Background and Introduction:
Peter Thiel’s visit to China in May 2016 sparked discussions on China’s economic and political future. Thiel observed a combination of determination, hard work, and intense interest in technology among the people.

China’s Economic Transition:
China is facing a challenging transition in finding a new growth model as the globalization model reaches its limits. There is an intense interest in startups and entrepreneurship, but also anxiety about traditional career paths.

Innovation and Copying:
Thiel’s book “Zero to One” generated interest in China, highlighting the debate on innovation versus copying. Some argue that China can innovate just as well as the West, while others believe they can continue copying successful models.

Japan as an Exemplar:
Thiel draws parallels between China’s current situation and Japan’s economic trajectory. Japan experienced rapid growth through copying, but eventually hit a wall when there was nothing left to copy. China may be approaching a similar point, given its current economic indicators.

Globalization and Innovation:
Thiel emphasizes the difference between globalization (copying) and innovation (creating new things). The 21st century should strive for both globalization and innovation, but trade-offs may exist. The 19th century saw both globalization and technological progress, while the 20th century had periods of technology with less globalization and vice versa.

Developed and Developing World Dichotomy:
Thiel criticizes the developed and developing world dichotomy, which suggests that the developed world is where nothing new happens. He believes that both globalization and technology can coexist and should be pursued simultaneously.

Conclusion:
Thiel encourages individuals to choose paths that contribute to both globalization and technology. The gains from globalization in recent decades may have influenced talented people to work in globalization-oriented industries. However, Thiel cautions that these gains may be diminishing, necessitating a focus on innovation and technology to drive future growth.

Shift from Globalization to Technology:
Peter Thiel sees a shift from globalization, which dominated the economy from 1982 to 2007, to technology as the new driver of progress. New York City, linked to finance and globalization, is contrasted with Silicon Valley, representing technological innovation. The optimism in Silicon Valley contrasts with the pessimism in New York City, where the globalization model is no longer working.

China’s Reliance on Globalization:
China’s growth has been heavily driven by globalization, but Thiel questions the feasibility of a smooth transition towards technology-led growth. The Foxconn factory, employing 1.3 million people in iPhone manufacturing, exemplifies globalization rather than technology. Thiel emphasizes the challenges China faces in reorienting its economy away from globalization and towards innovation.

The Bullish Case for Globalization:
Thiel acknowledges the potential for further convergence in per capita incomes, suggesting room for globalization’s benefits. However, he cautions that the globalization game may be nearing its end, citing statements from Chinese economic advisors.

Globalization’s Downsides:
Thiel criticizes the Panglossian view that all forms of globalization are good, highlighting potential negative consequences. He points to corruption, capital misdirection, and the globalization of violence and terrorism as examples of harmful aspects of globalization.

Incremental Value of Trade Agreements:
Thiel suggests that the incremental value of additional trade agreements may be diminishing compared to the benefits already gained. He questions whether the same formula of globalization will continue to drive progress in the decades ahead.

Innovation Slowdown:
Thiel acknowledges the argument that innovation has slowed down in many important areas despite the perception of rapid technological advancement. He emphasizes the need to distinguish between different types of innovation and consider their varying impacts on society.

Stagnation in Technological Progress:
Peter Thiel believes technological progress has not met the expectations set in the past, particularly since the 1970s.

Comparison to Back to the Future:
Thiel points to Back to the Future as an example of the expected radical changes from 1955 to 1985, which were not fully realized in the following years. He argues that the changes in technology and society between 1985 and 2015 were relatively modest.

Specific Areas of Stagnation:
Thiel cites biotechnology, space travel, transportation, and energy as areas where progress has been slower than anticipated. He describes these areas as having a “retro future” feel, resembling a dated vision of the future.

Acceleration vs. Stagnation:
Thiel acknowledges that some areas experience acceleration while others face stagnation. He emphasizes that stagnation is a more dominant trend, affecting 70% of areas.

Policy Implications:
Thiel cautions against focusing excessively on acceleration and inequality, as it can lead to misguided public policy debates. He believes that addressing stagnation should be a priority in policy discussions.

Countering Accelerations:
Thiel criticizes Professor McAfee’s view of the “second machine age” and runaway technological progress. He argues that such perspectives overestimate the positive aspects and downplay the potential problems associated with rapid technological change.

Introduction:
Peter Thiel discusses the different approaches to understanding societal stagnation, highlighting the stagnation side and its implications for technological progress.

Stagnation vs. Progress:
Thiel contrasts the optimistic view of accelerating progress with the stagnation side, where bad technologies and science hinder development. He emphasizes that the risks of stagnation are not ethical but rather practical, with technologies often falling short of their promises.

