AI 2041: Ten Visions for Our Future | Kai-Fu Lee

National Committee on U.S.-China Relations
5 Oct 202161:26

Summary

TLDRIn a thought-provoking discussion, Steve Orleans, President of the National Committee on U.S.-China Relations, interviews AI expert and venture capitalist Kai-Fu Lee about his book 'A.I. 2041', co-authored with Chen Quifan. The book presents ten science fiction stories illustrating the potential of AI, each followed by an analysis of its plausibility and societal impact. Lee emphasizes the importance of understanding AI's capabilities and risks, suggesting that storytelling is a powerful educational tool. He discusses the future of work, the potential for AI to reduce routine jobs, and the need for retraining and new forms of social contribution. The conversation touches on the U.S.-China relationship in the context of AI, the threat of autonomous weapons, and the role of 5G in advancing AI applications. Lee also addresses concerns about AI bias, suggesting that with careful development, AI could be less biased than human decision-making.

Takeaways

  • 📚 The book 'A.I. 2041' by Kai-Fu Lee and Chen Qifan combines science fiction stories with non-fiction analysis to explore the future of AI and its impact on society.
  • 🤖 AI has the potential to automate a significant portion of routine work, which could lead to job displacement and necessitate a focus on retraining and income redistribution.
  • 🚗 Autonomous vehicles, once refined, are projected to significantly reduce road fatalities, but society will need to grapple with the moral implications of AI errors leading to accidents.
  • 🌐 The widespread use of 5G and future 6G technology will enhance AI capabilities, particularly in fields like telemedicine and remote operations, potentially saving lives.
  • 📉 As AI takes over more jobs, there will be a shift in value towards service jobs that require a human touch, which AI cannot easily replicate.
  • 🚨 The threat of AI misuse is not only from state actors but also from non-state actors, such as terrorists, who could use affordable technology to cause harm.
  • 📈 China is positioning itself as a leader in AI development, which has implications for global competition and potential cooperation in AI research and governance.
  • 🌍 The book suggests that global cooperation is necessary for regulating technologies like autonomous weapons and that the U.S. and China, as major technology developers, should work together.
  • 💰 The concept of 'Moolah' in the book is a speculative idea where people are rewarded for socially beneficial actions, reflecting a potential future job market where economic incentives shift towards social good.
  • ⚖️ Addressing bias in AI is a complex issue that requires careful data management and ethical considerations to prevent systemic inequality.
  • 📉 The potential for AI to displace workers is a global concern, and while no government has yet implemented a comprehensive safety net, the issue is likely to become more pressing as technology advances.

Q & A

  • What is the title of the book that Kai-Fu Lee and Chancho Fan have written?

    -The book is titled 'A.I. 10 Visions for Our Future, 2041'.

  • How does Steve Orleans describe the book's approach to educating about AI?

    -Steve Orleans describes the book as using compelling science fiction stories related to AI, followed by realistic explanations, to educate readers about AI in an engaging way.

  • What is Kai-Fu Lee's belief regarding the general understanding of AI?

    -Kai-Fu Lee believes that many people find AI intimidating and complex, but he aims to make it understandable through plain language and storytelling.

  • How did Kai-Fu Lee and Stanley Chen decide on the ten stories for the book?

    -They wanted to cover about 20 technologies and apply them to different industries and parts of the world, mixing these elements together to brainstorm and write the stories.

  • What message does the book convey about U.S.-China relations?

    -The book suggests that despite not focusing specifically on U.S.-China relations, it paints a picture of a world where cooperation between countries is essential, especially in regulating technologies like autonomous weapons.

  • What are some areas where Kai-Fu Lee believes cooperation between the U.S. and China should be limited?

    -Kai-Fu Lee believes that areas related to national security or defense, such as the development of autonomous weapons and quantum computing, are areas where each country should develop independently.

  • How does Kai-Fu Lee perceive the current direction of both the U.S. and Chinese governments regarding data and technology?

    -He notes that both governments seem to be moving towards more restrictions on data and technology, which could potentially escalate and become counterproductive.

  • What does Kai-Fu Lee think about the threat of non-state actors in the misuse of AI?

    -He believes that the threat from non-state actors is significant and possibly more dangerous than state actors due to the lower barriers to entry for using technologies like drones.

  • How realistic does Kai-Fu Lee consider the 'quantum genocide' scenario depicted in the book?

    -While the scenario is speculative, Kai-Fu Lee considers it more realistic than ever before due to increased access to AI and drone technologies by individuals.

  • What is Kai-Fu Lee's perspective on the impact of 5G on the misuse of AI technologies?

    -He acknowledges that improved communication technologies like 5G can enable both positive and negative applications of AI, including the operation of drones.

  • How does Kai-Fu Lee envision the future of work with the advent of AI and robotics?

    -He predicts that routine human labor will be largely replaced by robots within the next 20 years, leading to a need for job rotation and retraining for new skills.

  • What is the concept of 'Moolah' introduced in the book?

    -Moolah is a digital system for measuring social contributions and encouraging service jobs that involve human connection, which are less likely to be replaced by AI.

Outlines

00:00

😀 Introduction and Book Endorsement

Steve Orleans, president of the National Committee on U.S.-China Relations, introduces the webinar and expresses his excitement for discussing Kaifu Lee's book, 'A.I. 10: Visions for Our Future, 2041.' He emphasizes the importance of storytelling in education and praises the book's ability to make AI accessible and understandable to a broader audience.

05:01

🌐 Global Impact and U.S.-China Cooperation

The discussion shifts to the implications of AI on U.S.-China relations. While the book is not specifically about this topic, it highlights the necessity for global cooperation, especially in areas like autonomous weapons regulation. The conversation touches on the potential for technological collaboration between the U.S. and China, as well as current political and trade tensions.

10:02

🚀 AI and National Security

Kaifu Lee and Steve Orleans delve into the relationship between AI and national security. They discuss the potential for autonomous weapons and the importance of international regulation. Lee suggests that while some areas of AI should be developed independently for security reasons, civilian applications should be a focus for international cooperation.

15:04

🤖 AI in Warfare and the Threat of Non-State Actors

The focus is on the potential misuse of AI, particularly by non-state actors. Lee warns of the dangers of accessible autonomous weapons and the potential for terrorist groups to use AI-enabled drones. He suggests that the threat from rogue actors may be more significant than that from states due to the lower barriers to entry.

20:04

🚨 Real-world AI Applications and Concerns

Lee discusses real incidents involving AI, such as drone strikes and assassinations, indicating that the scenarios depicted in his book are not far from reality. He also addresses the role of communication technology, like 5G, in facilitating the misuse of AI and the potential for AI to save lives in hazardous environments.

25:07

🏥 AI in Healthcare and Automation

The conversation explores the impact of AI on healthcare, with Lee predicting significant advancements in robotics and AI that will transform the industry. He suggests that AI will eventually outperform human capabilities in areas like diagnostics, leading to improved patient outcomes and reduced costs.

30:07

🚗 Autonomous Vehicles and Regulatory Challenges

Lee and Orleans discuss the potential of autonomous vehicles to save lives but also the regulatory and ethical challenges they present. They consider how society might respond to the initial mistakes made by AI-driven cars and the need for a proactive debate on the issue.

35:09

📈 AI and Economic Shifts

Lee explores the broader economic implications of AI, suggesting that as AI takes over routine jobs, there will be a need for a job transition and income redistribution. He also introduces the concept of 'Moolah' from his book, a digital currency earned through socially beneficial actions, as a potential solution to the changing job market.

40:12

👥 AI and Social Interaction

The discussion considers the irreplaceable nature of human service jobs and the potential for AI to enhance, rather than replace, certain professions. Lee argues that high-end service providers will become even more valuable as AI takes over routine tasks.

