocare a scacchi meglio di un uomo, start up come Facebook e Google distruggono giganti dell’industria mondiale come Nokia. Un’idea nata nel garage di una persona può esplodere e diventare un colosso globale come Apple o Amazon. McAfee e Brynjolfsson raccontano il cambiamento radicale che non solo l’economia, ma anche il nostro stile di vita stanno attraversando: un’intersezione tra macchine, piattaforme e moltitudine, che sta trasformando il modo in cui organizziamo il lavoro e abitiamo il mondo. E offrono un’analisi penetrante del nostro tempo che è anche uno strumento indispensabile per affrontarlo.

We report the results of a nationally-representative sample of the US population during the COVID-19 pandemic. The survey ran in two waves from April 1-5, 2020 and May 2-8, 2020. Of those employed pre-COVID-19, we find that about half are now working from home, including 35.2% who report they were commuting and recently switched to working from home. In addition, 10.1% report being laid-off or furloughed since the start of COVID-19. There is a strong negative relationship between the fraction in a state still commuting to work and the fraction working from home. We find that the share of people switching to remote work can be predicted by the incidence of COVID-19 and that younger people were more likely to switch to remote work. Furthermore, states with a higher share of employment in information work including management, professional and related occupations were more likely to shift toward working from home and had fewer people laid off or furloughed. We find no substantial change in results between the two waves, suggesting that most changes to remote work manifested by early April.

We study the effects of occupational licensing on consumer choices and market outcomes in a large online platform for residential home services. We exploit exogenous variation in the time at which licenses are displayed on the platform to identify the causal effects of licensing information on consumer choices. We find that the platform-verified licensing status of a professional is unimportant for consumer decisions relative to review ratings and prices. We confirm this result in an independent consumer survey. We also use variation in regulation stringency across states and occupations to measure the effects of licensing on aggregate market outcomes on the platform. Our results show that more stringent licensing regulations are associated with less competition and higher prices but not with any improvement in customer satisfaction as measured by review ratings or the propensity to use the platform again.

Big Data generated by crowds provides a myriad of opportunities for monitoring and modeling people''s intentions, preferences, and opinions. A crucial step in analyzing such “big data” is selecting the relevant part of the data that should be provided as input to the modeling process. In this paper, we offer a novel, structured, crowd-based method to address the data selection problem in a widely used and challenging context: selecting search trend data. We label the method “crowd-squared,” as it leverages crowds to identify the most relevant terms in search volume data that were generated by a larger crowd. We empirically test this method in two domains and find that our method yields predictions that are equivalent or superior to those obtained in previous studies (using alternative data selection methods) and to predictions obtained using various benchmark data selection methods. These results emphasize the importance of a structured data selection method in the prediction process, and demonstrate the utility of the crowd-squared approach for addressing this problem in the context of prediction using search trend data.

While it is now well established that IT intensive firms are more productive, a critical question remains: Does IT cause productivity or are productive firms simply willing to spend more on IT? We address this question by examining the productivity and performance effects of enterprise systems investments in a uniquely detailed and comprehensive data set of 623 large, public U.S firms. The data represent all U.S. customers of a large vendor during 1998-2005 and include the vendor''s three main enterprise system suites: Enterprise Resource Planning (ERP), Supply Chain Management (SCM), and Customer Relationship Management (CRM). A particular benefit of our data is that they distinguish the purchase of enterprise systems from their installation and use. Since enterprise systems often take years to implement, firm performance at the time of purchase often differs markedly from performance after the systems go live. Specifically, in our ERP data, we find that purchase events are uncorrelated with performance while go-live events are positively correlated. This indicates that the use of ERP systems actually causes performance gains rather than strong performance driving the purchase of ERP. In contrast, for SCM and CRM, we find that performance is correlated with both purchase and go-live events. Because SCM and CRM are installed after ERP, these results imply that firms that experience performance gains from ERP go on to purchase SCM and CRM. Our results are robust against several alternative explanations and specifications and suggest that a causal relationship between ERP and performance triggers additional IT adoption in firms that derive value from their initial investment. These results provide an explanation of simultaneity in IT value research that fits with rational economic decision-making: Firms that successfully implement IT, react by investing in more IT. Our work suggests replacing either-or views of causality with a positive feedback loop conceptualization in which successful IT investments initiate a virtuous cycle of investment and gain. Our work also reveals other important estimation issues that can help researchers identify relationships between IT and business value.