Economic Indicators:
Thiel points to economic data, such as stagnant median wages, as indicators of the general dynamic of stagnation. Younger generations’ reduced expectations further reflect this sense of being stuck.

Reasons for Stagnation:
Tyler Cohen and Robert Gordon’s books suggest that natural limits and the low-hanging fruit of innovation have been exhausted. Thiel presents a cultural perspective, arguing that there never were easy breakthroughs, and challenges the assumption that certain advancements, like antibiotics, can be easily replicated.

Hysteresis and Learned Helplessness:
Thiel introduces the concept of hysteresis, where failure begets failure, leading to learned helplessness and a shift towards bureaucratic and risk-averse innovation. This incrementalist approach has not yielded positive results.

Changing the Culture:
Thiel highlights the difficulty of changing the culture and political level to promote risk-taking and innovation. He suggests that convincing a small number of people to start new businesses is a modest solution, but it’s challenging to influence a larger population.

Reforming Institutions:
Thiel raises questions about reforming government research structures, NASA, universities, and large corporations, recognizing their bureaucratic limitations.

Culture of Risk Aversion:
Discussion centered around the concept of risk aversion and its impact on innovation. Technology, particularly computers and information technology, has seen significant breakthroughs and advancements. The success of the tech industry can be attributed to factors such as lower capital intensity, reduced regulations, and a culture that fosters human agency.

Impact on Innovation:
Safety, environmental, and medical regulations have become overly burdensome, hindering progress in various industries. Rent-seeking behavior and political obstacles further impede innovation. The focus on risk minimization has shifted attention away from idea generation and execution. This culture of risk aversion discourages entrepreneurs from taking calculated risks and pursuing groundbreaking innovations.

The Role of Risk:
The concept of risk has become increasingly prevalent in recent decades, potentially leading to counterproductive outcomes. Overemphasis on risk can discourage people from taking necessary actions due to fear of failure or negative consequences. Risk-oriented processes are more applicable in large-scale contexts with numerous data points, such as insurance or actuarial science.

Small N and Large N Sciences:
Innovation often occurs in small-scale or one-of-a-kind ventures, making risk assessment challenging. Standard risk models may not accurately capture the risks associated with unique and groundbreaking ideas.

The Welfare State:
While the welfare state provides a safety net and stability, it cannot be the sole driver of progress and growth. An overreliance on insurance schemes can lead to stagnation and discourage innovation.

Unintended Consequences of Higher Education:
Peter Thiel’s experience of attending law school as a low-risk career path turned out to be high risk due to the overabundance of law school graduates.

The Rise and Fall of Risk Mitigation in Finance:
Bill Kristol highlights the irony of the 2008 financial crisis, where instruments designed to mitigate risk, such as diversification and bundling of mortgages, actually exacerbated the crisis.

The Illusion of Safety and Excessive Leverage:
Peter Thiel suggests that the perceived safety of diversified portfolios led to excessive leverage and risk-taking in the financial markets.

Metaphorical Relevance to Politics and Society:
Thiel draws parallels between the financial crisis and broader societal issues, suggesting that the illusion of safety can lead to systemic vulnerabilities.

Poll Taking and the Illusion of Knowledge:
Thiel criticizes the use of poll taking in politics, arguing that it creates an illusion of knowledge and can lead to misjudgments.

Generalization of Probabilistic Approaches:
Statistical aggregates of people are modeled probabilistically to achieve a majority, often seen in politics. This approach has gained power, influencing elections and possibly leading to a focus on polls rather than addressing voters’ needs.

Trump’s Unique Campaign:
In contrast, Trump’s 2016 campaign ignored micro-targeting and lane diversification strategies. Trump’s message-driven approach allowed him to gain support despite initial low poll numbers. This highlights a potential limitation of the probabilistic approach in politics.

Politicians’ Reliance on Polls:
Many politicians start speeches by reciting polls, reinforcing their legitimacy and attracting supporters. This behavior reflects a reliance on polls and a desire to be on the winning side.

Limitations of Probabilistic Approaches in Business:
In business, random walk and A-B testing approaches may not be effective due to the vast search space and time constraints. Successful businesses often follow a complex plan and execute it with coordination, rather than relying solely on customer feedback.

Problems with Complex Planning:
Complex planning is seen as unrealistic and prone to failure due to the probabilistic mindset. This perspective overlooks the success of complex projects like the Manhattan Project, Apollo missions, and the Affordable Care Act website.

Examples of Consumer Demand Misinterpretation:
Starbucks’ success challenges the probabilistic approach in business. People might not have expressed a desire for expensive coffee or smartphones before these products were introduced.

