Podcast appearances and mentions of Jim Manzi

We're joined by analyst Ana Lai and co-host Jim Manzi to discuss the global office sector's uneven recovery post-pandemic. We dive into the vacancy rates in different regions around the world, pricing trends for the office sector in a higher-for-longer" interest rate environment, and office performance in relation to the CMBS market. We also discuss distributions of North American REIT debt maturities across commercial real estate sectors, especially for the office sector, and what that means for the market. Finally, we touch on our outlook for the U.S. office market going forward. Related Articles: SLIDES: Uneven Global Office Recovery Is Squeezing Credit Quality

Nelumbo nucifera, or the sacred lotus, is a plant that grows in flood plains, rivers, and deltas. Their seeds can remain dormant for years and when floods come along, blossom into a colony of plants and flowers. Some of the oldest seeds can be found in China, where they're known to represent longevity. No surprise, given their level of nitrition and connection to the waters that irrigated crops by then. They also grow in far away lands, all the way to India and out to Australia. The flower is sacred in Hinduism and Buddhism, and further back in ancient Egypt. Padmasana is a Sanskrit term meaning lotus, or Padma, and Asana, or posture. The Pashupati seal from the Indus Valley civilization shows a diety in what's widely considered the first documented yoga pose, from around 2,500 BCE. 2,700 years later (give or take a century), the Hindu author and mystic Patanjali wrote a work referred to as the Yoga Sutras. Here he outlined the original asanas, or sitting yoga poses. The Rig Veda, from around 1,500 BCE, is the oldest currently known Vedic text. It is also the first to use the word “yoga”. It describes songs, rituals, and mantras the Brahmans of the day used - as well as the Padma. Further Vedic texts explore how the lotus grew out of Lord Vishnu with Brahma in the center. He created the Universe out of lotus petals. Lakshmi went on to grow out of a lotus from Vishnu as well. It was only natural that humans would attempt to align their own meditation practices with the beautiful meditatios of the lotus. By the 300s, art and coins showed people in the lotus position. It was described in texts that survive from the 8th century. Over the centuries contradictions in texts were clarified in a period known as Classical Yoga, then Tantra and and Hatha Yoga were developed and codified in the Post-Classical Yoga age, and as empires grew and India became a part of the British empire, Yoga began to travel to the west in the late 1800s. By 1893, Swami Vivekananda gave lectures at the Parliament of Religions in Chicago.  More practicioners meant more systems of yoga. Yogendra brought asanas to the United States in 1919, as more Indians migrated to the United States. Babaji's kriya yoga arrived in Boston in 1920. Then, as we've discussed in previous episodes, the United States tightened immigration in the 1920s and people had to go to India to get more training. Theos Bernard's Hatha Yoga: The Report of a Personal Experience brought some of that knowledge home when he came back in 1947. Indra Devi opened a yoga studio in Hollywood and wrote books for housewives. She brought a whole system, or branch home. Walt and Magana Baptiste opened a studio in San Francisco. Swamis began to come to the US and more schools were opened. Richard Hittleman began to teach yoga in New York and began to teach on television in 1961. He was one of the first to seperate the religious aspect from the health benefits. By 1965, the immigration quotas were removed and a wave of teachers came to the US to teach yoga. The Beatles went to India in 1966 and 1968, and for many Transcendental Meditation took root, which has now grown to over a thousand training centers and over 40,000 teachers. Swamis opened meditation centers, institutes, started magazines, and even magazines. Yoga became so big that Rupert Holmes even poked fun of it in his song “Escape (The Piña Colada Song)” in 1979. Yoga had become part of the counter-culture, and the generation that followed represented a backlash of sorts. A common theme of the rise of personal computers is that the early pioneers were a part of that counter-culture. Mitch Kapor graduated high school in 1967, just in time to be one of the best examples of that. Kapor built his own calculator in as a kid before going to camp to get his first exposure to programming on a Bendix. His high school got one of the 1620 IBM minicomputers and he got the bug. He went off to Yale at 16 and learned to program in APL and then found Computer Lib by Ted Nelson and learned BASIC. Then he discovered the Apple II.  Kapor did some programming for $5 per hour as a consultant, started the first east coast Apple User Group, and did some work around town. There are generations of people who did and do this kind of consulting, although now the rates are far higher. He met a grad student through the user group named Eric Rosenfeld who was working on his dissertation and needed some help programming, so Kapor wrote a little tool that took the idea of statistical analysis from the Time Shared Reactive Online Library, or TROLL, and ported it to the microcomputer, which he called Tiny Troll.  