Frontiers and Futures of AI and Robotics

Berggruen Institute China Center

On March 17 and 18, the Berggruen Institute China Center (BICC) held the first of a series of workshops on AI, robotics, and society. The conference gathered Chinese and international experts and scholars to present keynote speeches and participate in academic discussions.

Roger Ames

Roger Ames, Humanities Chair Professor at Peking University and Berggruen Institute China Center Academic Director, opened the event with remarks about the Berggruen Institute’s work to share Chinese voices with Western thinkers and policy makers. Through the recently launched China Center, the Berggruen Institute seeks to fulfill the mutual need of China and the West to better understand one another.

Berggruen Institute China Center Director Song Bing

Song Bing, BICC Director, noted that the Berggruen Institute promotes research and cross-cultural, interdisciplinary dialogues with participants from the sciences, philosophy, and the social sciences as well as investment, publishing, and other industries. The speakers were chosen to further the Berggruen Institute’s mission. The Berggruen Institute will also publish a series of collected papers that were created around the workshops as part of a wider program to create academic activities such as lectures and cross-industry and cross-cultural dialogues.

Session speakers on March 17 included: Chen Xiaoping, Professor from the University of Science and Technology of China, Zeng Yi, a researcher from the Institute of Automation, Chinese Academy of Sciences, Luo Dingsheng, Associate Professor of the Department of Intelligence Science at Peking University. The conversation was moderated by Zhang Xiaorong, a senior consultant of Tencent Research Institute.

Chen Xiaoping

Chen Xiaoping’s presentation was titled “From Analyticity to Tolerance: A Continuous Change of Thinking in the New Progress of AI.” He demonstrated that, in the past 60 years, the development of AI research has been cumulative yet, while a large number of technologies continue to emerge, new technologies have not performed well in solving large-scale practical problems. For example, the new progress of AI represented by AlphaGo does not introduce new cutting-edge technologies but groundbreaking progress in solving large-scale real problems. It has abandoned the problem-solving method based on analyticity, i.e., the traditional concept of “analytic model + mathematical approximation.”

Using this new concept to promote simplification, large-scale engineering integration, and experimentation within existing AI technologies creates new capability levels that were unimaginable before. This demonstrates great potential for solving large-scale AI problems, and it brings new solutions to major social issues like industrial applications and technological risks.

Zeng Yi, Researcher at the Institute of Automation, Chinese Academy of Sciences

Zeng Yi delivered an academic report titled “Brain-Like Intelligence: Building Brain-Inspired Cognitive Machine” and announced his goal to build brain-like AI that has brain-inspired structures and mechanisms as well as human-like cognitive functions. In fact, building a brain-inspired intelligence core model is an important step toward the ultimate goal of true AI.

Zeng’s research team began with the premise that pruning synapses is crucial for the development of the brain and that intelligent systems need to acquire more adaptive learning capabilities. He also introduced his research team’s first attempt to build a road-map for machine-autonomous consciousness that took inspiration from the human brain itself. They used specific neuroscience research techniques like the robot-mirror image test of self-perception and mental speculation. More importantly, Zeng Yi envisaged the pursuit of future intelligent creatures in their own interests, values, meaning of life, emotions, and dreams. He believes that all of these are worth exploring and form concrete models based on strict scientific methods and practices. Finally, he emphasized that human beings, when formulating AI ethics, should think about what kind of mentality humans should have to coexist alongside intelligent agents in the future era of human-machine integration.

Peter Hershock, Director of the East-West Center at University of Hawaii and Berggruen Fellow

Peter Hershock, Director of the East-West Center at the University of Hawaii and Berggruen Fellow, noted that Eastern cultures emphasize morality, justice, and emotion. In fact, this coexistence amounts to a multi-level interactive relationship. We are socially connected with new intelligent agents, and they are associated with us in all aspects of spirit, culture, and material. Therefore, the development of AI should be considered as a philosophical paradigm that integrates not only intelligence itself and various advanced technologies but all relevant connections. This is a kind of interdependence in itself.

Luo Dingsheng, AAssociate Pprofessor of the Department of Intelligence Science at Peking University

While the international community has paid great attention to the ethical and legal issues of AI, the ethical and legal issues of AI application in old-age care services are rapidly becoming prominent and urgent. Luo Dingsheng analyzed the main issues of care ethics in AI research with a presentation on “Ethical Issues in Intelligent Nursing Robots.” His presentation analyzed how AI could augment old-age care systems with new technologies like nursing robots. The main ethical issues were comprised of four components including: privacy, mentality of the aged, ease of use and acceptance, and independent willingness.