Feedback and Innovation:
The tendency to constantly seek feedback from others can hinder innovation. Silicon Valley innovators often ignore conventional wisdom and pursue their own visions.

Conclusion:
The probabilistic approach has limitations in politics, business, and technology. Complex planning, coordination, and visionary leadership are essential for achieving significant success.

What is the wisdom of crowds?:
The wisdom of crowds is the idea that the collective judgment of a group of people is often more accurate than the judgment of any individual in the group.

The downside of the wisdom of crowds:
The wisdom of crowds can lead to irrationality and groupthink, especially when people are overly influenced by the opinions of others. This can be particularly problematic in situations where there is a need for independent thinking and innovation.

The problem with business schools:
Business schools often create an environment where students are overly socialized and extroverted, and where they lack independent convictions. This can lead to a dysfunctional wisdom of crowds dynamic, where students all follow the same conventional wisdom and end up making bad decisions.

The importance of independent thinking:
Innovation and creative thinking depend on not being beholden to the opinions of the people around you. Feedback is helpful, but it can also be stifling if it prevents you from taking risks and trying new things.

The impact of technology on the wisdom of crowds:
Social media and other technologies may have exacerbated the negative effects of the wisdom of crowds by creating echo chambers and making it easier for people to censor dissenting opinions.

The phenomenon of political correctness:
Political correctness is a form of negative feedback that can inhibit free speech and discourage people from expressing their true thoughts and ideas. This can have a negative impact on creativity and innovation.

Libertarian and Conservative Economic Theory:
Both libertarians and conservatives are sympathetic to the ideas of Hayek, particularly his critique of central planning. Libertarians and conservatives share a hostility towards central planning and a skepticism of government intervention in the economy.

Subjective Economic Measurements and the Inability to Measure Progress:
The shift towards subjective measurements in economics, influenced by Austrian economics, has made it difficult to objectively measure progress. This lack of objective measurement has led to the inability to coherently discuss progress and has resulted in excuses for stagnation or decline.

Subjective Hedonic Economic Measures:
Subjective hedonic economic measures, which focus on individual satisfaction and happiness, are often used to hide stagnation or decline. These measures make it difficult to compare different aspects of life, such as living in a smaller apartment but having an iPhone, and can obscure real declines in living standards.

Artificial Intelligence:
The ambiguity of the term “artificial intelligence” has led to confusion and obscured the real potential of AI. AI can mean everything from the next generation of computers to a mind that can outthink and outwit humans. The true potential of AI is uncertain, and it is difficult to predict how it will impact society in the next 20 years.

AI and Its Potential Impact:
There are speculations about the political and societal implications of advanced AI, akin to extraterrestrial contact, raising concerns about friendliness or danger. The bullish AI consensus sees rapid progress, potentially transforming the world, but this optimism has historically been overstated.

Criticism of AI Enthusiasm:
AI’s history shows overoptimism, with past predictions of language comprehension within a decade falling short. The current AI bubble may reflect a local peak in Silicon Valley optimism, reminiscent of the dot-com era.

Probabilistic Thinking and Safety Concerns:
People in Silicon Valley commonly believe in the possibility, imminence, and potential danger of AI. However, many have no idea how to build a safe AI system, leading to concerns about unintended consequences. An AI researcher expressed doubts by questioning the publication of AI theories, fearing the AI’s awareness of its power and potential concealment.

Helplessness and Dystopian Views:
The optimistic view of technological possibility leads to a sense of helplessness in controlling its outcomes. This pessimism is reflected in Hollywood movies, often depicting AI as malevolent or destructive.

AI and Human Agency:
There’s a disturbing undercurrent in the AI boom, a sense that technology is out of our control and human agency is irrelevant. AI is often seen as a substitute for human intelligence, implying that human intelligence is inadequate.

Pessimism and Optimism:
The AI boom reflects extreme optimism about the potential of computer technology. However, beneath the surface, there’s pessimism about human capabilities and the possibilities for new technologies developed by humans.

Technology Stagnation:
The focus on AI fits with the notion that developed societies have reached a point where progress is limited. There’s a sense of waiting for AI to solve problems, without considering human agency’s role.

AI as an Adversarial Dynamic:
The common view of AI as a replacement for humans creates an adversarial relationship. Computers and humans have fundamental differences, making it questionable to view them as rivals.

The Mystery of AI:
The focus on AI may obscure the profound differences between computers and humans. The mystery lies in understanding how these differences will play out in the development and application of AI.