Then he enrolled in the MBA program at MIT. He got a chance to see VisiCalc and meet Bob Frankston and Dan Bricklin, who introduced him to the team at Personal Software. Personal Software was founded by Dan Fylstra and Peter Jennings when they published Microchips for the KIM-1 computer. That led to ports for the 1977 Trinity of the Commodore PET, Apple II, and TRS-80 and by then they had taken Bricklin and Franston's VisiCalc to market. VisiCalc was the killer app for those early PCs and helped make the Apple II successful. Personal Software brought Kapor on, as well as Bill Coleman of BEA Systems and Electronic Arts cofounder Rich Mellon. Today, software developers get around 70 percent royalties to publish software on app stores but at the time, fees were closer to 8 percent, a model pulled from book royalties. Much of the rest went to production of the box and disks, the sales and marketing, and support. Kapor was to write a product that could work with VisiCalc. By then Rosenfeld was off to the world of corporate finance so Kapor moved to Silicon Valley, learned how to run a startup, moved back east in 1979, and released VisiPlot and VisiTrend in 1981. He made over half a million dollars in the first six months in royalties.  By then, he bought out Rosenfeld's shares in what he was doing, hired Jonathan Sachs, who had been at MIT earlier, where he wrote the STOIC programming language, and then went to work at Data General. Sachs worked on spreadsheet ideas at Data General with a manager there, John Henderson, but after they left Data General, and the partnership fell apart, he worked with Kapor instead. They knew that for software to be fast, it needed to be written in a lower level language, so they picked the Intel 8088 assembly language given that C wasn't fast enough yet. The IBM PC came in 1981 and everything changed. Mitch Kapor and Jonathan Sachs started Lotus in 1982. Sachs got to work on what would become Lotus 1-2-3. Kapor turned out to be a great marketer and product manager. He listened to what customers said in focus groups. He pushed to make things simpler and use less jargon. They released a new spreadsheet tool in 1983 and it worked flawlessly on the IBM PC and while Microsoft had Multiplan and VisCalc was the incumbent spreadsheet program, Lotus quickly took market share from then and SuperCalc. Conceptually it looked similar to VisiCalc. They used the letter A for the first column, B for the second, etc. That has now become a standard in spreadsheets. They used the number 1 for the first row, the number 2 for the second. That too is now a standard. They added a split screen, also now a standard. They added macros, with branching if-then logic. They added different video modes, which could give color and bitmapping. They added an underlined letter so users could pull up a menu and quickly select the item they wanted once they had those orders memorized, now a standard in most menuing systems. They added the ability to add bar charts, pie charts, and line charts. One could even spread their sheet across multiple monitors like in a magazine. They refined how fields are calculated and took advantage of the larger amounts of memory to make Lotus far faster than anything else on the market. They went to Comdex towards the end of the year and introduced Lotus 1-2-3 to the world. The software could be used as a spreadsheet, but the 2 and 3 referred to graphics and database management. They did $900,000 in orders there before they went home. They couldn't even keep up with the duplication of disks. Comdex was still invitation only. It became so popular that it was used to test for IBM compatibility by clone makers and where VisiCalc became the app that helped propel the Apple II to success, Lotus 1-2-3 became the app that helped propel the IBM PC to success. Lotus was rewarded with $53 million in sales for 1983 and $156 million in 1984. Mitch Kapor found himself. They quickly scaled from less than 20 to 750 employees. They brought in Freada Klein who got her PhD to be the Head of Employee Relations and charged her with making them the most progressive employer around. After her success at Lotus, she left to start her own company and later married. Sachs left the company in 1985 and moved on to focus solely on graphics software. He still responds to requests on the phpBB forum at dl-c.com. They ran TV commercials. They released a suite of Mac apps they called Lotus Jazz. More television commercials. Jazz didn't go anywhere and only sold 20,000 copies. Meanwhile, Microsoft released Excel for the Mac, which sold ten times as many. Some blamed the lack os sales on the stringent copy protection. Others blamed the lack of memory to do cool stuff. Others blamed the high price. It was the first major setback for the young company.  After a meteoric rise, Kapor left the company in 1986, at about the height of their success. He  replaced himself with Jim Manzi. Manzi pushed the company into network applications. These would become the center of the market but were just catching on and didn't prove to be a profitable venture just yet. A defensive posture rather than expanding into an adjacent market would have made sense, at least if anyone knew how aggressive Microsoft was about to get it would have.  