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Top 10 Questions Voting Result

We would like to thank all people who submited questions, voted for 10 questions, and join the Top 10 Questions Panel. The voting result of top 10 questions has been announced at the Top 10 Questions Panel on Dec 6.
331 people (109 TC members and 222 Non-TC members) voted for the top 10 questions, the voting results can be found at the following lists:

TC Member Voting Result

  1. Q3 Can machines be creative?
    Proposer: Flavius Gorgonio, Federal University of Rio Grande do Norte,Brazil
  2. Q17 How do we protect our privacy and security in the coming embedded intelligence era?
    Proposer: Bin Guo, Northwestern Polytechnical University, China
  3. Q9 Can the machine real understand the semantic of things?
    Proposer: Xiangfeng Luo, Shanghai university, Chain
  4. Q15 Can machines and the people think together?
    Proposer: Peidong Zhu, School of Computer, NUDT, China
  5. Q53 What are fundamental mathematical and cognitive problems to be solved for modeling the mind?
    Proposer: Leonid Perlovsky, Harvard University, USA
  6. Q11 Can computers become socially intelligent?
    Proposer: Frank Dignum,Utrecht University,Netherlands
  7. Q23 Is it possible to have "Internet of Thinking"?
    Proposer: Huansheng Ning, Beihang University, China
  8. Q2 How do we make the balance between human intelligence and machine intelligence?
    Proposer: Bin Guo, Northwestern Polytechnical University, China
  9. Q63 How do we teach computers about our concepts of right and wrong?
    Proposer: Daniel Buehrer, National Chung Cheng University, Taiwan
  10. Q61 What is thinking? Do we already have the model of thinking? Is there one general model of thinking or are there many different models to consider?
    Proposer: Selim Erol,Vienna University of Technology,Austria

Non-TC Member Voting Result

1.  Q5 Will computers replace human thinking?
Proposer: Leonid Perlovsky, Harvard University, USA
2.  Q3 Can machines be creative?
Proposer: Flavius Gorgonio, Federal University of Rio Grande do Norte,Brazil
3.  Q9 Can the machine real understand the semantic of things?
Proposer: Xiangfeng Luo, Shanghai university, Chain
4.  Q17 How do we protect our privacy and security in the coming embedded intelligence era?
Proposer: Bin Guo, Northwestern Polytechnical University, China
5.  Q2 How do we make the balance between human intelligence and machine intelligence?
Proposer: Bin Guo, Northwestern Polytechnical University, China
5.  Q15 Can machines and the people think together?
Proposer: Peidong Zhu, School of Computer, NUDT, China
7.  Q63 How do we teach computers about our concepts of right and wrong?
Proposer: Daniel Buehrer, National Chung Cheng University, Taiwan
8.  Q11 Can computers become socially intelligent?
Proposer: Frank Dignum,Utrecht University,Netherlands
9.  Q23 Is it possible to have "Internet of Thinking"?
Proposer: Huansheng Ning, Beihang University, China
9.  Q85 How can social computing help us to achieve world peace and prosperity?
Proposer: Daniel Buehrer, National Chung Cheng University, Taiwan

Welcome to join the Top10Qi Question Panel

Stage 3: Question Panel (QP)
16:20-18:00, December 6 at Fisherman's Wharf Room 1,
during the World Intelligence Congress in Macau.

In the panel, the detailed information and statistic data will be first reported by the technical committee, and then two sets of Top 10 questions, T10QiCP and T10QiCM, will be announced. Also, Top 10 People who have the most questions in the T10QiCP and T10QiCM will be announced. Next, invited Top10Qi Panelists will give their statements and remarks on the Top 10 Questions. Afterwards, the panel will have open discussions between panelists and all participants. The panel will be lively broadcasted on the Internet, and everyone is welcome to remotely join the panel and ask questions in the panel.

