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Newsletter February 2021

February 14, 2021

AI International Governance Newsletter

The Institute for AI International Governance of Tsinghua University (I-AIIG)


Frontier View


The thematic session - “Role of AI in combating Covid-19: what are the lessons?”, organized bytheInstitute for AI International Governance of Tsinghua University (I-AIIG),was successfully held on 18th December, during theInaugural Tsinghua University International AI Cooperation and Governance Forum 2020.Co-organizers of the session include Tsinghua University’s Institute for Artificial Intelligence, China Institute for Science and Technology Policy, Center for Science & Technology Development and Governance, and Center for Industrial Development and Environmental Governance. The event was moderated by Professor Liang Zheng, Vice Dean of I-AIIG. Professor Xue Lan, Dean of I-AIIG, delivered welcome remarks.


Xue Lan, Dean of I-AIIG, expressed that since the beginning of 2020, as the biggest “black swan event” of this century, the global pandemic of COVID-19 has seriously threatened the lives and health of people in all countries, hindering and delaying the development of global economy. In the process of fighting the epidemic, AI technology has played an important role in aspects such as precise identification, precise prevention and control, precise policy implementation, and resumption of work and production. It has become a powerful supporting tool for emergency management in the context of the outbreak of major public health risks. However, at the same time, the widespread application of AI technology in the fight against the epidemic has also brought about many controversies in social ethics, personal privacy, and even in public safety.


Yu Yang, Director for International Academic Exchange at I-AIIGand Assistant Professor at the Institute for Interdisciplinary Information Sciences, Tsinghua University, introduced the research results on the participation of AI in epidemic management in China. He said that in the practice of China’s epidemic management, two features of information and data technology represented by AI were shown, namely comprehensive and fast. China's epidemic management is delivered by an integrative coordination governance body formed by an AI-adaptive government and active and capable enterprises. AI technology can participate in China's epidemic management in a comprehensive, fast and penetrable manner mainly because it is supported by three key elements: enterprises who actively participate in the management, the government of algorithm thinking, and the large number of hub departments in the government and enterprises. He believed that China’s experience in the epidemic has shown two facts. One is that AI can quickly and fully participate in the management of the epidemic. The second is that such a fast and comprehensive penetration of AI did not occur in any other AI powers and big countries. The second key element is the government with algorithmic thinking. This government cannot only actively seek technology in social sectors, but also can use algorithmic thinking in governance. For example, divide-and-conquer algorithm was utilized in China's large-scale nucleic acid testing which has greatly improved the testing speed. More than 8 million people were tested in Qingdao within three days, for instance. The third key element is a large number of hub departments in the government and enterprises. These hub departments in enterprises have many cross-departmental talents who understand government tasks and government rules and regulations. There are also hub departments in such a government where there are officials who understand the entire production process, from technology to products, and to tasks. Therefore, the reason why AI technology can be involved in China's epidemic management in a comprehensive and fast penetration is due to the following three elements: the first is proactive and capable enterprises, NGOs, and social organizations. The second is an AI-adaptive government. The Chinese government is not hostile to AI, nor does it mean that it cannot accommodate AI. The third is hub departments that widely exist in governments, enterprises and NGOs. These three key elements ensure that China's governance during the epidemic is an integrative one joined by enterprises, NGOs and the government. This integrative governance enables AI to be involved in the entire process. Based on this conclusion, Yu Yang put forward three policy recommendations. First, any country and region should be clear that AI enterprises and NGOs are important reserve forces for national governance, and systems should be established to accommodate and encourage AI enterprises and NGOs to govern voluntarily. Second, the algorithmic thinking of the government in governance should be cultivated, and an AI-adaptive government in terms of thinking, system, and structure should be built. The third suggestion is to strengthen and promote the hub departments in the government, enterprises and NGOs who have the ability to coordinate and integrate AI.