Manzi was far more concerned about the millions of illegal copies of the software in the market than innovation though. As we turned the page to the 1990s, Lotus had moved to a product built in C and introduced the ability to use graphical components in the software but not wouldn't be ported to the new Windows operating system until 1991 for Windows 3. By then there were plenty of competitors, including Quattro Pro and while Microsoft Excel began on the Mac, it had been a showcase of cool new features a windowing operating system could provide an application since released for Windows in 1987. Especially what they called 3d charts and tabbed spreadsheets. There was no catching up to Microsoft by then and sales steadily declined. By then, Lotus released Lotus Agenda, an information manager that could be used for time management, project management, and as a database. Kapor was a great product manager so it stands to reason he would build a great product to manage products. Agenda never found commercial success though, so was later open sourced under a GPL license. Bill Gross wrote Magellan there before he left to found GoTo.com, which was renamed to Overture and pioneered the idea of paid search advertising, which was acquired by Yahoo!. Magellan cataloged the internal drive and so became a search engine for that. It sold half a million copies and should have been profitable but was cancelled in 1990. They also released a word processor called Manuscript in 1986, which never gained traction and that was cancelled in 1989, just when a suite of office automation apps needed to be more cohesive.  Ray Ozzie had been hired at Software Arts to work on VisiCalc and then helped Lotus get Symphony out the door. Symphony shipped in 1984 and expanded from a spreadsheet to add on text with the DOC word processor, and charts with the GRAPH graphics program, FORM for a table management solution, and COM for communications. Ozzie dutifully shipped what he was hired to work on but had a deal that he could build a company when they were done that would design software that Lotus would then sell. A match made in heaven as Ozzie worked on PLATO and borrowed the ideas of PLATO Notes, a collaboration tool developed at the University of Illinois Champagne-Urbana  to build what he called Lotus Notes.  PLATO was more more than productivity. It was a community that spanned decades and Control Data Corporation had failed to take it to the mass corporate market. Ozzie took the best parts for a company and built it in isolation from the rest of Lotus. They finally released it as Lotus Notes in 1989. It was a huge success and Lotus bought Iris in 1994. Yet they never found commercial success with other socket-based client server programs and IBM acquired Lotus in 1995. That product is now known as Domino, the name of the Notes 4 server, released in 1996. Ozzie went on to build a company called Groove Networks, which was acquired by Microsoft, who appointed him one of their Chief Technology Officers. When Bill Gates left Microsoft, Ozzie took the position of Chief Software Architect he vacated. He and Dave Cutler went on to work on a project called Red Dog, which evolved into what we now know as Microsoft Azure.  Few would have guessed that Ozzie and Kapor's handshake agreement on Notes could have become a real product. Not only could people not understand the concept of collaboration and productivity on a network in the late 1980s but the type of deal hadn't been done. But Kapor by then realized that larger companies had a hard time shipping net-new software properly. Sometimes those projects are best done in isolation. And all the better if the parties involved are financially motivated with shares like Kapor wanted in Personal Software in the 1970s before he wrote Lotus 1-2-3. VisiCalc had sold about a million copies but that would cease production the same year Excel was released. Lotus hung on longer than most who competed with Microsoft on any beachhead they blitzkrieged. Microsoft released Exchange Server in 1996 and Notes had a few good years before Exchange moved in to become the standard in that market. Excel began on the Mac but took the market from Lotus eventually, after Charles Simonyi stepped in to help make the product great.  Along the way, the Lotus ecosystem created other companies, just as they were born in the Visi ecosystem. Symantec became what we now call a “portfolio” company in 1985 when they introduced NoteIt, a natural language processing tool used to annotate docs in Lotus 1-2-3. But Bill Gates mentioned Lotus by name multiple times as a competitor in his Internet Tidal Wave memo in 1995. He mentioned specific features, like how they could do secure internet browsing and that they had a web publisher tool - Microsoft's own FrontPage was released in 1995 as well. He mentioned an internet directory project with Novell and AT&T. Active Directory was released a few years later in 1999, after Jim Allchin had come in to help shepherd LAN Manager. Notes itself survived into the modern era, but by 2004 Blackberry released their Exchange connector before they released the Lotus Domino connector. That's never a good sign. Some of the history of Lotus is covered in Scott Rosenberg's 2008 book, Dreaming in Code. Others are documented here and there in other places. Still others are lost to time. Kapor went on to invest in UUNET, which became a huge early internet service provider. He invested in Real Networks, who launched the first streaming media service on the Internet. He invested in the creators of Second Life. He never seemed vindictive with Microsoft but after AOL acquired Netscape and Microsoft won the first browser war, he became the founding chair of the Mozilla Foundation and so helped bring Firefox to market. By 2006, Firefox took 10 percent of the market and went on to be a dominant force in browsers. Kapor has also sat on boards and acted as an angel investor for startups ever since leaving the company he founded. He also flew to Wyoming in 1990 after he read a post on The WELL from John Perry Barlow. Barlow was one of the great thinkers of the early Internet. They worked with Sun Microsystems and GNU Debugging Cypherpunk John Gilmore to found the Electronic Frontier Foundation, or EFF. The EFF has since been the nonprofit who leads the fight for “digital privacy, free speech, and innovation.” So not everything is about business.    

