Irving Wladawsky-Berger

What’s the Value of Open Source Software Based on Actual Usage Data?

“The value of a non-pecuniary (free) product is inherently difficult to assess,” wrote Manuel Hoffmann, Frank Nagle, and Yanuo Zhou in their recent working paper, “The Value of Open Source Software.” “A pervasive example is open source software (OSS), a global public good that plays a vital role in the economy and is foundational for most technology we use today.” The paper reminded us that in 2011, VC Mark Andreessen famously argued that software is eating the world. Then two years ago, VC Joseph Jacks added that open source is eating software FASTER than software is eating the world.

“Other recent studies have come to similar conclusions showing that open source software (OSS) — software whose source code is publicly available for inspection, use, and modification and is often created in a decentralized manner and distributed for free — appears in 96% of codebases, and that some commercial software consists of up to 99.9% freely available OSS,” said the paper. “Although in its early days OSS frequently copied features from existing proprietary software, OSS today includes cutting edge technology in various fields including artificial intelligence (AI), quantum computing, big data, and analytics.”

But, despite the increasing importance of OSS to the economy, its overall impact has been difficult to quantify. The reason is that the value created by a good or service is traditionally measured by multiplying the price p times the quantities sold q, but with OSS, the p is generally zero since open source code is publicly available, and its actual usage q has been very hard to measure.

The Case for Open Healthcare Systems

As we’ve learned since the advent of the Industrial Revolution, major technological advances have the potential to radically transform a whole industry, but realizing that potential generally requires large intangible investments and a fundamental rethinking the industry being transformed. So, it’s not surprising that there’s much hope and excitement that the advent of AI as a major 21st century technological advance might, over time, help to radically transform our highly complex and expensive healthcare industry. 

Healthcare is a system of coupled systems, encompassing medical and pharmaceutical research; the delivery of healthcare to patients by a variety of practitioners, including hospitals, physicians, nurses, and pharmacists; and the insurance companies and governments that pay for healthcare. Healthcare costs have continued to rise across the world, especially in the US. Total healthcare spending in 2023 was approximately $4.7 trillion, accounting for 18% of US GDP, and is projected to grow at an average of 5.5% per year to over $7 trillion in 2031, roughly 20% of US GDP.

The potential evolution of healthcare brings to mind my personal experience in the information technology (IT) industry for the past 50 years.

The Uncertain Impact of AI on Economies and Societies

“Artificial intelligence (AI) promises to boost productivity and growth, but its impact on economies and societies is uncertain, varying by job roles and sectors, with the potential to amplify disparities,” said “GenAI: Artificial Intelligence and the Future of Work,” a recently published report by the International Monetary Fund (IMF). “As a positive productivity shock, AI will expand economies’ production frontiers and will lead to reallocations between labor and capital while triggering potentially profound changes in many jobs and sectors. AI offers unprecedented opportunities for solving complex problems and improving the accuracy of predictions, enhancing decision-making, boosting economic growth, and improving lives. However, precisely because of its vast and flexible applicability in numerous domains, the implications for economies and societies are uncertain.”

“The impact of AI is also likely to differ significantly across countries at different levels of development or with different economic structures,” adds the IMF report. “Advanced economies, with their mature industries and service-driven economies, typically have a higher concentration of jobs in sectors that require complex cognitive tasks. These economies are therefore both more susceptible to, yet better positioned to benefit from, AI innovations.”

“Conversely, emerging market and developing economies, often still reliant on manual labor and traditional industries, may initially face fewer AI-induced disruptions. However, these economies may also miss out on early AI-driven productivity gains, given their lack of infrastructure and a skilled workforce. Over time, the AI divide could exacerbate existing economic disparities, with advanced economies harnessing AI for competitive advantage while emerging market and developing economies grapple with integrating AI into their growth models.”

The Promise of Digital Health in the 21st Century

In 2021 the Linux Foundation (LF) announced the formation of Linux Foundation Research, a new organization to broaden the understanding of open source ecosystems and to explore opportunities for new open source initiatives. Given my long involvement with Linux, the Linux Foundation and open source communities in general, I was invited to become a member of the newly created LF Research Advisory Board (RAB).

At a September, 2023 meeting of the Advisory Board, we discussed that one of the few industry sectors in which the LF does not have projects is healthcare, despite its size and importance around the world. The LF had launched healthcare initiatives in the past, but they all eventually failed. At that meeting, LF Research launched a study to understand what we should be doing in the healthcare sector. I’m involved in the study, and for the past several months, I’ve been learning about the opportunities of digital technologies in healthcare systems by reading a number of articles and talking to key experts.

“The Promise of Digital Health: Then, Now, and the Future,” a discussion paper published in June of 2022 by the US National Academy of Medicine is one of the articles that I found most instructive. The paper is based on the contributions of 25 member of the National Academy of Medicine (NAM), including two of the experts I’ve recently spoken with, John Halamka and Peter Lee.