Companies that don''t use AI will soon be obsolete. From making faster, better decisions to automating rote work to enabling robots to respond to emotions, AI and machine learning are already reshaping business and society. What should you and your company be doing today to ensure that you''re poised for success and keeping up with your competitors in the age of AI? Artificial Intelligence: The Insights You Need from Harvard Business Review brings you today''s most essential thinking on AI and explains how to launch the right initiatives at your company to capitalize on the opportunity of the machine intelligence revolution. Business is changing. Will you adapt or be left behind? Get up to speed and deepen your understanding of the topics that are shaping your company''s future with the Insights You Need from Harvard Business Review series. Featuring HBR''s smartest thinking on fast-moving issues--blockchain, cybersecurity, AI, and more--each book provides the foundational introduction and practical case studies your organization needs to compete today and collects the best research, interviews, and analysis to get it ready for tomorrow. You can''t afford to ignore how these issues will transform the landscape of business and society. The Insights You Need series will help you grasp these critical ideas--and prepare you and your company for the future.

GDP is a measure of production and yet it is widely used as a proxy for well-being. It is particularly ill-suited for assessing the contributions of digital goods which are free to consumers and thus excluded from GDP measures. This underscores the need to develop new measures of well-being which can assess not only the contributions of digital goods but also welfare more generally. In Brynjolfsson, Eggers, and Gannamaneni (2017), we propose a new way of measuring consumer welfare using massive online choice experiments. This brief paper motivates the need for such an approach and introduces the method.

Digital versions of labor and capital can be reproduced much more cheaply than their traditional forms. This increases the supply and reduces the marginal cost of both labor and capital. What then, if anything, is becoming scarcer? We posit a third factor, ''genius'', that cannot be duplicated by digital technologies. Our approach resolves several macroeconomic puzzles. Over the last several decades, both real median wages and the real interest rate have been stagnant or falling in the United States and the World. Furthermore, shares of income paid to labor and capital (properly measured) have also decreased. And despite dramatic advances in digital technologies, the growth rate of measured output has not increased. No competitive neoclassical two-factor model can reconcile these trends. We show that when increasingly digitized capital and labor are sufficiently complementary to inelastically supplied genius, innovation augmenting either of the first two factors can decrease wages and interest rates in the short and long run. Growth is increasingly constrained by the scarce input, not labor or capital. We discuss microfoundations for genius, with a focus on the increasing importance of superstar labor. We also consider consequences for government policy and scale sustainability.

L’uomo sta perdendo la gara con la tecnologia? La tecnologia e l’innovazione lo stanno impoverendo? L’innovazione sta distruggendo posti di lavoro invece di crearne? Perché la ripresa economica è senza lavoro? Come può succedere che dell’enorme valore creato dalla tecnologia non benefici l’intera società, ma solo una minoranza? Come può esserci un’accelerazione delle tecnologie mentre i redditi ristagnano? A queste domande, che sembrano dei paradossi, i due autori, professori del mit, cercano di rispondere in questo saggio che ha mosso un dibattito vastissimo anche in Italia. Lo sviluppo della tecnologia e dell’innovazione non va a beneficio di tutti, anzi accelera le criticità e le disuguaglianze della società. C’è una via d’uscita? Sì! Consiste nel lavorare con le macchine innovando le organizzazioni, investendo nel capitale umano attraverso la scuola e la formazione continua. Gli autori indicano diciannove aree d’intervento per battere le macchine. In questa seconda edizione è presente una sezione eXtra con due saggi: il primo si chiede se il pil riesca ancora a misurare l’andamento reale dell’economia e del benessere di un Paese; il secondo, di Giulio Sapelli, analizza le problematiche del capitalismo tecnologico in relazione al lavoro, ai lavoratori e ai sindacati.

“A clear and crisply written account of machine intelligence, big data and the sharing economy. But McAfee and Brynjolfsson also wisely acknowledge the limitations of their futurology and avoid over-simplification.” —Financial Times In The Second Machine Age, Andrew McAfee and Erik Brynjolfsson predicted some of the far-reaching effects of digital technologies on our lives and businesses. Now they’ve written a guide to help readers make the most of our collective future. Machine | Platform | Crowd outlines the opportunities and challenges inherent in the science fiction technologies that have come to life in recent years, like self-driving cars and 3D printers, online platforms for renting outfits and scheduling workouts, or crowd-sourced medical research and financial instruments.