In this week's episode of Take Notes, hosts Tom Schopflocher and Jim Manzi discuss their recently published chartbook: U.S. Structured Finance Snapshot: The Health Of U.S. Consumers. Topics include U.S. macroeconomic conditions, consumer ABS, housing/RMBS, and non-agency multifamily CMBS, and how the trends in asset classes reflect the health of U.S. consumers. Related Article: U.S. Structured Finance Snapshot: The Health Of U.S. Consumers

Our host, Jim Manzi, is joined by U.S. CLO sector lead Stephen Anderberg, Director Daniel Hu, and research analyst Evan Gunter to do a deep dive into the history of U.S. CLO defaults. Of the 16,000+ CLO tranches that we have rated since the mid-late 1990s, there have been 50 that defaulted. We go over some notable observations and trends (e.g., rating categories, timings, etc.) in our historical data. We also discuss how we look at current tranches that are candidates for a potential default, and what a typical "path to default" might look like. Related Article - CLO Spotlight: U.S. CLO Defaults As Of March 17, 2022

Hosts Tom Schopflocher and Jim Manzi discuss our expectation of another $1 trillion-plus in issuance volume for Global Structured Finance in 2020, as well as our view of some factors that could affect the market in the coming year.

A physics and math wonk from MIT, Jim Manzi figured out early in his career that he loved the application of pragmatic, quantitative approaches to solve pesky real-world business problems, including today, challenges faced by life science and healthcare organizations. Jim’s early life sounds like a Springsteen song, and indeed, he grew up less than 10 feet […]

Hosts Tom Schopflocher and Jim Manzi take a deeper look at the non-QM market, which has been doubling and then some every year for the past few years. With about $20 billion+ in issuance, we explore borrower and loan characteristics, as well as what differentiates non-QM from subprime loans.

Jim Manzi is co-founder of Foundry.ai, a technology studio that creates artificial intelligence software companies, and is a member of Aledade's board. He joins Josh (@DrJIsrael) and Joe (@JoeShonkwiler) to help us understand how machine learning, scientific methodology and experimentation can be used to help guide corporate business decisions.

There may be an art to business, but there is science in data science.  In this episode of the Big Data Beard podcast we talk with McKay Curtis, Senior Principal, Decision Science at The Walt Disney Company, about tackling the challenges of real world business with scientific experimentation.  Hear best practices on how his team works across this giant enterprise to power incredible experiences with data driven insights. This podcast was recorded at the Disney Data and Analytics Conference in Orlando, Florida. Music from this episode is by Andrew Belle.  Please go check him out...you'll thank us! Links: Changing Science of Machine Learning Uncontrolled by Jim Manzi Stone Roses - Breaking into Heaven I Love You, Now Die

How should we think about global warming and climate change? How can we develop a sensible strategy to confront a problem for which the risks are inherently difficult to predict with accuracy? And how might the risks from climate change compare with other threats we'll face in the years ahead? In this Podcast, Jim Manzi, a leading technology entrepreneur, shares his perspective. In contrast to the maximalism we often hear in debates about climate change—“is the world going to end?” or “is this a hoax?”—Manzi urges us to think quantitatively about climate change and to pursue a strategy that would allow us to deal with a range of possible outcomes. Manzi explains why the predictions about climate are inherently uncertain—and warns against taxation that would not meaningfully affect climate change but would empower rivals to the United States like China. Instead, Manzi recommends “technology rather than taxation,” a strategy that emphasizes public and private investment in ambitious research toward technologies that will equip us to meet possible challenges and threats from climate change in the years to come.