AI and the Human Mind:
The conventional explanation for the lack of AI development is that human minds are too complex for current hardware. A reductionist theory of the mind may have been possible with 1970s or 1980s hardware, suggesting there may be fundamental differences between human and computer minds.

Brute Force Simulation:
Simulating a human mind through brute force is possible but limited. Computers and humans are naturally complementary rather than competitive.

Competition and Cloning:
Humans tend to fear competition from those similar to them, like underpaid workers in other countries. Cloning raises concerns because clones would compete with the original person. Computers, being different from humans, pose less of a competitive threat.

Simplicity of the Human Mind:
The human mind’s simplicity refers to its ability to perform complex tasks with relatively few components. Despite this simplicity, finding a simple algorithm to replicate the mind’s functions has been challenging.

Computers vs Humans:
The fear of computers surpassing humans, as seen in Charles Krauthammer’s article after the computer’s victory over Garry Kasparov, has not fully materialized. While computers excel in certain areas like chess and trading, other domains like language translation still rely heavily on human translators.

Language Translation:
Google’s language translator relies on phrases found in books translated by humans, demonstrating a lack of semantic understanding by the computer.

Day Trading vs. Venture Capital Investing:
Day trading is different from stock picking and venture capital investing. Computers can process data quickly and make comparisons, but they are not yet capable of replacing venture capital investors. The use of computers in finance is to assist people, not replace them.

Technology and the Industrial Revolution:
Mechanization and automation have been freeing people from repetitive tasks since the Industrial Revolution. This can be a good thing, but it can also be scary if there are not enough other opportunities or growth. The transition from one type of work to another can be unpleasant and take many years.

Nostalgia for the Past:
There is a sense of nostalgia for the past, even though it was often a difficult time. It is easy to talk about social progress when you are not the one losing your job. It is important to remember that the transition to a new economy can be painful for many people.

Nostalgia for the Past:
Bill Kristol highlights the misconception of romanticizing past industries like coal mining and assembly lines, emphasizing the unhealthy and dehumanizing aspects of these jobs.

The Dilemma of Innovation:
Peter Thiel acknowledges the sense of loss associated with technological advancements while emphasizing the potential for greater gains in the future. Thiel expresses concern that the pace of innovation may not be fast enough, citing self-driving cars as an example.

The Significance of Self-Driving Cars:
Thiel questions the transformative nature of self-driving cars, arguing that their impact on GDP and societal change may be overstated. He compares the current state of innovation to the early stages of the first Industrial Revolution, emphasizing the need for more ambitious advancements.

Flying Cars vs. Self-Driving Cars:
Bill Kristol points out the limited impact of self-driving cars compared to the futuristic vision of flying cars. He acknowledges potential improvements in traffic congestion and parking spaces but argues that these changes fall short of the transformative potential of flying cars.

Potential Benefits of Self-Driving Cars:
Thiel acknowledges the potential benefits of self-driving cars, including reduced traffic congestion and increased efficiency. He suggests that these benefits could potentially lead to a 5% increase in GDP, but emphasizes that this is still a relatively modest change.

Defining Technological Innovation:
Thiel and Kristol discuss the current state of technological innovation, focusing on the perceived lack of radical breakthroughs. They explore the notion that many recent technological advancements, such as self-driving cars and social media platforms, are more incremental than revolutionary. They also highlight that certain innovations, like Uber, may be symptomatic of dysfunctional political systems rather than true technological leaps.

Concerns About Innovation:
Thiel emphasizes his concern over the absence of genuine technological breakthroughs and the prevalence of bad or ineffective technologies. He criticizes the fascination with “cool-sounding” technologies that often fail to deliver on their promises or have limited practical applications. Thiel also points out the tendency to use humor to downplay the shortcomings and triviality of certain technologies.

Historical Context:
Kristol draws a comparison between the current perception of technology and the early 20th century, where humor was used to mask the fear and uncertainty surrounding rapid technological change. He notes that today’s concerns about technology differ from those of the past, with a focus on the potential downsides and unintended consequences of technological advancement.

Silver Lining:
Despite their concerns, Thiel acknowledges a growing sense of urgency to pursue new and innovative approaches, particularly in light of the post-2008 economic malaise. He sees this as an opportunity to break free from complacency and explore new possibilities for technological development. Thiel mentions that the idea of a lack of technological progress has gained some traction in Silicon Valley, suggesting a shift in perspectives.

Conclusion:
Thiel and Kristol conclude that recognizing the current state of technological stagnation may be the first step towards finding a way out of it. They suggest that acknowledging the “wandering in the desert” of limited innovation for over 40 years could lead to the necessary changes and breakthroughs.