45:12

🌟 The Future of Translation and AI

Lee addresses the future of translation in the age of AI, noting that while high-end translation services may remain in demand, business translation is increasingly being automated. He predicts significant job displacement for translators and other professionals as AI technology improves.

50:14

📉 Inequality and AI's Role in Society

The conversation concludes with a discussion on the potential for AI to exacerbate social inequalities. Lee acknowledges the issue but suggests that with careful programming and data management, AI can be made less biased than human decision-making.

Mindmap

Keywords

💡AI

Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. In the video, AI is the central theme, with discussions ranging from its capabilities, potential dangers, to its impact on future societies as depicted in the book 'A.I. 2041'.

💡Quantum Computing

Quantum computing is a form of computing that uses quantum bits or qubits to perform operations on data. It has the potential to solve complex problems much faster than classical computers. In the script, quantum computing is mentioned as a significant technological advancement that could have profound implications for computing and security.

💡Autonomous Weapons

Autonomous weapons are systems that can independently select and engage targets without human intervention. The video discusses the potential dangers of such weapons, especially in the hands of non-state actors, and the need for international cooperation to regulate them.

💡Globalism

Globalism is the state of the world being interconnected and interdependent in terms of trade, culture, and communications. The script emphasizes the need for increased global cooperation and trust, especially in the face of technological advancements that affect all countries.

💡5G Technology

5G is the fifth generation of mobile networks, offering faster speeds and more reliable connections compared to previous generations. The script mentions 5G as an important element for the operation of AI technologies, particularly in the context of drones and remote operations.

💡AI Superpowers

The term 'AI Superpowers' is used in the context of the video to describe the transformative abilities of AI and its potential to significantly alter the way we live and work. It is also the title of a previous book by the guest, which explored the impact of AI on the world.

💡Rogue Actors

Rogue actors refer to individuals or groups that operate outside the norms of the state or recognized institutions, potentially causing harm or disruption. In the video, the concern is raised about the misuse of AI by such actors, highlighting the need for regulation and oversight.

💡National Committee on U.S.-China Relations

This organization is mentioned in the script as the host of the discussion. It is dedicated to understanding and improving the relationship between the United States and China. The video touches on the implications of AI advancements for this bilateral relationship.

💡Sinovent

Sinovent is a venture capital firm that invests in startup companies, as mentioned in the script. It serves as an example of the type of organization that can drive technological innovation and investment, particularly in the context of AI and startups.

💡AI Bias

AI bias refers to the tendency of AI systems to make decisions based on biased data, which can lead to unfair or discriminatory outcomes. The video discusses the importance of addressing AI bias to ensure fairness and equality in AI applications.

💡Universal Basic Income (UBI)

UBI is a concept where every citizen receives a set amount of money from the government regardless of their income or employment status. The video mentions UBI as a potential solution to job displacement caused by AI and automation.

Highlights

Steve Orleans, President of the National Committee on U.S.-China Relations, introduces the discussion on AI's future.

Kaifu Lee, co-author of 'A.I. 10 visions for our future, 2041,' joins the conversation to discuss the potential of AI.

The book combines science fiction stories with non-fiction analysis to make AI more accessible and less intimidating.

Lee emphasizes the importance of understanding AI's capabilities, potential dangers, and solutions through engaging storytelling.

The book covers a range of AI technologies and their applications across different industries and global regions.

Lee discusses the need for global cooperation, particularly between the U.S. and China, on AI governance and autonomous weapons regulation.

The potential areas of AI cooperation and limitations due to national security concerns are debated.

Lee predicts increased restrictions on data and AI-related acquisitions could lead to a decoupling of global AI development.

The threat of non-state actors misusing AI for autonomous weapons is highlighted as a significant concern.

Lee suggests that the misuse of AI technologies for nefarious purposes is more likely from individuals rather than states.

The role of 5G in enhancing AI capabilities and the potential risks associated with its widespread use are discussed.

Lee forecasts that AI and robotics will significantly reduce routine human labor, leading to a shift in job markets.

The ethical considerations of deploying AI in sensitive areas like healthcare and autonomous vehicles are examined.

Lee proposes the concept of 'Moolah' as a digital currency earned through socially beneficial actions.

The potential impact of AI on demographic challenges, such as China's aging population, is explored.

Lee discusses the current state and future of AI in translation services, suggesting significant job displacement in the future.

The issue of AI bias and the need for careful data management to prevent systemic inequality is addressed.

Lee and Orleans debate the different cultural attitudes towards privacy and data sharing between China, the U.S., and Europe.

The impact of GDPR on AI development in Europe and its potential influence on global AI policy is discussed.

Transcripts

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okay well let us reward the people who

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are prompt and the many

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thousands of people who will view this

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after we've done this program but i am

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steve orleans president of the national

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committee on u.s china relations and i'm

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thrilled

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absolutely thrilled to be joined by

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kaifu lee my old friend

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um and i'm even more thrilled to have

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read this extraordinary book

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a.i

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10 visions for our future

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2041

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which kaifu and chancho fan have

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written and recently translated into

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english one of the great things about my

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job is i get to read books by friends

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and colleagues

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and this one was really a pleasure i

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blew more than a pleasure it was

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absolutely enthralling

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um

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more

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you know at the national committee what

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we often try to do is find ways to

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educate people and what i'm frequently

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telling

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my colleagues chinese officials american

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officials is you educate through story

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that you tell a story that delivers a

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message and then you explain the message

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that it's really a terrific political

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technique on how to educate

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and what kaipu has done with this book

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is

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and with

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uh mr chun

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who wrote the

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fiction part of it and kai who wrote the

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non-fiction part of it is tell these

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absolutely compelling

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science science fiction stories related

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to a.i

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and then kaifu explains is this

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realistic is this not realistic um how

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does it work it it's you know i loved ai

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superpowers his former book his his late

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his last book which was on the new york

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bestseller the new york times

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bestsellers list uh but this one is

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really compelling if anyone on this

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has not read it yet

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read it it is truly a

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wonderful experience one

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which for me who doesn't know much about

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ai it really educated me about ai and

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what we should think about looking into

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the future so i've always been an

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admirer of kaifu now even more so even

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more so i won't go over you know he's

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currently we won't go over his bio

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because we talked about all the awards

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and all the things

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that he has done we wouldn't have time

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uh for the program but he is the ceo of

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sinovent

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synovation ventures

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um and as everybody knows his story from

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ai uh super powers started out at

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carnegie mellon was it google microsoft

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other companies and then started

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cynovase which invests in startup

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companies so kaifu

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um i've given a big pitch for the book

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this is this is the cover

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um

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tell me it was so imaginative how did

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you come up

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with the idea

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of kind of combining

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fiction

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with ai

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analysis well thank you steve uh for for

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having me on this uh uh webinar

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uh the idea is that i i believe is

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incredibly important for everyone to

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understand what ai is and is capable of

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and its potential dangers and how to fix

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them and and yet many people find ai

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intimidating because it seems like as a

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rocket science but but it really isn't

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so i tried to explain it in plain

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language in ai superpowers i think i had

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some limited success and people told me

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they and they thought they understood

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some of ai actually with me explaining

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it

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in a non-fiction

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but then still people were intimidated

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so i thought well the only way to get

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people to truly understand ai

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is through

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entertaining and engaging

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storytelling which i personally cannot

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do so i reached out to my friend um chen

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chilfan also known as stanley chen

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to ask if he would write the stories and

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and he uh kindly agreed uh it is rather

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uh unusual that a science fiction writer

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who's used to

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let the imagination run wild

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was willing to constrain his imagination