How should we think about global warming and climate change? How can we develop a sensible strategy to confront a problem for which the risks are inherently difficult to predict with accuracy? And how might the risks from climate change compare with other threats we'll face in the years ahead? In this Podcast, Jim Manzi, a leading technology entrepreneur, shares his perspective. In contrast to the maximalism we often hear in debates about climate change—“is the world going to end?” or “is this a hoax?”—Manzi urges us to think quantitatively about climate change and to pursue a strategy that would allow us to deal with a range of possible outcomes. Manzi explains why the predictions about climate are inherently uncertain—and warns against taxation that would not meaningfully affect climate change but would empower rivals to the United States like China. Instead, Manzi recommends “technology rather than taxation,” a strategy that emphasizes public and private investment in ambitious research toward technologies that will equip us to meet possible challenges and threats from climate change in the years to come.

How should we think about global warming and climate change? How can we develop a sensible strategy to confront a problem for which the risks are inherently difficult to predict with accuracy? And how might the risks from climate change compare with other threats we'll face in the years ahead? In this Podcast, Jim Manzi, a leading technology entrepreneur, shares his perspective. In contrast to the maximalism we often hear in debates about climate change—“is the world going to end?” or “is this a hoax?”—Manzi urges us to think quantitatively about climate change and to pursue a strategy that would allow us to deal with a range of possible outcomes. Manzi explains why the predictions about climate are inherently uncertain—and warns against taxation that would not meaningfully affect climate change but would empower rivals to the United States like China. Instead, Manzi recommends “technology rather than taxation,” a strategy that emphasizes public and private investment in ambitious research toward technologies that will equip us to meet possible challenges and threats from climate change in the years to come.

Jim Manzi talks with CMBS analysts Mathias Herzog and Edward Twort about the deal pipeline and two of the biggest topics in the European CMBS market—Brexit and retail. We also give an update on some new guidance related to our “CMBS Global Property Evaluation” criteria.

A leading software entrepreneur and developer of artificial intelligence (AI) technology, Jim Manzi shares his perspective on AI—what it is, what it can do today, and how it might develop in the coming years. Manzi also discusses how AI currently affects politics and society, and the implications of progress in AI for the future. Finally, Manzi compares today's advances in computer science and in biology to past scientific breakthroughs in chemistry and physics.

A leading software entrepreneur and developer of artificial intelligence (AI) technology, Jim Manzi shares his perspective on AI—what it is, what it can do today, and how it might develop in the coming years. Manzi also discusses how AI currently affects politics and society, and the implications of progress in AI for the future. Finally, Manzi compares today's advances in computer science and in biology to past scientific breakthroughs in chemistry and physics.

A leading software entrepreneur and developer of artificial intelligence (AI) technology, Jim Manzi shares his perspective on AI—what it is, what it can do today, and how it might develop in the coming years. Manzi also discusses how AI currently affects politics and society, and the implications of progress in AI for the future. Finally, Manzi compares today’s advances in computer science and in biology to past scientific breakthroughs in chemistry and physics.

Jim Manzi is the founder and chairman of Applied Predictive Technologies, a software company that enables businesses to design and conduct large-scale experiments, and a senior fellow at the Manhattan Institute. In this conversation, Kristol and Manzi discuss how scientific trial-and-error might help us develop better business and policy practices. The two also reflect on the limits of science in politics and offer a modest defense of social science experimentation for policy making.

Jim Manzi is the founder and chairman of Applied Predictive Technologies, a software company that enables businesses to design and conduct large-scale experiments, and a senior fellow at the Manhattan Institute. In this conversation, Kristol and Manzi discuss how scientific trial-and-error might help us develop better business and policy practices. The two also reflect on the limits of science in politics and offer a modest defense of social science experimentation for policy making.

Jim Manzi is the founder and chairman of Applied Predictive Technologies, a software company that enables businesses to design and conduct large-scale experiments, and a senior fellow at the Manhattan Institute. In this conversation, Kristol and Manzi discuss how scientific trial-and-error might help us develop better business and policy practices. The two also reflect on the limits of science in politics and offer a modest defense of social science experimentation for policy making.

