The Coming AI Revolution

“The Coming AI Economic Revolution: Can Artificial Intelligence Reverse the Productivity Slowdown?” was recently published in Foreign Affairs by James Manyika and Michael Spence, two authors I’ve long admired. James Manyika is senior VP of research, technology and society at Google, after serving as chairman and director of the McKinsey Global Institute from 2009 to 2022. Michael Spence, a co-recipient of the 2001 Nobel Prize in Economics, is professor in economics and business at NYU’s Stern School of Business, and was previously professor of management and dean of the Stanford Graduate School of Business.

Irving Wladawsky-BergerIrving Wladawsky-BergerMarch 2, 2024artificial intelligence, complex systems, economic issues, future of work, management and leadership, political issues, services innovation, society and culture, technology and strategy

The Current State and Future Trends of Enterprise Blockchain Technologies

“Blockchain is one of the major tech stories of the past decade,” said a December, 2022 McKinsey article, “What is Blockchain.” “Everyone seems to be talking about it — but beneath the surface chatter there’s not always a clear understanding of what blockchain is or how it works. Despite its reputation for impenetrability, the basic idea behind blockchain is pretty simple,” namely: “Blockchain is a technology that enables the secure sharing of information.”

Irving Wladawsky-BergerIrving Wladawsky-BergerFebruary 20, 2024blockchain and identity, cloud computing, complex systems, economic issues, innovation, management and leadership, open source, services innovation, society and culture, technology and strategy, blockchain

What’s the Likely Long Term Evolution of AI?

Since the advent of the Industrial Revolution, general purpose technologies (GPTs) have been the defining technologies of their times. Their ability to support a large variety of applications can, over time, radically transform economies and social institutions. GPTs have great potential from the outset, but realizing their potential takes large tangible and intangible investments and a fundamental rethinking of firms and industries, including new processes, management structures, business models, and worker training. As a result, realizing the potential of a GPT takes considerable time, often decades. Electricity, the internal combustion engine, computers, and the internet are all examples of historically transformative GPTs.

Irving Wladawsky-BergerIrving Wladawsky-BergerSeptember 4, 2023artificial intelligence, complex systems, data science and big data, economic issues, education and talent, future of work, innovation, political issues, services innovation, smart systems, society and culture, technology and strategy, permalink

The 2022 State of AI in the Enterprise

“Rapidly transforming, but not fully transformed - this is our overarching conclusion on the market, based on the fourth edition of our State of AI in the Enterprise global survey,” said Becoming an AI-fueled organization, the fourth survey conducted by Deloitte since 2017 to assess the adoption of AI across enterprises. “Very few organizations can claim to be completely AI-fueled, but a significant and growing percentage are starting to display the behaviors that can get them there.”

Irving Wladawsky-BergerIrving Wladawsky-BergerOctober 4, 2022technology and strategy, services innovation, artificial intelligence, management and leadership, economic issues, innovation, education and talent, complex systems

How Can You Trust the Predictions of a Large Machine Learning Model?

Artificial intelligence has emerged as the defining technology of our era, as transformative over time as the steam engine, electricity, computers, and the Internet. AI technologies are approaching or surpassing human levels of performance in vision, speech recognition, language translation, and other human domains. Machine learning (ML) advances, like deep learning, have played a central role in AI’s recent achievements, giving computers the ability to be trained by ingesting and analyzing large amounts of data instead of being explicitly programmed.

Irving Wladawsky-BergerIrving Wladawsky-BergerMay 24, 2022artificial intelligence, complex systems, data science, big data, education and talent, innovation, management and leadership, services innovation, smart systems, society and culture, technology and strategy

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