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to what i paint as feasible

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and unfeasible and only write about

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what's feasible in the next 20 years but

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he's done an amazing job and hopefully

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the book delivers the engaging

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aspect and draws people in who otherwise

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might find ai to be intimidating and and

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who might have been misinformed about ai

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who can now get hopefully the right

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picture and after each story

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i give an explanation of the technology

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what the canon cannot do the problems it

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might introduce on society and how we

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might deal with it so that's how it came

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about and how did you arrive at the ten

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stories and you know the different

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kind of aspects of ai that must have

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been difficult because you could think

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about five thousand

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yeah

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it was um it was a puzzle we're putting

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together a puzzle i wanted about 20

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technologies covered from natural

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language processing to quantum computing

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um to

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drug discovery i wanted about 20

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technologies covered and

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i wanted to see them covered from easy

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to hard and i wanted to see them covered

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applied to different industries like

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entertainment

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communications healthcare

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and

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work uh and uh etc so so that was my

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puzzle and then stanley introduced

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another puzzle he wanted to

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have 10 stories take place in 10

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different parts of the world

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uh partly to make the stories more

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interesting and partly to show that this

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will impact all countries and all

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industries so we mix these four puzzles

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together and then we brainstorm possible

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uh story lines and then um uh and then

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he went off and and wrote the stories

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and then i wrote the commentary that's

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how the puzzle came together we didn't

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quite cover every technology there were

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a few

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we wish we could get in but the puzzle

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just didn't didn't fit

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now it's because we're the national

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committee on u.s china relations um and

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our audience are basically people who

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are looking at the u.s china

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relationship what is the book

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what is the message the book conveys

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about u.s china relations

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uh this book isn't in particular about

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u.s china but it paints a world in which

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we really need to work closely together

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under more not less globalism with more

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not less trust between countries because

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our fates is very linked

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for example

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autonomous weapons can only be

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regulated with uh cooperation from

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countries

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and

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many of the governance ideas

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can can become universal if people come

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to a common understanding

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and and also

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technology advances were driven by china

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and u.s

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and

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the scientists ought to work together

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fortunately they still do so those are

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some things one could read through the

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stories

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um and and also

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uh in some of the background it is

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clearly still portraying that

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technologies coming from u.s and china

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are the two most significant

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technology superpowers that will

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continue in 20 years so these are the

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subtle aspects one could find in the

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book but it's really not prominent

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which areas

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should the united states and china with

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respect to aib cooperating which ones

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should cooperation be limited and which

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ones can we really not cooperate on i

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mean i hear discussions in washington

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that quantum computing is just we should

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not really be cooperating in that

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because it can be there's too many uh

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there's too much military applicability

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there so how do you kind of divide those

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areas

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right

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um i i think

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ai as a general omnius technology deep

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learning extensions uh

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including uh

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some of the more recent advances beyond

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deep learning are pretty universal they

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the the papers are published even with

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source code and data

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and

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the chinese european american scientists

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are already working together and then

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the technologies are already applied to

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industries so um so i think that is uh

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the the horse has left the barn and and

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it's becoming omni use applied to

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industries uh more cooperation i think i

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think would be very suitable

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there are obviously

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civilian and non-civilian applications

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but the cooperation on civilian which is

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a much larger part i think canon should

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go on

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specifically

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the use of ai in climate in uh

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healthcare ought to be less

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controversial and potentially uh the use

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for uh profit making for for for use in

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financial industries and other

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industries i think could also span

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multiple countries

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uh i think both countries will assert

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that

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on technologies that

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relate to national

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security or defense that's an area where

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each country should develop its own and

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probably uh you know europe and russia

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will also want to develop their own

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and um i think

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autonomous weapons the development of

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that um should either be should i think

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will happen independently but they

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should be regulated working together

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and i think quantum computing i can see

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the logic of why

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having a quantum supremacy is important

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to many countries and

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because i think quantum computing uh

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basically changes the paradigm of

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computing and makes possible

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things like breaking computer security

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figuring out uh extremely fast

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communications uh completely disrupting

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the type of every algorithm from ai and

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and

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and so on so i i think i can see

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uh countries wanting to be

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superior in quantum and and it's not a

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technology that i think people are

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inclined to work together with other

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companies companies are doing it

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and i think each company and probably

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each country views it as an expensive

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endeavor that would give it an advantage

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in a disruptive future direction so i

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think i i would understand understand

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that one

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and there are probably other

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basically the question i think is if

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it's really legitimately related to

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national defense

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uh and security i think it's

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understandable that cooperation be

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limited everything else i would hope for

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more cooperation

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aren't we seeing

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[Music]

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both governments

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if i agree with you i'm a hundred

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percent in agreement with you we should

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find ways to cooperate but aren't we

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seeing both governments actually move in

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the opposite direction more restrictions

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on data

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blocking of

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chinese acquisitions of companies in the

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united states that have access or

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are a a bank for health care data for

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individuals data

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dating apps um

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you know obviously the the

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you know dd

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you know having certain data and that

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actually the walls

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rather than getting lower

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are getting higher what i've always

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argued for is defining national security

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narrowly and building those walls very

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high but for the other things don't have

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walls at all

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yeah i agree with you

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uh i think if we trace back on how this

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began

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i think it was under president trump

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that went after a number of these

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aspects

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i don't want i don't i'm not an expert

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on which of the policies are legitimate

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which are questionable but i think

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uh china's i think the chinese

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government's preference would have been

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to continue globalism china clearly has

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been a beneficiary and cannot contribute

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but

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i think seeing some of these

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companies that have been put on entities

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list with export control cepheus and the

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frequency and the degree of the

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application of these um

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measures are making china feel that it

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needs to be self-sufficient in

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technologies otherwise

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every company could follow the path of

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huawei of being

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limited in its access to necessary uh

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infrastructural technologies so yes in

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recently china has been

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extending its regulation too it is kind

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of a

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symmetrical escalation which is

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unfortunate and i hope there will be

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some de-escalation otherwise this will

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probably get worse not better

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yeah

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the national committee runs what are

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called track two dialogues and one of

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them is actually on the digital economy

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and our hope is to be able to propose to

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both governments some rules of the road

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where we don't have this continuing

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expansion of restrictions because

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ultimately these expansions of

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restrictions take the dream of ai and

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the good things that it can do and it

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impedes the realization of that dream

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you know i know the book's not about u.s

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china relations but the chapter it was

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interesting the chapter on um a quantum

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genocide which was you know riveting i

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mean i i was late for an appointment

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because i was reading

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it was the fiction part not the

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analytical part

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but

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it's about it's about rogue actors

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and

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is it fair to say the greatest threat

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of the misuse of ai is actually not from

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state actors but from rogue non-state

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actors

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uh

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i it's hard to say which is

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larger but uh yeah i would i would tend

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to agree

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uh because that's the difference with

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let's say nuclear weapons

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while that's incredibly

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dangerous it is only a few countries

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that have it and they can hopefully

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negotiate treaties and regulations and

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and control themselves and

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due to deterrence and

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some degree of trust etc

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because states i think generally

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speaking are much more trustworthy than

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than non-state actors so the big danger

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for autonomous weapons is that the cost

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of building one can be very low like a

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thousand dollars

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equip equipping a

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drone with facial recognition and gps

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and uh and a little bit of dynamite then

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it becomes an assassination machine that

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flies a very fast speed very small very

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difficult to catch and shoot someone

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point blank

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and and the other danger is that the

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terrorists do not have to sacrifice

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their lives unlike the uh the the

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suicide bombers who do so this lowers

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the barrier the cost is lower and also

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one could a terrorist group can send a

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swarm of these

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so so i think that slowers the cost of

