Erik Brynjolfsson - US grants

The project will (1) assess the efficiency and effectiveness of investments in information technology (IT); (2) identify the organizational and IT management practices associated with achieving greater value through IT, and (3) disseminate result in academic, business and policy circles. These issues will be addressed at firm, industry, and country levels, based on several large, detailed, longitudinal databases that will be coupled together for more robust analysis than was heretofore possible. The study will include data on IT in five to 15 industry sectors in 50 countries from 1980-95, and on 200 large US firms for the 1990-95 period. Existing databases will be updated annually, and new databases will be built. The study will shed new light on whether, how, and why IT makes a difference in effectiveness and efficiency across a global spectrum of use, helping to clarify our understanding of the well-known "productivity paradox". It will produce a definitive body of research that uncovers the potential payoffs from IT investment and illuminates the mechanisms by which they can be harnessed.

This is the first year funding of a five-year continuing award. The world of business and organizations is entering a period of dramatic and rapid technology-based transformations that many people believe will be as significant as those that characterized the Industrial Revolution. This project will investigate the profound socioeconomic changes likely to be associated with such transformations through conducting empirical research that is broad-based, in-depth, and longitudinal. Using multiple theoretical and methodological approaches, a panel of strategically-selected firms in established as well as entrepreneurial and emergent businesses will be tracked over time. A comprehensive set of systematic and grounded empirical data in these organizations will be collected and analyzed over five years, and will generate deep insights and general theories about what is really happening as organizations use information technology to transform how they work and interact with the market over time.

Some of the key determinants of productivity, economic growth, innovation, and income inequality are the management practices of firms. Unfortunately, in contrast to labor, capital and resource inputs, consistent and comprehensive data do not exist on management and organizational practices. This project collaborates with the Census Bureau to survey establishments about the nature and extent of these practices.

Intellectual Merit: This is the first large-scale cross-sector panel dataset that can be matched by the US research community to numerous existing datasets on productivity, innovation, employment, technology, energy and indicators of worker well-being (such as health) within the Census Research Data Centers.

Because of the importance of the topic, the Census Bureau believes this can be added as a repeated supplement to the Annual Survey of Manufacturing (ASM) in order to construct a panel of data on about 45,000 establishments. This survey is initially targeted at manufacturing because of the availability of a range of other manufacturing data and the relative ease of measuring productivity, but the plan is to rapidly extend this to other sectors, in particular retail and health care to build on our existing firm-level management surveys in these areas.

The project uses these data to address a number of important research, policy and managerial questions. For example:

- What is the relationship between management, organization, productivity and growth, and what policies can promote these practices to support the growth of US firms?

- What are the extent of regional, industrial and firm-size variations in management and organizational practices;

- What are the dynamics of organizational practices over time and firms?

- What types of management practices are associated with changes in inequality over time?

Broader Impacts: These questions are central to US policy-makers who seek to promote the success of US firms, and to make decisions based on a sound understanding of the economy. The data analysis should yield important academic and policy results.

There is widespread research, business and policy interest in the growing impact of Information and Communication Technologies (IT) on firm productivity, income and inequality. This project would work with the US Census Bureau to collect a massive new 55,000 plant dataset on IT use, twinned with detailed firm management and performance data, and worker income data to investigate the causes and effects of IT. This would create a Census super-survey to be publicly available in the Census RDCs for researchers around the US to use, and on-line as a Public Use Microdata Set (PUMS) for the broad research, business and policy access. In addition, the project would use this new dataset to undertake detailed empirical analysis to describe and determine the causes of effects of computerization, exploiting the rich regional, industry and firm variation in the dataset spanning.

In particular, the project will combine this dataset with detailed Census plant, firm and worker level data, as well as external data, to undertake empirical analysis to describe and determine the causes and effects of the use of IT and variations in management practices on a range of outcomes including growth, innovation, productivity, employment and inequality. It will utilize the rich regional, industry and firm variation in the dataset to deliver both accurate measurement and identification of the drivers of adoption of these practices. The findings would be highly relevant for public policy, business decisions and academic research.

This project will promote exploration of scalable tools to aid workers and organizations adapt to artificially-intelligent robots. In a sharp departure from current robotic systems that have to be programmed for a single manipulation task in a very tightly constrained set of conditions, venture-funded firms are designing and beginning to test qualitatively new robotic technologies that promise to flexibly automate entire classes of embodied tasks in widely divergent conditions. In this likely future, robots will adapt as readily to new repetitive manual tasks as a modern microprocessor adapts to new computational tasks. Such "learning" robots would clearly have profound implications for workers and organizations, but previous research on automation offers only limited guidance on how they will adapt. The researchers have recently begun a nationwide, four-year field study that will identify edge cases in which organizations and low-skill workers achieve unlikely yet systematic success, given the introduction of this disruptive technology. This will allow deriving design constraints for potential solutions from grounded theory, centering on the hard-won, demonstrably successful innovations of a suitably-diverse pool of informants. While existing research stands to unveil the mechanisms behind rare, in vivo learning successes to the world, this FW-HTF-P (Future of Work at the Human-Technology Frontier - Planning) award will assemble a world-class team of researchers who are committed to trying to expand and capitalize upon these mechanisms via new tools. This research has high-impact potential for organizations, lower-skilled workers and policy makers on how to expand and enrich work involving increasingly intelligent systems in the 21st century.

With AI in robotics as the technology, humans collaborating with robots as the workers, and organizations employing both the robots and the workers as the context of work, the team of researchers will specifically contact and convene a group of top experts in diverse technical domains including social media, massive open online courseware, crowdsourced knowledge repositories, peer assessment and coaching, user experience design and platforms for on-demand labor, crowdsourcing and innovation challenge execution. Beyond these technical disciplines, the researchers will invite policymakers and technologists, as the pathways to local success will likely be deeply intertwined with legal and commercialization processes. The researchers will begin by sharing very preliminary findings, research questions and objectives from the current study with a select group of such researchers who may have interest in a potential collaboration. The researchers will then extend formal invitations to a workshop to no more than ten potential collaborators. This workshop will be one day in length and will be described as an opportunity to explore and decide upon potential collaborative opportunities related to helping workers and organizations adapt more productively to general-purpose robots. The researchers will explore potentially new organizational theories that take perspectives such as: (a) accounting for success as a learning problem in which robots, workers and organizations learn from each other; (b) the character of learning infrastructures evident in various practices for adapting to learning machines acting as co-workers; (c) how the organization of such learning practices impacts skill changes, role transformations, as well as workers and organizations. The researchers will then solicit participants' input and commitment for tools to scale the successes inherent in the findings and select the tool likely to have the greatest benefit for the most Americans. The researchers will then jointly craft an FW-HTF-R (Future of Work at the Human-Technology Frontier - Research) proposal with interested collaborators that reflects a rigorous test of this tool in real-world settings. The ultimate goal of this project is to develop the necessary research personnel, research infrastructure, and foundational work to expand the opportunities for studying future technology, future workers, and future work at the level of a FW-HTF full research proposal.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.