First, privacy protection is particularly important because intelligent nursing robots are more commonly used in private spaces. For example, for the design of nursing robots it is necessary to adopt a perceptive strategy with low risk for information leakage especially through data usage, data security in transmission, and storage. Analysis and presentation are particularly important when formulating national laws and regulations and relevant responsibilities should be regulated. Second, the aging population has frequent psychological problems. Psychological needs of the aged should be considered when designing nursing systems, such as how the robots appear to and interact with people. It is also necessary to consider that nursing systems should increase the daily social life of the elderly, and should strengthen rather than reduce their children’s sense of responsibility. Third, ease of use and acceptance profoundly affect the usefulness of intelligent nursing systems. The ability of the elderly to learn new things differs greatly. When designing nursing systems, personalized considerations should be made on the granularity of different groups or individuals, and the economical affordability of users should also be taken into account. Under the premise of guaranteeing quality, efforts should be made to reduce costs. Also, guidance and support are required from national policies and they effectively integrate and optimize the allocation of individuals, families, communities, institutions, and healthy old-age care resources. Finally, attention should be paid to the independent willingness of the elderly, because the need for dignity is especially important. Intelligent nursing robots should fully respect the independent willingness of the elderly on the premise of ensuring safety and health.


Luo Dingsheng suggested that the new business model of intelligent old-age care services based on robotics and AI technology is the most promising and feasible solution to building an old-age care service system. The need to explore the ethical issues involved in the use of AI in old-age care, define guiding principles, and clarify the degree of balance between monitoring and privacy and between convenience and dignity is a top priority. Only the integration of state and private AI practitioners, and comprehensively considering solutions to various ethical issues from a variety of perspectives including policy formulation, resource allocation, and industry standards, can intelligent old-age care be truly and widely accepted and effective, thus eventually benefiting the human society.

Tang Yiyuan, CASBS Fellow at Stanford University

Tang Yiyuan, CASBS Fellow at Stanford University, stated in his summary speech, that humans development of AI cannot be stopped or reversed. Despite this, AI is emerging when human beings are still imperfect, and our civilizations are not ideal. Therefore, we have no leeway and must face AI head on. It is possible that AI will surpass human intelligence  in the future and it is necessary to consider that possibility. Accelerating human civilization and development may be a key step in meeting this potentiality This begs the question of whether this emerging relationship between humanity and machines will reduce, replace, or complement human relationships. These challenges may be far beyond current AI development, ethical research, and the core issue of human evolution. If we are to find a solution, Tang believes that we must embark on a road of balance and consider the viewpoints of Eastern cultures and wisdom alongside Western technology and philosophy.

Berggruen Institute China Center Workshop on Artificial Intelligence, March 2018

More than 40 experts, scholars and participants from various universities, research institutes and the finance sector attended the forum, including: Tsinghua University, Peking University, Renmin University of China, Fudan University, Zhejiang University, China University of Political Science and Law, Shandong University, University of Science and Technology of China, University of Cambridge, Stanford University, Wesleyan University, University of Hawaii, Chinese Academy of Sciences, Chinese Academy of Social Sciences, Tencent Research Institute, and the Berggruen Institute.

composed by Arswain
machine learning consultation by Anna Tskhovrebov
commissioned by the Berggruen Institute
premiered at the Bradbury Building
downtown Los Angeles
april 22, 2022

Human perception of what sounds “beautiful” is necessarily biased and exclusive. If we are to truly expand our hearing apparatus, and thus our notion of beauty, we must not only shed preconceived sonic associations but also invite creative participation from beings non-human and non-living. We must also begin to cede creative control away from ourselves and toward such beings by encouraging them to exercise their own standards of beauty and collaborate with each other.

Movement I: Alarm Call
‘Alarm Call’ is a long-form composition and sound collage that juxtaposes, combines, and manipulates alarm calls from various human, non-human, and non-living beings. Evolutionary biologists understand the alarm call to be an altruistic behavior between species, who, by warning others of danger, place themselves by instinct in a broader system of belonging. The piece poses the question: how might we hear better to broaden and enhance our sense of belonging in the universe? Might we behave more altruistically if we better heed the calls of – and call out to – non-human beings?

Using granular synthesis, biofeedback, and algorithmic modulation, I fold the human alarm call – the siren – into non-human alarm calls, generating novel “inter-being” sonic collaborations with increasing sophistication and complexity. 

Movement II: A.I.-Truism
A synthesizer piece co-written with an AI in the style of Vangelis’s Blade Runner score, to pay homage to the space of the Bradbury Building.

Movement III: Alarmism
A machine learning model “learns” A.I.Truism and recreates Alarm Call, generating an original fusion of the two.

Movement IV: A.I. Call
A machine learning model “learns” Alarm Call and recreates A.I.Truism, generating an original fusion of the two.