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terrorism

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and increases their

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uh

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lethality so i i do think it is much

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more dangerous and in fact i'm

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i think i think any day now we're going

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to see some such activities and

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people are in

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countries actually generally not taking

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this seriously enough and it's going to

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take another autonomous weapon terrorist

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group 9-1-1 like event that i think will

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wake everyone up

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yeah

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how realistic by the is is the

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quantum genocide

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kind of

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fiction part you know where this

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effectively a mad scientist you know

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whose life has been ruined

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you know kind of takes over

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uh i i think it's higher than ever

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before

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because you know with unabomber is the

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the the characters was built on

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unabomber but unabomber is um

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deranged but and and smart but but not a

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deep scientist so so nowadays many more

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people have access to these ai

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technologies and the drone technologies

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and and can program them

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uh so i think that is more realistic

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than ever more dangerous than ever the

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part about that that

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character uh becoming the first person

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to invent the quantum computer and uses

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the quantum computer to do bad things

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that's much more speculative

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obviously it's really the national

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laboratories and the ibms and googles

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that really are likely to make the big

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break in quantum

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and and and those large companies and

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large national laboratories are not very

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likely to have such a deranged person at

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the top

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yeah

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you know um

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i think it was trump used to joke he

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said we don't know if this is a state or

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a fat guy sitting in the in the basement

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who's hacking into stuff and trying to

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do all this so the question you know

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how

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do you need states to be behind this or

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is it possible for kind of

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literally the mad scientist to you know

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use ai to accomplish very nefarious

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objectives

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i i think the mad scientist can do it

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and depends on what bad things are being

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done

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if it's really to build a small number

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of killer drones or slaughter bots i

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think even uh even an advanced hobbyist

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could build that don't you really need a

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deep scientist

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so

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so that's why i think the danger is

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becoming greater and greater because the

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barrier to building ai

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is lower and lower more and more people

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every year

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can program ai and do good things and

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also do bad things

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yeah

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you know it was interesting as i was

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reading the book um you know there were

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two

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major incidents involving ai

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one was

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the alleged assassination by israel

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of the leading nuclear scientist the

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person trying to create a nuclear weapon

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in iran

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who apparently a uh

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a machine gun was placed which was

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operated fully by ai

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and the other was the sad

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action by the united states to have a

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drone strike on a car

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where the intelligence apparently

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was faulty

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one of those are we very close to to

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kind of what you know you say 2041 but

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is it this is 202 one

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sounds like you're getting pretty close

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i think we're pretty close

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there's also i think then attempted

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assassination on the venezuelan

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presidents and also the alleged strike

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on the saudi oil fields by

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iran

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and all of those

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half drones playing a role there are two

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types of drones

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in most of these cases

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very sturdy

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military-grade drones were used and

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those are very high expensive and still

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out of reach by terrorists because

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they're not acquirable commercially but

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i think the venezuelan president

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assassination i think that was using

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more of a standard hobbyist drone i i'm

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not certain but

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but those can be equally lethal today so

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i i do think in the next

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three years we will see

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these killer drones uh do something

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terrible and

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and then we'll wake up and start reading

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all these papers that various people

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wrote the part my book

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autonomous weapon the section was

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excerpted and and published in the

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atlantic

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and there are other people who have

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written

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a thousand several thousand ai

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scientists uh along with the late

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stephen hawking elon musk have written a

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plea that

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that government should look at the

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regulation or perhaps spanning of

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autonomous weapons but it's all fallen

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on deaf ears and

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and i'm afraid it's going to take a a

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terrible uh um

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atrocity that will uh wake people up

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what is the widespread use of 5g going

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to affect this

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oh

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certainly communications is

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a an important element for any

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misuse of ai technologies

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um

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right uh yeah of course positive and

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negative uh that the drones wouldn't be

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able to operate

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if they couldn't use the gps element for

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example and the 5g

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but that's already i think a um

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a reality it is the way it is yeah so

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and i think going on to 6g

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it will even enable other types of

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things

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um

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i saw and when i was

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watching a demonstration of 5g

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um

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[Music]

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i was in shanghai and they they showed

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um

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a

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mechanical arm mining rare roof

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i think in guijo or something something

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where

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[Music]

play23:21

years ago

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um

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miners would have died

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now it's just a machine and they can lit

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and they obviously you know it's a

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thousand miles 1500 kilometers and they

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could sit there and the 5g was so

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perfect

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that they could mine

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them operate accordingly i mean isn't

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and that's obviously all ai and a

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combination of ai and 5g it was it was

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one of the most

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you know it really brought home to me

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the lives that could be saved

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by ai

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uh yeah absolutely in a dangerous

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situations in mines or

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accidents or fires

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robotic technologies can be life-saving

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and the way robotic technologies are

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likely to develop is first in

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extreme conditions where people are

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willing to pay a very high price such as

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these

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and then moving into the factories and

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then within factories there will be

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smart forklifts smart

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autonomous vehicles smart arms that can

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grasp any object and then that will be

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refined by use at the high price

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paid by the manufacturing companies to

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basically

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replace routine work by people

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and then the technology will become

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cheaper than adopted in the camera in

play24:46

commercial in commercial applications

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like restaurants and malls and then it

play24:50

will come to our homes and become great

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household helpers so so that's something

play24:57

we can look at a 20-year horizon and and

play25:00

see pretty much all of the routine human

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labor will be doable by um by robots and

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i think that will be one of the big

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advances and it will free up a lot of

play25:10

our time so the the positive benefits

play25:13

are are definitely much larger

play25:16

yeah

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now in the holy driver

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um you know you talk about you know

play25:22

autonomous vehicles and you know the use

play25:24

of ai and it's this i mean i want to

play25:27

ruin the ending you know how how lives

play25:29

could be saved this way but you also

play25:31

then in the analytical part you talk

play25:33

about

play25:34

uh are people

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will the regulatory apparatus be willing

play25:40

to deal with

play25:44

the general

play25:45

savings of life so you will have the

play25:47

data will show we save lives but there

play25:50

will be an instance or two or five or

play25:54

ten where someone dies as a result how

play25:56

does that get resolved

play25:59

and is that something where china is

play26:01

able to look

play26:03

at the broader data

play26:05

whereas

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democracies

play26:08

can't

play26:11

it's possible um yeah the specific

play26:14

issue that steve you were talking about

play26:16

is ai gets better with data so

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if you allow an autonomous vehicle to