Effy Vayena,co-chair of the WHO’s expert advisory group on Artificial Intelligence health ethics and governance and a Professor at the Swiss Federal Institute of Technology (ETHZ) for Big Data and Artificial Intelligence Ethics, then gave a speech introducing the epidemic situation in Europe and related experiences and lessons. First, digital transformation and governance are very urgent tasks. It can be seen that there are no such systems in some places at present. During the epidemic in the past few months, the necessity for various countries to cooperate and coordinate clearly in the governance of digital applications is found. There must be a clear path of cooperation. From a European perspective, it is a bit simpler to coordinate among countries, but great importance should be attached to international coordination on the borders. At present, we have not done enough in this respect. Therefore, on the one hand, we really need to do a great job in each individual country, and on the other hand, we need to promote international cooperation. Second, we can see the so-called “bipolarity” phenomenon during the epidemic. If we take a look at many existing frameworks, we will find that in fact, every country, in most of the time, faces the challenge of “bipolarity” between freedom and health, and between we and they. In fact, there will be divergence in the framework formulated in this way. The choice for everyone is different, and the result is that some proposals are unimaginative and not able to help us tackle the challenges. Generally speaking, bipolarity does not do much good, and will lead to polarization. Actually, it brings many problems. I think we have learned lessons and experiences in the process of epidemic prevention and control. So what kind of approach will help? The answer is to get rid of the simple dichotomy. Technology can bring solutions, but it cannot deprive people of making choices. This statement mentioned that member states can achieve their own public health goals while protecting some basic rights, such as privacy. The two can be achieved at the same time. When epidemics occur in the future, dialogues can be conducted by integrating the above-mentioned two aspects. Third, we feel that countries sometimes overreact to issues such as data protection and data resource. In Europe, countries want to protect their citizens from being affected by the crisis, but at the same time they don’t want to violate the rule of law, democracy, and basic rights. We should not neglect this when taking measures through official channels during the epidemic, calling on everyone to protect human rights by the United Nations, and formulating emergency measures. Fourth, during the discussion and the process of developing different technologies, we saw the emergence of ethical and transparency issues. Moreover, public participation is another principle.


Xia Huaxia,Vice President and Chief Scientist of Meituan, then shared the measures taken by Meituan in fighting the epidemic, boundaries in AI application and AI governance. During the epidemic, Meituan helped various communities and people by providing delivery services since many people cannot go out, especially those medical workers. On the one hand, it helped to better connect businesses and consumers, and provides medical workers with delivered food. The simulated robot generated by machine can communicate with many merchants, riders, and users. With this customer service robot, more than 1 million calls can be made every day in parallel, updating the actual status of each shop in real time. On the other hand, on the consumer side, Meituan helped with quarantine. A video of an unmanned delivery vehicle which was first in service during the epidemic in February this year was shown. The vehicle is still providing normalized operation and delivery services in Shunyi District, Beijing. It drives on open roads that can automatically recognize traffic lights, and avoid pedestrians and various obstacles on the road. During the epidemic, it served about 8 communities in Shunyi District. Up to now, it has served nearly 20 communities and provided delivery services to local residents on a daily basis. Now it has delivered over 1 million orders. Meituan also provided big data services to the government to help with the better control of work resumption and production in various local districts, counties and industries. Since there is a large amount of data regarding local life services, Meituan did data mining, and then provided the government with a very accurate digital governance method.