Jim Manzi, founder and chair of Applied Predictive Technologies, senior fellow at the Manhattan Institute, and author of Uncontrolled, talks with EconTalk host Russ Roberts about the Oregon Medicaid study and the challenges of interpreting experimental results. Manzi notes a number of interesting aspects of the study results that have generally been unnoticed--the relatively high proportion of people in the Oregon study who turned down the chance to receive Medicaid benefits, and the increase (though insignificant) in smoking by those who received Medicaid benefits under the experiment. Along the way, Manzi discusses general issues of statistical significance, and how we might learn more about the effects of Medicaid in the future.

Jim Manzi, founder and chair of Applied Predictive Technologies, senior fellow at the Manhattan Institute, and author of Uncontrolled, talks with EconTalk host Russ Roberts about the Oregon Medicaid study and the challenges of interpreting experimental results. Manzi notes a number of interesting aspects of the study results that have generally been unnoticed--the relatively high proportion of people in the Oregon study who turned down the chance to receive Medicaid benefits, and the increase (though insignificant) in smoking by those who received Medicaid benefits under the experiment. Along the way, Manzi discusses general issues of statistical significance, and how we might learn more about the effects of Medicaid in the future.

Jim Manzi, founder and chair of Applied Predictive Technologies, senior fellow at the Manhattan Institute, and author of Uncontrolled, talks with EconTalk host Russ Roberts about the Oregon Medicaid study and the challenges of interpreting experimental results. Manzi notes a number of interesting aspects of the study results that have generally been unnoticed--the relatively high proportion of people in the Oregon study who turned down the chance to receive Medicaid benefits, and the increase (though insignificant) in smoking by those who received Medicaid benefits under the experiment. Along the way, Manzi discusses general issues of statistical significance, and how we might learn more about the effects of Medicaid in the future.

Jim Manzi, founder and chair of Applied Predictive Technologies, senior fellow at the Manhattan Institute, and author of Uncontrolled, talks with EconTalk host Russ Roberts about the Oregon Medicaid study and the challenges of interpreting experimental results. Manzi notes a number of interesting aspects of the study results that have generally been unnoticed--the relatively high proportion of people in the Oregon study who turned down the chance to receive Medicaid benefits, and the increase (though insignificant) in smoking by those who received Medicaid benefits under the experiment. Along the way, Manzi discusses general issues of statistical significance, and how we might learn more about the effects of Medicaid in the future.

Jim Manzi, author of Uncontrolled, talks with EconTalk host Russ Roberts about the reliability of science and the ideas in his book. Manzi argues that unlike science, which can produce useful results using controlled experiments, social science typically involves complex systems where system-wide experiments are rare and statistical tools are limited in their ability to isolate causal relations. Because of the complexity of social environments, even narrow experiments are unlikely to have the wide application that can be found in the laws uncovered by experiments in the physical sciences. Manzi advocates a trial-and-error approach using randomized field trials to verify the usefulness of many policy proposals. And he argues for humility and lowered expectations when it comes to understanding causal effects in social settings related to public policy.

Jim Manzi, author of Uncontrolled, talks with EconTalk host Russ Roberts about the reliability of science and the ideas in his book. Manzi argues that unlike science, which can produce useful results using controlled experiments, social science typically involves complex systems where system-wide experiments are rare and statistical tools are limited in their ability to isolate causal relations. Because of the complexity of social environments, even narrow experiments are unlikely to have the wide application that can be found in the laws uncovered by experiments in the physical sciences. Manzi advocates a trial-and-error approach using randomized field trials to verify the usefulness of many policy proposals. And he argues for humility and lowered expectations when it comes to understanding causal effects in social settings related to public policy.

Jim Manzi, author of Uncontrolled, talks with EconTalk host Russ Roberts about the reliability of science and the ideas in his book. Manzi argues that unlike science, which can produce useful results using controlled experiments, social science typically involves complex systems where system-wide experiments are rare and statistical tools are limited in their ability to isolate causal relations. Because of the complexity of social environments, even narrow experiments are unlikely to have the wide application that can be found in the laws uncovered by experiments in the physical sciences. Manzi advocates a trial-and-error approach using randomized field trials to verify the usefulness of many policy proposals. And he argues for humility and lowered expectations when it comes to understanding causal effects in social settings related to public policy.

May 22, 2012: Jim Manzi, a senior fellow at the Manhattan Institute, founder and chairman of Applied Predictive Technologies, and contributor to National Review Online, joins Martha Montelongo, Ben Boychuk, and John Seiler to discuss his new book, Uncontrolled. In particular, we focus on Manzi’s policy prescriptions for education, immigration, and welfare. How much government […]