play26:22

launch

play26:23

and it will

play26:24

certainly make mistakes but maybe we

play26:27

don't allow to launch unless it drives

play26:29

roughly as well as people maybe a little

play26:31

better i think that is feasible then it

play26:34

will gather more data

play26:35

and then in another month a new software

play26:38

will be sent to all the vehicles and

play26:41

then it will drive better much better

play26:43

than people and and then in a year five

play26:46

years ten years uh it will become so

play26:49

much better

play26:50

at driving than people because it's seen

play26:53

you know billions of miles and no human

play26:56

has ever seen that

play26:57

uh and it's it's a honed to a perfect

play26:59

driving capability also the autonomous

play27:02

vehicles can talk to each other and just

play27:04

miss each other by an inch and humans

play27:06

cannot have that precision

play27:08

and also

play27:10

a autonomous vehicle that might be

play27:12

having trouble like a blown tire can

play27:14

broadcast to nearby cars to stay away

play27:17

from me and humans can't respond in that

play27:19

kind of a split second uh

play27:22

accident or issue

play27:23

so uh it's very clear that uh in let's

play27:27

say given 10 years from launch to 10

play27:30

years autonomous vehicles ought to save

play27:34

90 percent

play27:35

of the lives lost on the road today this

play27:38

is this is a scientifically estimated

play27:41

projection by mckenzie so the question

play27:44

is what if

play27:46

we launch it

play27:47

and it's uh yet many people die because

play27:50

of it uh not more people died than human

play27:53

drivers are we willing to say we'll

play27:56

launch the product when it's as good as

play27:58

human

play27:59

uh

play28:00

and the autonomous vehicle will make

play28:01

mistakes uh there will be people who get

play28:04

hit and who die uh not worse than people

play28:07

but different people

play28:09

and then over

play28:10

time it gets better

play28:12

is that the price we're willing to pay

play28:14

so i think different people and

play28:16

different governments will thrill

play28:17

differently

play28:18

and and we'll see how that plays out but

play28:21

uh i would bet many countries perhaps

play28:24

including china would feel at a ten-year

play28:26

horizon that's a good thing and at no

play28:29

given moment in time is it worse than

play28:31

people then it's something we could look

play28:34

into one could also extrapolate on

play28:36

robotic surgeries on doctors who

play28:39

diagnose patients

play28:41

similar issues with human lives will be

play28:43

involved

play28:44

so so i think we should go in with our

play28:46

eyes open and have the intellectual

play28:48

debate now

play28:50

ai

play28:52

is going to make fewer mistakes

play28:54

an ai radiologist is going to make fewer

play28:57

mistakes than the best radiologist in

play28:59

the world

play29:00

because

play29:02

the best radiologist maybe he's seen a

play29:05

hundred thousand but the ai has seen

play29:08

a hundred million

play29:10

right so they will simply make fewer

play29:13

mistakes so and so no one should suffer

play29:16

from that

play29:17

transition

play29:18

to

play29:19

mediology

play29:21

i i don't know i don't know because the

play29:23

problem is when ai makes the mistakes

play29:26

many of those mistakes look silly to

play29:28

people and actually look ridiculous

play29:30

and and it could be viewed as uh

play29:33

irresponsible how could you launch a

play29:35

product like that that is so pretty

play29:38

immature for example when tesla

play29:41

for the first tesla accident that killed

play29:43

the driver using autopilot the tesla saw

play29:47

a giant white truck

play29:50

and the reflections as sky and it drove

play29:53

right into the truck i would say

play29:55

probably no human driver would ever make

play29:57

that mistake and people are shocked and

play30:02

angry that how could tesla launch such a

play30:04

ridiculous product but if you look at

play30:06

the track record of autopilot it's

play30:09

actually driven

play30:10

safer than people in terms of total

play30:12

fatalities but when it makes a mistake

play30:14

it's a ridiculous unforgivable mistake

play30:18

that i think is the dilemma i will be

play30:20

facing wow that's that that is uh

play30:25

that is fascinating that that is that is

play30:28

fascinating um

play30:30

you've talked about kind of the the and

play30:33

the book talks about this in various

play30:35

places that you know and especially in

play30:37

the chapter on plenitude so ai is able

play30:40

to kind of reduce the amount of time we

play30:42

need to do things things are able to be

play30:45

produced less expensively so they're

play30:47

more broadly distributed money becomes

play30:49

less

play30:50

less important

play30:52

two questions on that one is china is

play30:55

confronting

play30:56

um a demographic challenge which we talk

play30:59

about a lot of the at the national

play31:01

committee its workforce has already

play31:03

peaked it's reducing its population is

play31:06

on the verge of peaking is ai going to

play31:09

solve that problem for china

play31:12

uh the problem of population not growing

play31:16

or the population

play31:18

yeah population not growing you know

play31:21

generally population not growing would

play31:23

lead to reductions in gdp that

play31:26

population growth is generally one of

play31:28

the ways that pdp will grow

play31:31

right right

play31:32

i'm probably somewhat contrarian on this

play31:35

view so i'll answer it but i would say

play31:37

many people would disagree with me

play31:39

i feel with

play31:41

aiona robotics taking over so much

play31:44

routine work

play31:45

countries that grow too much in

play31:47

population may not see

play31:50

the historical

play31:51

correlation with

play31:53

gdp growth anymore

play31:55

and in in that case

play31:58

countries like india may be facing more

play32:00

of a challenge than countries like china

play32:03

in terms of the population growth uh

play32:05

there are obviously a lot of smart

play32:06

people who disagree on that so we'll

play32:09

have to see how it plays out in my

play32:11

opinion

play32:13

if we believe ai over the next 20 years

play32:15

will displace 50 percent of human

play32:18

human work which is routine

play32:21

and that means there will be a large job

play32:23

rotation huge issue with

play32:26

redistributing income to the people who

play32:28

lost their jobs and a big problem in

play32:31

terms of retraining people for skills

play32:34

that

play32:35

are not easily replaced by ai and the

play32:38

individual is capable of being trained

play32:41

and learning that new skill

play32:43

i think that is a a set of challenges i

play32:46

feel would be of a highest priority

play32:50

we're seeing the very beginnings of that

play32:52

not enough sign to worry any

play32:55

governments or politicians yet but i

play32:58

think it it may get worse especially as

play33:01

covid um

play33:02

is is we get out of covid yet

play33:06

companies may not be hiring people back

play33:09

and maybe using automation

play33:11

we might see a a jump but but that's

play33:14

something i'm i believe i believe will

play33:16

happen one day and uh but we have to see

play33:19

the data to to uh to validate that

play33:22

yeah certainly in the healthcare sector

play33:25

we're using much more robotics

play33:27

uh much more intelli you know

play33:30

telemedicine that we've seen a shift

play33:33

which i would have thought probably

play33:34

would have taken 20 years has occurred

play33:37

in 18 months

play33:38

and and there's no question it will also

play33:40

reduce

play33:41

reduce employment and in in

play33:45

in your chapter and plenitude you talk

play33:47

about

play33:48

the need to retrain

play33:50

people right you know and government

play33:53

taking over that responsibility the um

play33:57

you have this window also in plenitude

play34:00

you talk about moolah

play34:02

which is

play34:03

the new money which you you collect by

play34:05

doing good deeds

play34:07

um

play34:08

so two questions one

play34:11

does this kind of does this in your mind

play34:13

stem from china's social credit system

play34:16

that is beginning to

play34:18

take hold in china you know that people

play34:21

if they don't visit their parents they

play34:23

they lose credit you know if they

play34:25

jaywalk they lose credit but if they do

play34:27

good things for science society they

play34:29

gain credit so is that related and then

play34:32

the second kind of subsidiary question

play34:35

is

play34:35

is china's central bank digital currency

play34:38

some step in that direction making all

play34:41

current you know getting rid of paper

play34:42

money

play34:45

uh

play34:46

actually those were not my inspirations

play34:49

uh the the social credit system and the

play34:52

central bank system uh but clear the the

play34:55

reason i decided to put that in the

play34:57

story it's a very speculative direction

play35:00

of course i can't

play35:02

prove that is the direction we must go

play35:04

it's more motivated by my belief that

play35:09

work for economic gains

play35:11

will

play35:13

become more diminished that is we if we

play35:17

only had human jobs and professions

play35:20

for

play35:21

for for for work that will have an

play35:24

economic benefit to the society we won't

play35:27

have enough jobs for everyone because ai

play35:30

will have taken over so much of it

play35:33

uh and and yet if we think about what

play35:36

humans can do that ai cannot do

play35:39

uh obviously there's creativity there's

play35:41

you know your job my job the ceo's job m

play35:45

a expert's job scientist job yes there

play35:47

are those but this is a small percentage

play35:49

what is the large

play35:51

number of

play35:53

existing

play35:55