Mr. Xia Huaxia continued to indicate that AI brings us a lot of convenience, but at the same time, it also raises some privacy or security issues. Some of the problems caused by AI can be solved through technology, such as privacy issues. We can process a lot of data at the end through technical means instead of sending data to the cloud. When data is kept on terminal devices, user privacy can be better protected. There are also some AI governance problems that cannot be easily dealt with through technology. In these cases, there is a need to better integrate with the government and regulations, and to regulate the application of technology in accordance with laws. Moreover, we hope that AI would become a tool for ordinary people but not a substitute, a harm to people, nor the terminator of humanity. We hope that the entire society could embrace AI. I also want to share with you on what we have done in Meituan. Last month, a special AI governance committee was established with the cooperation of Tsinghua University. Meituan then established its corresponding internal organization. The tasks of this organization include thinking about how to apply technology within the company and how to use AI, exploring some boundaries and how to protect the privacy of users, etc. We also reflect on how to educate users and tell users how AI is used in Meituan. People fear the unknow. If users don’t know how we apply AI, they would not accept us. But if the users were informed clearly about how data is used and protected, and when the technology is used transparently, it would be easier for them to understand and accept us. At the same time, we are also actively participating in the formulation of some standards and regulations. These are some of the actions we are taking. Generally speaking, we recognize that AI has a huge impact on the entire human society. Meituan is also working hard to apply AI technology in various aspects and make AI the basic facility for our services. AI may not necessarily be seen, but AI is everywhere. This is the direction we have been working towards.


Shi Jun,President of Asia Pacific Business Group and Vice President of Strategic Planning of SenseTime, made a presentation. He said that in the midst of the epidemic, as the flow of people and logistics is declining, a de-internationalization argument has emerged. He believed that the essence of de-internationalization is actually to implement polycentric governance. Compared with the unification of the world, the coexistence of multiple small centers is the world's development trend. During the epidemic, the policies adopted by various countries are still somewhat similar. For example, fiscal and financial policies are easing, so the US dollar may become less and less valuable. However, in terms of how to deal with the epidemic, every country has its own thought to contend.

SenseTime developed an AI thermometer installed in Japan's largest retail company. The principle is not to use AI to measure temperature, but to use AI to guide the temperature measurement points to measure according to seasons, whether its winter or summer, and to adjust the angle based on people’s position, so to achieve the greatest degree of accuracy. We are very concerned about whether AI can attract the next round of investors after the epidemic, because we are still a start-up company and survival is the priority. We have also kept a watchful eye on policy-makers in various countries during the epidemic. Their focus were more on addressing the epidemic. Therefore, the release of AI white papers seems to have been slightly delayed, but the discussion on AI governance has not stopped. Our experience is that as an AI company, we need to develop responsible AI. What is being responsible? Mr. Xia just mentioned the delivery services. To be responsible, as a deliveryman, first of all, you need to be healthy and rational. You must be able to deliver very quickly and healthily, and you need to take your body temperature and wear a mask every day. Then comes compliance. It is necessary to stop when the traffic light is red. Another factor is rational. It is essential for the deliverymen to determine the order of priority based on the order receiving sequence, rather than other factors, such as the appearance of customers judged in their mind.


Expert Perspectives


Panel 1: International experience on using AI to fight the epidemic


1. Hsiao-Wuen Hon: Responding, Recovering and Reshaping Strategies in the Face of the Epidemic


The first stage is response. Due to its earliest outbreak, China is very experienced at this stage. The most important feature here is remote working, such as telecommuting, ZOOM, WeChat, and even telemedicine. Cloud computing also played an important role. This is because although people cannot flow, information can. Relying on the backstage IT technology, cloud computing makes the world go round, and it is noticed by everyone that high-tech has played a decisive role in the fight against the epidemic.


The second stage is recovery. China has done the best in this part. Today, we need to show the health code when we go to many places. According to China’s experience, the stage of recovery is more important than response, because activities such as scanning and tracking are not involved at the response stage. Moreover, accelerating vaccine production is also a top priority. There are many types of vaccines. In addition to the traditional inactivated vaccines, there are also adenovirus-based vaccines which make the adenovirus looks like a coronavirus in order to push the production of antibodies.


The final stage is reshaping. The post-epidemic era will change many things in this world. Let me give an example of Microsoft where employees generally work remotely. 50% of its employee can work from home without the approval of the company, and it allows employees to live far away from the company, even in other countries. Of course, this kind of teleworking is not a replacement of the traditional way of working, yet it plays a bigger role. We need to pay close attention to those changes in the post-epidemic era.