Wie aufmerksame Leser wissen, beschäftigt sich XING Magazin gerne mit Zukunftsfragen. Das ist kein einfaches Terrain, und - so mögen Sie vielleicht einwenden - auch vergebene Liebesmüh ́. Viele Menschen haben den Eindruck, dass Fortschritt ein autonomer (sozialer) Prozess sei, der sich wie eine Naturgewalt vollzieht und das Individuum hätte nur die Wahl, sich diesen Entwicklungen anzuschließen, oder zunehmende Isolation in Kauf zu nehmen. Willy Brandt würde einer solchen Einstellung wahrscheinlich nicht zustimmen, denn ihm wird das Credo zugeschrieben: ,,Der beste Weg, die Zukunft vorauszusagen, ist, sie zu gestalten."

Faut-il avoir peur des robots ? Les plateformes que sont Facebook, Google et autres vont-elles régner sans partage sur l’économie ? Que deviennent les compétences et les métiers à l’ère du tout-numérique ?Écrit par deux des meilleurs spécialistes de la transformation numérique, ce livre met à la portée de tous les évolutions que l’on constate aujourd’hui, notamment en matière d’intelligence artificielle — algorithmes de plus en plus puissants, apprentissage profond (deep learning), etc. Plutôt que de céder à la crainte et aux fantasmes que font naître ces bouleversements, Erik Brynjolfsson et Andrew McAfee nous invitent à imaginer de nouvelles collaborations entre la machine et le cerveau humain, les plateformes et les produits, l’intelligence collective et les savoir-faire au sein des entreprises. Nourri d’exemples passionnants de machines intelligentes et créatives, d’entreprises pionnières, de collaborations possibles entre la machine et l’homme, ce livre est une mine pour tous ceux qui veulent maîtriser les principes fondamentaux de ce nouveau monde. Andrew McAfee dirige la recherche scientifique du Center for Digital Business du MIT. Erik Brynjolfsson est économiste et dirige le Center for Digital Business du MIT (Massachusetts Institute of Technology). Ils ont coécrit Le Deuxième Âge de la machine, best-seller du New York Times.