lower middle class people going to do

play35:57

when ai takes over all the routine job

play36:00

so my thoughts that i began to express

play36:03

in ai superpowers that went into ai

play36:06

2041 is that

play36:08

it is really service jobs that will not

play36:11

be replaceable by ai because the human

play36:15

connection required because as as

play36:18

everything becomes cheaper people want

play36:20

to pay a premium for services for a

play36:23

wonderful masseuse for a great concierge

play36:27

for

play36:28

for a tour guide and for health care

play36:31

services and some of the health care

play36:33

services are not necessarily you know

play36:36

economic requirements that is in elderly

play36:39

care elderly companion

play36:41

someone to take an elderly person to see

play36:44

a doctor

play36:45

or foster home volunteer hotline

play36:47

volunteer

play36:49

someone who decides to

play36:50

to homeschool their children these are

play36:53

all activities worth compensating people

play36:56

for

play36:56

worth calling jobs if you will yet they

play37:00

don't really contribute much

play37:01

economically to society but it gives

play37:03

people something meaningful to do

play37:06

these jobs are create positive social

play37:09

energy it gives people a sense of

play37:12

satisfaction having helped seeing a

play37:15

smile from the elderly person they uh

play37:18

spend time with so there should be

play37:20

encouragement of this type of

play37:23

human to human connection service type

play37:26

of services

play37:27

so it was with this thought in mind that

play37:30

i thought um

play37:32

instead of just encouraging people with

play37:35

a pay they should be encouraged with

play37:37

some kind of um

play37:39

digital system that measures their

play37:42

contributions socially so it was

play37:44

inspired by this not not the other

play37:46

factors

play37:48

the um you know it's interesting i mean

play37:50

some

play37:52

you know you say tour guides

play37:54

i would say tour guides have to some

play37:56

degree already been replaced by a very

play37:59

simplified ai so once upon a time you

play38:02

need somebody to walk you around a

play38:03

museum

play38:05

now you simply put on earphones

play38:08

and when you get to a particular place

play38:11

the

play38:12

museum talks to you with what the tour

play38:14

guide formally said

play38:15

very simple kind of ai

play38:20

yes yes but i think there's also room

play38:22

for a storyteller if tour guide tour

play38:24

guys should compete against that by

play38:27

being a brilliant storyteller

play38:28

incorporating personal experience fun

play38:31

anecdotes things that are very personal

play38:33

and connect human to human

play38:35

um there are still many of those

play38:38

turquoise i hope i hope that could

play38:40

emerge to be uh sufficiently competitive

play38:43

um

play38:46

yeah

play38:47

they're also you know like a chef and a

play38:49

waiter you know we're investors uh in

play38:52

china and there are a lot of companies

play38:54

coming up with robotics chefs and

play38:56

robotic waiters and waitresses and and

play38:59

they're very effective very cost

play39:00

effective i think they will populate uh

play39:03

to middle or lower end restaurants you

play39:06

know maybe like equivalent of denny's in

play39:08

the u.s higher than mcdonald's but not a

play39:11

not a high-end restaurant but then that

play39:14

i think accentuates the value when you

play39:16

go to a a top restaurant a michelin

play39:19

restaurant or maybe something less

play39:21

expensive but still a fancy restaurant

play39:24

people will treasure even more the human

play39:26

service that's provided so i think a lot

play39:28

of things will become multi-tiered at

play39:31

the top will be the human

play39:34

service providers curators and people

play39:37

who deliver an amazing experience and on

play39:39

the bottom will be uh robots taking over

play39:42

the jobs

play39:45

i was in i mean it was a lien yeah it

play39:48

was a uh whatever the unshort band is it

play39:50

was a a chain restaurant but it was a

play39:53

main focus restaurant

play40:04

you pressed what you wanted

play40:06

and you made your order and then i

play40:08

expected the robot to bring the food out

play40:11

but then a person brought the food out

play40:13

so their ai was rather imperfect um i

play40:17

mean their robotics were isn't perfect

play40:19

you know somebody this gets to a

play40:20

question someone has asked which is leo

play40:25

from beijing language and culture

play40:27

university

play40:29

she thinks ai has its limits for example

play40:31

this is an interesting question no

play40:33

matter how advanced ai technologies are

play40:37

professional translators and

play40:39

interpreters are still needed

play40:41

are we exaggerating the potential of ai

play40:44

by thinking that those jobs

play40:46

will get eliminated

play40:50

uh the highest gen well it goes back to

play40:52

the concierge and uh the chef and the

play40:55

waiter uh the same will happen with

play40:58

translators

play40:59

uh the very high-end super you know if

play41:02

you translate for the president of a

play41:04

country or a president of a large

play41:06

fortune 500 company that is unlikely to

play41:09

be taken over by ai in the next 20 years

play41:11

because mistakes are extremely costly

play41:14

and there's a lot of subtlety but

play41:16

business translation is rapidly being

play41:18

taken over by

play41:21

semi-autonomous methods i'll describe to

play41:23

you what is happening today so we're

play41:25

investors in two companies uh one called

play41:28

the transient the other is called lane

play41:30

boat and the two of them are working

play41:32

together one is on a domain specific

play41:35

high quality text translation the other

play41:38

is building a tool for translators and

play41:41

the tool still has people using the

play41:43

tools the people has the final say on

play41:46

what the translation looks like but the

play41:48

ai does the first pass and we're seeing

play41:50

ai improving very rapidly by 12 just in

play41:54

the last year so that means 12 more of

play41:57

the translations don't have to be

play41:58

touched by the human anymore

play42:01

and and we're seeing the overall

play42:03

productivity of the translator pool go

play42:06

up significantly costs come down

play42:08

significantly because ai is doing more

play42:10

and more and more of course the

play42:12

translators feel very empowered because

play42:14

ai is doing all the routine basic

play42:16

translation and the translator gets to

play42:18

tweak a little here and little there but

play42:20

what they don't see is the amount of

play42:22

reliance

play42:24

on their human capacity is coming down

play42:26

over time so we're actually in a very

play42:29

strange time in history right now

play42:31

because

play42:32

i i know you as the person who asked the

play42:34

question is is probably looking at the

play42:37

boom in the human translator space i i

play42:40

do believe in the past year there are

play42:42

more people who get paid by more

play42:44

translator jobs as a result of more

play42:46

people using machine translation and not

play42:49

happy with the result and hiring a human

play42:51

to fix it but this boom is a transient

play42:56

thing and as technology gets better with

play42:58

more data the human reliance and

play43:00

requirement for human will come down

play43:03

it's very much similar to uh

play43:06

bank tellers and atms when when atms

play43:09

first came out it drew people to the

play43:10

bank they had to hire more tellers but

play43:13

eventually atm became more and more

play43:15

powerful and tellers had to be moved to

play43:17

other jobs so i would be quite confident

play43:20

that in a 10 to 20 year horizon the

play43:23

number of professional translators will

play43:24

come down significantly even

play43:27

dramatically and the ones who remain are

play43:29

going to be the ones who are so good at

play43:31

it they're like instantaneous voice

play43:33

translator or extremely high quality no

play43:36

mistake tolerated kind of jobs

play43:40

why is your former employer's uh

play43:43

translation function so mediocre

play43:48

i i i talk when i use it i'm just

play43:51

shocked at

play43:53

because they should have data

play43:56

more data than they possibly

play43:59

can analyze to make their translations

play44:02

more accurate what's going on

play44:05

i don't think they put the state of the

play44:06

art the state of the art requires um a

play44:09

lot more compute power and the number of

play44:12

users who use it and also they make no

play44:14

money from the product so they put a

play44:17

older version but even then if you look

play44:19

at the quality of the product five years

play44:21

ago ten years ago there's been big

play44:23

advances and also in the last just in

play44:26

the last two years there's a huge um

play44:29

advancement almost a breakthrough

play44:32

called

play44:33

self-supervised learning and and if you

play44:36

probably know it by gpt 3 or transformer

play44:39

or birds these are the

play44:41

technologies coming out of

play44:44

google microsoft and openai

play44:47

that allows

play44:48

essentially you know trillions of data

play44:51

to be used for training a super smart

play44:54

natural language engine on top of which

play44:57

you can build machine translation and

play44:59

specif and and also

play45:01

targeted for specific industries like

play45:03

electronics or

play45:05

finance and we are seeing big jump in

play45:08

performance so

play45:09

you i i would be very comfortable

play45:12

predicting that in five years

play45:14

we will have speech recognition

play45:16

dramatically better than they were today

play45:18

even though they're pretty good already

play45:20

will have machine translation

play45:22

both

play45:23