2. Song Jiqiang: AI Technology Improves the Efficiency of Detection, Prevention and Treatment


In terms of fighting the epidemic, three actions must be done simultaneously, detection, treatment, and prevention. One purpose is to greatly improve efficiency, because we are racing against time. Moreover, we need to replace people and try to minimize people involvement. We need to protect people who have not been vaccinated and avoid contact. In order to achieve these comprehensive goals, we first had a look at Intel’s various technologies, including hardware, software, and network technologies, and made them applicable for industry partners. Intel itself is a upstream company in the industry chain and does not produce various products directly.


In terms of detection, the first thing to do is to see if there are any symptoms, and use CT to check the changes in the lungs. This would be a long process if such detections are done manually and if there are many people to do detections. Therefore, we firstly applied AI technology in this field. With the help of partners, we quickly upgraded this function to a usable level. Through effective cooperation, the detection rate has been increased to 96%. It soon replaced human to do detection, and the speed can reach 500 detections in 20 seconds. If a center of AI can be established, then many cases could be detected through this way. In addition, after detection, early virus analysis need to be done which actually requires a lot of calculations for genetic analysis. Viruses are new things to us. We quickly set up a high-performance computing center with BGI and Lenovo to do all the sequencing of genome, which has increased the analysis speed by more than 40 times. Fast response allowed the detection stage to achieve excellent results.


For prevention, we know that wearing masks is the priority. At that time, the production capacity of masks, including quality tests of masks, did not meet the high demand. If we activate some production lines as soon as possible and automate the production, then we would depend on people to do quality check. This means many people have to participate in the production process which does not meet the requirements of epidemic prevention. Therefore, our company and some other companies use AI to do testing to check whether the production of masks is compliant, replacing people while improving efficiency.


There are many aseptic processing areas. There is no need for people to enter the emergency ward to do sterilization and examination. Some personnel screening can be done by robots. At that time, it was discovered that the demand for robots was so strong, yet the capabilities of robots did not reach such high levels. Therefore, we made full use of available technologies. In the aspects of delivery and ward sterilization, the speed of robots has been increased several times or even dozens of times. These aspects are very important in dealing with various problems that may arise now.


3. Tang Jian: AI Technology Helps Fight the Epidemic


The initial outbreak of the epidemic was during the Spring Festival of 2020. First of all, Didi took less than 31 hours to launch the medical care security fleet service provided for medical workers in Wuhan. 500 full-time drivers were dispatched urgently to provide commuting services for more than 8,000 Wuhan medical workers, which has been fully affirmed and recognized by Wuhan medical workers and the government. Later, this service was promoted to 14 cities including Beijing, Shanghai, Ningbo, and Nanjing, covering more than 23,000 medical workers.


Second, Didi Hero was launched mainly to help with the international epidemic prevention and control. We have recruited more than 50,000 drivers to voluntarily serve international passengers and provide medical workers with free or discounted transportation services. In addition, Didi has set up a special epidemic prevention fund of about RMB 300 million to support the services of the medical fleet and to purchase medical supplies such as protective films, masks and detergents.


In addition, Didi also particularly explored and practiced on how to use technology, such as AI technology to help fight the epidemic. Here are two specific examples. At the beginning of the epidemic, during the Spring Festival, our team accepted a command in such a critical situation, and used less than 23 hours to equip hundreds of thousands of vehicles, and now more than one million vehicles with a black box, which is an on-board equipment to detect whether the driver is wearing a mask and then transfer results online. This sounds relatively simple, but it is very difficult to be realized. The accuracy is affected by many factors, such as light, and whether the head of the driver in an open environment face directly to the camera. We quickly increased the accuracy rate to over 98%, which played a crucial role in ensuring safe travel services during the epidemic.