★★Amazon.com商業理財Top1 ★★ 全球暢銷書《第二次機器時代》作者最新力作 兩位MIT數位頂尖科學家歷時三年時間 走訪矽谷、華府、劍橋、紐約、倫敦、舊金山等科技政經重鎮 拜會許多領域精英進行交流，結合宏觀趨勢觀察， 指出人人都應關注的三重革命 科技正以空前速度改變每個產業及每個人的生活， 你該如何做，才能保持領先？ 我們生活在一個奇特的時代，人工智慧擊敗頂尖的人類圍棋高手，也以空前效率運作現代資料中心。在全球許多市場上，優異的智慧型手機已經不再足以確保製造商賺錢，反而是蘋果和谷歌之類的平台建造者，才能攫取高份額的價值。在一個又一個的競爭場上，從計算生物學到量化投資，生手擊敗標竿，門外漢比知名專家想得更快、更遠。 這個世界究竟發生了什麼事？本書作者安德魯．麥克費和艾瑞克．布林優夫森為MIT史隆管理學院教授，也是數位科技領域的頂尖思想家，點出由於近年來的科技變化，每個人都必須正視數位三重革命，重新思考人腦與機器之間、產品與平台之間、核心與群眾之間的再平衡。了解這件事不是重要，已是必要。 人腦與機器 人工智慧、自動駕駛汽車、無人機、3D列印機、人工神經網路……，種種形式的數位機器超越以往限制，扮演起全新角色。人腦聰明、直覺性強，但有各種偏誤與缺失，最好的辦法就是建立、善用人機新夥伴關係，在合適情境中讓機器做決策，再明智地讓人類智慧參與其中。。﷽﷽﷽﷽﷽﷽﷽﷽﷽﷽﷽﷽﷽誤、缺師，，，， 產品與平台 線上平台改變成本結構，改善供需媒合，在音樂、城市運輸、電腦軟硬體、團體運動等無數產業，創造出可畏的新競爭者。這一波平台革命最應關注的是第二代O2O（Online to Offline）平台，，﷽﷽﷽﷽﷽﷽﷽﷽﷽﷽﷽line)師，，能以多重效應結合原子經濟與位元經濟。﷽﷽﷽﷽﷽﷽﷽﷽﷽﷽﷽﷽﷽﷽e)師，，創造極大價值。 核心與群眾 在網路上自動集結的全球群眾，合力打造出世界上最大的作業系統與線上百科全書。秉持著開放等原則，經常可見業外人士一再擊敗領域專家。群眾撼動核心，而聰明的組織則謀劃善用群眾的力量。 本書充滿科幻成真的實例，以及新創公司如何變成全球重炮的故事，但作者並非只是綜述這些新發展而已，也引據經濟學等學科理論，解釋這些創新與破壞背後的基本原理。 現在，不論個人或整個社會，可以運用的科技力量遠比以往更強大。我們擁有更多自由，可以做到先前世代無法做到的事，所以價值觀的重要性也就更甚以往。機器、平台、群眾，可以帶來非常不同的影響，一切取決於我們如何運用。 強力推薦 「就連矽谷，也被現今的變化速度與範圍震驚。想要掌握這些驚人的變化，最好的方法就是了解背後的根本原理──那些縱使在諸多破壞中依舊持久不變的原理，而本書對那些原理提供了最佳解釋。」 ──艾力克‧施密特（Eric Schmidt），前谷歌執行長，Alphabet, Inc. 執行董事長 「我們邁入的數位革命令人感到不安，但麥克費及布林優夫森告訴我們，這些強大的技術將使我們的選擇比以往更為重要。本書是所有領導人航行於這個新世界時，能夠有效做出明智選擇的路線圖。」 ──雅莉安娜‧哈芬登（Arianna Huffington），前《哈芬登郵報》（The Huffington Post）總裁暨總編輯，《從容的力量》（Thrive）及《愈睡愈成功》（The Sleep Revolution）作者 「人工智慧、平台、群眾，全是強大的改造力量。它們的同時演進，意味著我們開始經歷網路型破壞的新紀元，有益但容易令人迷失的變遷變成現狀。想要成功航行於這個新世界的民眾、創業者、公司及政府，第一步就是找到可靠、具有先見之明的嚮導，麥克費及布林優夫森就是兩位最佳嚮導。」 ──雷德‧霍夫曼（Reid Hoffman），創投公司Greylock Partners合夥人、領英（LinkedIn）共同創辦人，《自創思維》（The Start-Up of You）及《聯盟世代》（The Alliance）合著作者 「本書兩位作者說明了驚人的科技發展，如何改變我們的生活，並且分享和全球領導人息息相關的精闢洞察。沒有人確定未來會如何變化，但可以確定的是，我們必須把科技的破壞力量視為機會，好好掌握，以謀劃我們的未來。本書敦促我們思考：我們是否將善用科技來幫助加速發展、改善生活水準，促進包容性的成長？我們是否將善用科技的力量，去除制度上的繁文縟節，投資於教育，釋放創業能量，創造新的就業機會？這本書對所有尋求指引的政治制定者來說，都是一本必讀之作，有助於了解如何結合人類與科技的力量，為民眾創造更美好的未來。」 ──克里斯蒂娜‧拉加德（Christine Lagarde），國際貨幣基金組職董事總經理 影音： l 人類該害怕人工智慧嗎？https://youtu.be/QajYpPjuUiY l 三個關鍵詞，決定你的未來https://youtu.be/4ic0-Qf4PbA

We live in an age of paradox. Systems using artificial intelligence match or surpass human level performance in more and more domains, leveraging rapid advances in other technologies and driving soaring stock prices. Yet measured productivity growth has declined by half over the past decade, and real income has stagnated since the late 1990s for a majority of Americans. We describe four potential explanations for this clash of expectations and statistics: false hopes, mismeasurement, redistribution, and implementation lags. While a case can be made for each, we argue that lags have likely been the biggest contributor to the paradox. The most impressive capabilities of AI, particularly those based on machine learning, have not yet diffused widely. More importantly, like other general purpose technologies, their full effects won''t be realized until waves of complementary innovations are developed and implemented. The required adjustment costs, organizational changes, and new skills can be modeled as a kind of intangible capital. A portion of the value of this intangible capital is already reflected in the market value of firms. However, going forward, national statistics could fail to measure the full benefits of the new technologies and some may even have the wrong sign.

Recent years have seen dramatic changes in data storage and processing technologies. New opportunities to collect and leverage data have led many managers to change how they make decisions -- relying less on intuition and more on data. In this paper we provide the first systematic empirical study of the diffusion of data-driven decision-making and the factors influencing its adoption.