text to text but also a simultaneous

play45:26

voice to voice translation so that you

play45:28

can go to a foreign country with your

play45:30

sets and um have a decent conversation

play45:34

with someone with some mistakes but a

play45:36

decent um fluid conversation it will

play45:39

jump it will jump in the next five years

play45:42

that will be i mean certainly the voice

play45:44

recognition

play45:46

is already

play45:47

you know 99.99

play45:49

when i give speeches in china

play45:52

yeah you know i i see on the sides they

play45:55

have

play45:56

you know a transcription going on if

play45:59

people don't understand my chinese or my

play46:01

english so

play46:03

it's pretty good it's pretty good it's

play46:05

very distracting for the speaker

play46:07

um yes

play46:08

i mean are jobs

play46:11

you know

play46:12

partly because i come from wall street

play46:14

and started out doing credit analysis is

play46:16

that kind of job

play46:19

just going to disappear it's all going

play46:20

to be done

play46:22

by ai because ai

play46:25

is going to be better at judging the

play46:27

borrower

play46:28

with all the data that they have and all

play46:30

the data that they're able to sweep in

play46:32

through ali and 10 cent and in the

play46:35

future for the digital currency that

play46:38

those jobs are going to basically

play46:40

disappear

play46:42

uh

play46:43

yes i think all routine jobs are going

play46:45

to be gone and there are some jobs that

play46:48

you would not think are routine

play46:50

they're going to be gone too

play46:52

for example a radiologist's job one

play46:54

would not think that's routine

play46:56

a translator's job one would not think

play46:58

that's routine but it's all about data

play47:01

huge amounts of data

play47:03

fed through to a mathematical

play47:04

quantitative algorithm and the

play47:07

improvements are just very dramatic and

play47:10

the way that jobs will be displaced will

play47:13

be first ai will come out as an

play47:16

assistant radiologist assistant

play47:18

translators assistant doctors assistant

play47:21

for diagnosis then they will become

play47:23

quite good doing more decisions

play47:26

autonomously then one day will come when

play47:29

the professional will feel wow the ai is

play47:31

better than me i don't dare override its

play47:35

decision anymore and then it's going to

play47:37

flip and take over more jobs i think

play47:40

people really have to be

play47:41

prepared for that we are seeing the

play47:43

writing on the wall as you were

play47:45

describing speech recognition i worked

play47:47

on speech recognition

play47:49

in the 80s and it barely worked back

play47:52

then if you draw a curve of improvement

play47:54

it goes like this especially it actually

play47:56

goes like this in the more last 10 years

play47:58

big jump due to deep learning and its

play48:01

descendants so we really

play48:03

should become prepared for domains in

play48:06

which ai will emerge as an assistant and

play48:09

actually evolve into the main

play48:13

worker

play48:15

the chapter on that you call golden

play48:18

elephant kind of

play48:20

highlights potential inequalities in the

play48:23

use of ai you know with

play48:26

i mean it's so

play48:27

it's so smart it's so interesting

play48:29

because it you know talks about

play48:30

insurance and how if you do one thing

play48:33

you're you know given you've consented

play48:35

to kind of be followed and have

play48:37

everything you do be monitored your

play48:39

insurance premium would jump up or drop

play48:42

down which was which was i think just

play48:44

wonderfully interesting i was going to

play48:46

ask my insurance my friends who

play48:48

insurance companies if they're moving in

play48:50

that direction um but my question is how

play48:52

do we deal

play48:53

with the systemic you know the potential

play48:56

systemic inequality in ai

play48:59

uh yeah today i think the inequality in

play49:02

ai is quite a serious matter and people

play49:04

have to work on it uh fortunately i

play49:06

think we can make a big improvement in

play49:08

the short term

play49:10

uh we've probably read about uh you know

play49:12

a large american company trained this hr

play49:16

ai using more men than a lot more men

play49:18

than women and it ended up being very

play49:20

biased against

play49:22

letting women pass the screen and that

play49:25

kind of error in the imbalance of data

play49:29

that you expose to an ai system so much

play49:32

of one gender or race or whatever and so

play49:35

little of others will cause ai systems

play49:38

to be biased and those can be caught by

play49:41

automatic tools that will alert the ai

play49:43

programmer saying you should not launch

play49:45

this because it will have this kind of

play49:47

an impact so i think we can catch you

play49:49

know 80 90 percent of the most obvious

play49:53

of of the problems because they're

play49:54

pretty obvious mistakes we should also

play49:56

train ai engineers to be conscientious

play50:00

that they're not just trying to build a

play50:02

tool make money but rather

play50:05

they're they're going to impact people's

play50:07

lives so i think we can keep that under

play50:09

control but there are a lot of

play50:11

subtleties that are very hard

play50:14

the golden elephant was particularly

play50:16

written that way

play50:17

there you have a

play50:19

well-intended benevolent insurance

play50:22

company meaning to help people reduce

play50:25

their insurance premium which ought to

play50:27

be correlated with them not getting sick

play50:29

as often seems like everybody wins but

play50:32

yet still terrible things happen so it

play50:35

is pointing out there are extreme cases

play50:38

and a lot more research needs to be done

play50:41

we can capture them obvious cases and

play50:43

make it work much better but the extreme

play50:45

cases require a lot more work

play50:47

i would close on this question by saying

play50:50

if we captured if we do a really good

play50:53

job on the big mistakes i think we will

play50:56

reach a point that ai will be already

play50:59

less biased than people uh we we don't

play51:02

recognize how biased we are

play51:05

um

play51:06

think think about a um some a loan

play51:09

officer at the bank if you ask them well

play51:11

why did you turn down that

play51:12

person's loan you know they'll usually

play51:14

give you a a

play51:16

a legitimate reason

play51:18

insufficient income

play51:19

uh

play51:20

two new at the job or something but

play51:22

buried in that person's um

play51:24

subconsciousness is a lot of bias and

play51:28

prejudice uh you know

play51:30

things like

play51:31

the person doesn't look trustworthy or i

play51:33

don't trust you know men or women or

play51:35

whatever

play51:37

that kind of thing does does come

play51:38

through and ai will we can do such a

play51:41

good job by honing the right data set

play51:44

eliminating biases in the data as much

play51:46

as we can so that ai can and will do

play51:49

better than people another example with

play51:51

people is there were there's a study in

play51:54

israel that showed that judges were gave

play51:58

harsher sentences just before lunch just

play52:01

because they were hungry so it's not

play52:02

even caused by prejudice they're just

play52:04

i'm hungry i'm going to be mean so so i

play52:07

think ai can and will do better and and

play52:10

this doesn't mean

play52:11

we shouldn't work on it we should work

play52:13

very hard on it to make ai as fair

play52:15

unbiased as possible but we should not

play52:18

look at it and say well it's so much

play52:19

worse than people because uh

play52:22

you know we're all people we can

play52:24

think about you know are we really

play52:26

unbiased i think we actually are quite

play52:28

poor and ai should be a blessing if we

play52:31

do a good job

play52:32

of course the data will tell us whether

play52:36

there's a correlation between potential

play52:38

bias and and outcomes

play52:40

and then hopefully the person who's then

play52:42

creating

play52:44

you know the programs can kind of

play52:47

get the get the bias out of the of the

play52:50

uh

play52:52

the ai

play52:53

we can get a lot of it out you can

play52:55

actually go further if let's say

play52:57

uh racial bias is your biggest concern

play53:00

then just remove um race out of the data

play53:05

then it won't be pivoting on that column

play53:07

of saying okay i'll treat the chinese

play53:10

worse and treat the you know filipino

play53:12

better or something like that but but i

play53:15

would also caution that even if you take

play53:17

that one out there are probably other

play53:19

ways to infer race by you know the la

play53:22

the surname and right place they live

play53:25

they live in chinatown they're probably

play53:26

chinese so

play53:28

you probably have to remove a fair

play53:30

amount of data to remove most of the

play53:32

inferible racial elements but if that's

play53:34

really important to the ai you want to

play53:36

build

play53:37

then remove remove all of that yeah

play53:40

i want to make sure i get to some

play53:42

audience questions before we close um

play53:44

morgan pierce from csis asks

play53:47

experts for predicting that ai will

play53:49

displace many blue-collar workers as you

play53:52

said uh what's the chinese government

play53:55

doing to provide a safety net for those

play53:58

who are going to be impacted

play54:00

yeah uh we are not seeing

play54:03

much action by any government right now

play54:06

on this ai displacement issue

play54:08

because i think most of the

play54:11

displacements are absorbed in the

play54:14

employment process that is you know

play54:16

people lose their jobs then they go on

play54:17

and find something else so we haven't

play54:20

reached a point where large numbers of

play54:23