Later, this AI function was extended to the international service team, and it was also launched in many countries and regions in South America, serving many drivers. China has done an excellent job and performed outstandingly in this epidemic. It has been found from experience that wearing a mask is the most effective way to quickly control and ultimately block the transmission route of the virus. The outbreak of the epidemic was in the peak travel season of the Spring Festival. There were a large number of passengers returning to Beijing at the end of the Spring Festival holiday. Didi Chuxing and the State Key Laboratory of Software Development Environment, Beihang University have worked hard together to develop the monitoring and analysis technology for the tracing of returning passengers under the guidance of the Beijing Municipal Government. Later, we reported to the Beijing Municipal Party Committee the source of passengers returning to Beijing and the development of the epidemic in various districts of Beijing, and provided them with data and reports.


4. Kong Qiushi: AI and Big Data Empowered Frontline Epidemic Prevention and Control, and Realized the Scientific Decision-making of the Government


We have achieved certain results in applying AI and big data technology to carry out epidemic prevention and control, and have accumulated some experience. First, the epidemic situation must be visualized. Relying on data visualization, the“Xiaoshan fight against epidemic”digital cockpit, with the function of data analysis and research, helped to control the development of the epidemic in the entire district in a timely and accurate manner. Xiaoshan District has a relatively large area and a relatively large population base. Therefore, through automatic analysis of the system and visualization of the epidemic, administrators can fully and intuitively get the dynamics of the epidemic in the entire district, so as to make better scientific and accurate decisions. For example, through the“three-return monitoring”function, the information of people“returning to school, returning to work, and returning to operating post”can be dynamically monitored. And through the epidemic broadcasting function, the epidemic situation can be detected and data of personnel at district-level centralized medical observation points can be detected. Second, the epidemic investigation process should be intelligent. In the systematic work of epidemic prevention and control, the grassroots units are the forefront and need to undertake a lot of heavy investigation work. By realizing the intelligence of epidemic investigation, work efficiency can be effectively improved and the burden of grassroots work can be reduced. For example, the intelligent chatbot I mentioned before can automatically carry out the collection of health information of residents and the investigation of the epidemic situation in the areas under administration. In response to the different answers of interviewees, we have designed different inquiry paths. The intelligent chatbot can convert interviewees’response into text and input into the database, analyze the residents' epidemic-related information in the database, generate classified statistical reports, and quickly realize the troubleshooting of community residents' information, health status and flow situation. If the interviewee is found to have a fever, cough, etc., the background will give an alarm immediately, and send such information to the community where the interviewee is located. The community staff will then visit the interviewee to do verification. In this way, we can accomplish the whole process of pre-warning, prevention and control, and follow-up. Third, early warning of risks should be precise. Accurate early warning of epidemic risks cannot only help to make“precise fight”in epidemic management, but also effectively avoid the spread of panic caused by misinformation, which is also helpful to enhance the credibility of the government among the general public. For example, Xiaoshan District innovatively used computer simulation algorithms to dynamically generate the“close contact index map”during the epidemic. The Xiaoshan jurisdiction area is subdivided into grids of 100-meter, and the massive data iterative algorithm model is used to analyze the potential epidemic risks of each grid in real time. According to the degree of danger from high to low, each grid is marked with a color: red, orange, yellow, or blue. Early warning is given to the red and orange grids, and the towns and streets where the grids are located will be urged to increase the intensity of prevention and control measures.


Panel 2: The outlook of post-pandemic governance of AI in the globe


5. Jiang Yan: Implement Corporate Social Responsibility and Actively Participate in AI Governance


As one of the representatives of domestic AI enterprises, Megvii was the first to realize that the COVID-19 pandemic is not simply a major crisis in the field of public health, it also poses new challenges to the development of emerging technologies represented by AI. Innovative digital technology cannot only effectively alleviate the impact of the epidemic, but also stabilize economic and social development during the epidemic. Megvii actively implemented corporate social responsibilities during the anti-epidemic period and took the lead in setting up an emergency R&D team. It took Megvii only ten days to develop an AI temperature measurement system solution, which was then put into service in crowded areas such as hospitals, transportation hubs, and shopping malls with no delay to provide assistance to the anti-epidemic process.