displacements are causing the government

play54:25

to have to step in you know on the you

play54:27

know on the u.s side i think covet has

play54:30

made unemployment numbers not so

play54:32

dependable so uh despite efforts you

play54:35

know you know like andrew yang he speaks

play54:37

up about the need for universal basic

play54:39

income due to ai displacement but you

play54:42

know one percent of u.s listens to him

play54:44

so he's getting some voice but the

play54:46

government hasn't really seen it

play54:48

necessary to come up with any policies i

play54:50

would say

play54:51

china is not looking at the terrible

play54:53

unemployment number and i would say

play54:55

generally speaking when governments are

play54:57

not seeing bad unemployment numbers

play54:59

they're not likely to proactively deal

play55:02

with this

play55:05

humo

play55:06

from his law firm i asked since china is

play55:08

the leading country in development and

play55:10

implementation of ai what's the

play55:12

implication for the u.s and europe in

play55:14

light of the open competition and

play55:16

potential conflict with china in the

play55:18

years ahead

play55:20

well commercial ai is not really a

play55:23

conflict between countries uh you know

play55:26

tencent alibaba google amazon can can

play55:29

all be successful

play55:30

they'll have different products

play55:32

different geographies so i i think on

play55:35

the commercial aspect i would anticipate

play55:38

you american companies to be really

play55:40

successful um probably more so in

play55:44

enterprise software space like c3ai and

play55:48

palantir and the like uh chinese

play55:50

companies will probably see more

play55:53

robots and automation because of the

play55:55

manufacturing prowess

play55:57

and i think both countries will do well

play56:00

europe i think will not be able to

play56:02

emerge as a giant in ai

play56:04

partly because um i think the eu wants

play56:08

to limit ai because of their concerns

play56:11

about personal data and um and their

play56:14

concerns about um

play56:17

internet companies having too much power

play56:19

and also eu is not really one language

play56:22

one culture entity so a ai company will

play56:26

have a harder time penetrate all of eu

play56:29

whereas the chinese or american

play56:30

companies would not have that problem

play56:32

it's a cohesive

play56:34

single language single culture large

play56:36

market so u.s china continue will

play56:39

continue to be ai superpowers as i

play56:41

predicted in my last book

play56:45

and that's why europe developed this

play56:48

gdpr which is replete with problems and

play56:51

makes kind of development of ai and

play56:53

collection of data which would enhance

play56:55

ai extremely difficult yeah i think gdpr

play56:59

is very well intentioned it tries to

play57:01

protect things that we should

play57:03

try to protect but it does so in ways

play57:06

that i think will impede the growth of

play57:08

ai and and to some extent it will

play57:11

influence other countries including u.s

play57:13

and china to to use gdpr as a reference

play57:16

and develop their own laws but i think

play57:19

europe will enforce it with the

play57:21

strictest

play57:22

requirement for compliance and thereby

play57:24

making it more difficult

play57:26

to start an ai company in europe

play57:28

compared to us or china

play57:31

yeah there's no question that europe the

play57:33

amendment of the amount of venture

play57:35

capital in europe the amount of kind of

play57:37

stock the number of startups in europe

play57:40

is a tiny tiny portion of the united

play57:42

states or china

play57:45

right

play57:46

it's and i guess that's how it's going

play57:48

to be the europeans

play57:50

are willing

play57:52

to

play57:53

live with that result it's interesting

play57:57

yes i spoke once to a european regulator

play57:59

and i said all these policies will cause

play58:02

ai to slow down in europe and his answer

play58:05

was dr lee

play58:07

that's not a side effect that is what we

play58:09

intend so that is a very different

play58:11

mentality than the uh american or the

play58:14

chinese field yeah

play58:16

and is that this uh

play58:18

that'll let you get to your your paying

play58:20

job in a couple of minutes the um

play58:23

is that

play58:25

are the views because you've spent your

play58:27

life in china and the united states is

play58:30

are the views of the individuals just

play58:33

different with respect to data and

play58:35

privacy that that a chinese is willing

play58:38

to give up

play58:40

um their data in exchange for

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potentially more personal safety or more

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advancements in science americans are

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less willing and europeans the least

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willing is that a fair characterization

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uh it is a

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reasonable high level characterization

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but the answer is much more nuanced i

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think you know i think it's universal

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value that everybody

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wants to keep their personal data as

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private uh as possible but when it comes

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to two priorities of uh needing to be

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prioritized

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i think chinese and europeans and

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americans may prioritize them

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differently uh an example is a co

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incovid right because of kovid

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everyone in china has a extremely

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accurate con contact tracing app that

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knows exactly where i've been and

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whether i've been contact with anyone

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who may have contracted coronavirus and

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as a result

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and also the use of you know cameras a

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facial recognition along with

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temperature and when i go into a

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building uh it

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at least the building i work in it knows

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who i am and what my temperature is so

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if i have a fever

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i will be invited i will be asked to go

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to a hospital

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no matter

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no matter where i go so that's the

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chinese way

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you know i think most americans and

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certainly europeans will find that

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unpleasant and maybe unacceptable

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but today if you do a survey to china of

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saying chinese people given this is how

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china controls coronavirus these are the

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things you give up these are the things

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you gain safety lower deaths etc

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do you would you rather go for a chinese

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approach or a european american approach

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i would say almost 100 percent of

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chinese people would say i think it's a

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good trade-off that

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our government and our companies do what

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they do

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and and conversely i also think most

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americans europeans would prefer to keep

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the systems they have rather than adopt

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a chinese system so you know while

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everyone wants personal private data

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the answer is nuanced and this is a case

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in point

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wow

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fascinating kaifu thank you so much to

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our listeners and viewers

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this book will give you hours of

play61:07

pleasure and lots of education

play61:10

so thank you so much for being a great

play61:12

friend of the national committee and

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thank you for writing

play61:16

another great book

play61:25

you

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