Jiang Yan pointed out that the key to the development of AI in the post-epidemic era is to properly handle the relationship between innovative development and effective governance. On the one hand, AI technology should be put into specific scenarios to improve its flexibility and fineness. On the other hand, a comprehensive supervision system should be established to reassure the public so that they can enjoy the value and profits brought by technology. In general, Megvii adheres to the following three principles in the practice of AI governance. The first is no absence. As the provider of AI technology, AI enterprises must participate in the whole process of governance. The second is no confrontation. The application and development of technology and its application in business, and the formulation of rules can complement and reinforce each other, and they are not in opposition to each other. Third, actions speak louder than words. AI governance must be implemented in the daily work of enterprises, thereby gradually realizing the sustainable development of technology and society.


6. Jenny (Yu) Zeng,: COVID-19 Pandemic Triggered New Market Segments and New Business Formats


While bringing more possibilities to the financial market, the epidemic has also brought unavoidable uncertainties. During the epidemic, subdivided industries such as online education, collaborative office, home fitness, online medical care, chronic disease management, and remote diagnose through interrogation rose rapidly. The market has both high expectations for high-tech companies, especially AI-empowered companies and industries, as well as concerns about bubbles. The reason is that the development of emerging technologies represented by AI has reached a milestone stage. The sudden outbreak of the COVID-19 pandemic has increased the number of application scenarios of technology in a short period of time, and has stimulated the empowerment of technology to the industry. Although many companies' original businesses have been affected and hit by the epidemic, there are also many companies that have taken this opportunity to achieve quick business transformation. If we want to apply technology to help the world, it is very important to have strong organizational and calling abilities, and different subjects have to make concerted efforts.


7. Tokuchi Tastsuhito: Summary of Japanese Government’s Experience in Fighting the Epidemic


During the epidemic, Japanese government agencies did not provide sound guidance for AI technology to play its due role. First, the government offered subsidies equivalent to about RMB 7,000 to every Japanese citizen during the epidemic, but the distribution was very inefficient. The reason is that the statistical work was not in place, which has caused widespread dissatisfaction among Japanese citizens.


Japan's AI technology is difficult to apply on a large scale. One of the important reasons lies in the protection of personal privacy or the legalization of government’s enforceable rights to people.


The COVID-19 pandemic has made Japan realize the great benefits that AI technology may bring to human life, and a powerful system may be able to save millions of lives. Japan neither hopes to sacrifice hundreds of thousands of lives for the sake of freedom, nor can it sacrifice the freedom of the people for the sake of life safety. Therefore, in order to implement AI governance, the following issues, at least, need to be dealt with. First, the issue of ownership, usage, sharing, and responsibility division of data needs to be handled. Second, the issue of how to protect personal privacy and personal safety is to be settled. Third, the issue of how to coordinate the relationship between the state, platform companies, and the society has to be worked out. Fourth, the complex international politics has fragmented the Internet, so there is the issue on how to protect the Internet which needs to be coped with.

Countries hold different ideas in solving the above-mentioned issues. Mr. Ted Tokuchi believed that the keys to solving these problems are for people to participate and to supervise, and international issues must be resolved under the international framework formed by relevant countries. Under the leadership of the new prime minister, the Japanese government is moving towards new reforms. In the coming three to five years, it will coordinate the virtual platforms of the central and local governments of Japan, and connect business platforms such as medical care and education platforms, thereby promoting Japan's construction of a new digital society in the 21st century.

8. Adrian Weller: AI Systems Need to Attend to Various Interests

While bringing challenges to all mankind, the epidemic also brings favourable opportunities for technology-empowered social governance. For example, personal health information can be integrated into the system to realize the monitoring of health condition of a specific population or area. The systematic integration of data helps us outline better social outcomes and policies, so that the society can assume better responsibilities. At the same time, some countries keep eyes on microeconomic activities during the epidemic and establish models to promote economic development.


In addition, in the past, we usually believed that AI systems were adopted to optimize industrial management, or the flow of goods supplied, etc. However, through this epidemic, people realized that what we need to think about is not just instant optimization, but also ways to make the system more powerful. In addition, the sudden outbreak of the epidemic has encouraged us to focus on how to balance the support provided to individuals and to groups, such as how to share health data or use digital tracking technology to benefit everyone.


Currently, at the international level, there have been many agreements concerning the principles of AI. Although there are many overlaps among these principles, there are also some differences. For example, some countries emphasize strongly on, or compare to other countries, put more emphasis on the concept of harmony or social rights and interests. In addition to personal rights and interests, they pay more attention to social rights and interests. At present, there is no unified and dominant solution. If we want to make further progress in formulating principles, we need to better understand the interrelationship amongst these principles, especially under specific scenarios. For example, the United Nations Roadmap for Digital Cooperation and the one set up by UNESCO are good platforms. Weller suggested that extensive collaborations can be promoted in technical fields with no controversies.


9. Rohinton Medhora: Challenges to AI Development Brought by COVID-19


First, the COVID-19 pandemic has demonstrated the importance of the so-called digital divide. Two-thirds of the world’s population still don’t have any access to the Internet, while in more developed societies, people can work and have meetings at home. Then came the issues of network security and the resilience of the supply chain. These problems have been in existence before the outbreak of COVID-19 pandemic, but the epidemic has made these problems more prominent.


Second, the COVID-19 pandemic has triggered a reflection on the widespread use of technology. For example, many countries apply tracking applications as one of the measures to fight the epidemic. However, people are concerned about data issues such as how data is collected, how data is stored, and how data is used, down to other governance issues, including privacy, security, and human rights. The COVID-19 pandemic has further highlighted these issues and made them major diplomatic challenges facing all countries around the world.


In the field of science, especially when data algorithms are increasingly applied to promote social management, the importance of scientific cooperation has been highlighted by the outbreak of COVID-19 pandemic. China released the genetic sequence of the novel coronavirus in early January, 2020, and has since accelerated the speed of vaccine development. It can be said that sometimes crisis can foster positive cooperation and lead people to think more deeply about different ways of cooperating in science and sharing intellectual property rights. But in fact we are still in the early stages. When I see this series of issues, in my opinion, the first step must be taken is to have some kind of global declaration on how to use new technologies, which will become a consensus-based benchmark to guide national and subnational legislation.


Major Events


1. I-AIIG Co-hosted Tsinghua University Data Utilization and Data Governance Forums


On15th February, 2021, five think tanks in the field of digital governance of Tsinghua University, including the Institute for AI International Governance, jointly held the webinar of the first Tsinghua University Data Utilization and Data Governance Forums: Thematic Session on Enterprise Data Utilization and Governance. The main focus of the forum was on key issues including how to determine the ownership of different types of data held by platform enterprises, how to safely open and use data involving personal rights, business secrets and intellectual property rights, how to regulate data competition amongst enterprises, how to open and use corporate data involving public interests, how to securely govern the cross-border flow of corporate data, how to identify corporate data as assets, how to build transaction or sharing markets for corporate data, etc. Experts from all parties shared their opinions actively and conducted engaging discussions.


2. Seminar Held on Research on the Comprehensive Impact of AI on Public Governance


On13th January 2021, the major project of Research on Challenges and Countermeasures of AI Governance in Key Fields---Topic 4 Research on the Comprehensive Impact of AI on Public Governance seminar was held at Tsinghua University. The seminar was presided over by Professor Liang Zheng, vice president of the Institute for AI International Governance. Wu Peiyi, assistant researcher of the Institute for AI International Governance, summarized the research progress of Topic 4 in 2020 and introduced the research tasks in 2021. Yu Zhen, Zhang Hui, Zeng Xiong, Li Rui and other members of the research team conducted full exchanges and discussions on the research tasks for the first half of 2021. Finally, Professor Liang Zheng made comments and summarized the research project.

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