Edward Feigenbaum, Stanford University, USA
Jeffrey Bradshaw, Institute for Human and Machine Cognition, USA
Alexander Felfernig, Graz University of Technology, Austria
Ali-Akbar Ghorbani, University of New Brunswick, Canada
Sven Koenig, University of Southern California, USA
Sankar Pal, Indian Statistical Institute, India
David M W Powers, Flinders University, Australia
Vijay Raghavan, University of Louisiana at Lafayette, USA
Eunice Santos, University of Texas at El Paso, USA
Takahira Yamaguchi, Keio University, Japan
Yiyu Yao, University of Regina, Canada

Jianhua Ma, Hosei University, Japan
Jiming Liu, Hong Kong Baptist University, HK
Ning Zhong, Maebashi Institute of Technology, Japan


The Top10Qi vote stage has been over.
The voting results will be announced in the WIC-2012 panel at Macao.
Appreciate all of you, especially these who submitted or voted for questions!

Questions Received (Last Updated on November 16, 2012)

Questions Received (PDF format)

  1. Are we alone? We are searching for intelligence outside our world but what if a new consciousness will raise within the machines we create?
  2. How do we make the balance between human intelligence and machine intelligence?
  3. Can machines be creative?
  4. Will the human existence be reliant on computers to the extent of computer systems becoming a basic necessity?
  5. Will computers replace human thinking?
  6. Will human brain degenerate with the support rich set of intelligent services in the AI-enhanced world?
  7. How do we engage with, shape or influence human and social behavior in cyberspace?
  8. What is the relationship between online and off-line human and social behaviour?
  9. Can the machine real understand the semantic of things?
  10. Can we solve the over-crowded problem on the earth using crowd-computing? (not cloud-computing)
  11. Can computers become socially intelligent?

    Description: Human interaction requires that people are aware of all kinds of social aspects such as social relationships, conventions, status, history, etc. Will computers learn to behave using all these aspects or will human contacts deteriorate to the level that computers can easily...

  12. DWIM - Do What I Mean problems. Can computers do what I think or intend or say?

    Description: Brain Computer Interface and Audiovisual/Biological Computer (ABC) Interfaces are learning to detect intentions and emotions, and even linguistic or visual features. Within 10 years we will see exciting new capabilities develop in the lab, and within 20, the misunderstandings we currently get in speech recognition will be a thing of the past with products that use multiple sources of information to do what you mean.

  13. How do AI researchers take advantage of these new platforms such as the mobile systems to design context aware and intelligent systems?

    Description: The mobile systems are emerging as a new mass computing solution. Considering they will replace personal computers for the majority of regular users, how the AI researchers will take advantage of these new platforms to design context aware and intelligent systems.

  14. What's lacking to computers to become more intelligent than men not in a single domain but in all domains?
  15. Can machines and the people think together?

    Description: Some operations can be well done by computing machines, while others by the human. For the tasks, e.g., image searching, we can borrow the power from the people in the form of social tagging to help the computers work better. Generally, can we expand the computers' capabilities by integrating the social force in a wider sense so that the computers can accomplish most of the jobs they are not good at before? How to design the social-technical system just like one computing machine? For the Turing machine, all the operations are undertaken by one single machine, how to describe in a formal way the new computing machine, and how intelligent it can be with the participation of the intelligent humans?

  16. What are the most promising solutions and techniques to build real commercial intelligent systems?

    Description: There is a gap between theory and practice when we think about AI. What are the most promising solutions and techniques to build real commercial intelligent systems?

  17. How do we protect our privacy and security in the coming embedded intelligence era?

    Description: In the future world, machines will get more and more aware of human, such as your location, your movement patterns, your hobbies... It is becoming a truth with the development of smart phones. So, how to protect our privacy and security in the coming embedded intelligence era.

  18. What is the basic difference between human being and cyber intelligence even the latter get best evolved?
  19. Can Cyber Intelligence provide a mechanism to taking humans’ responsibilities while assisting humans’ thinking?
  20. Can we find an online persona or virtual manifestation of an individual in cyber social networks?
  21. How do we take advantage of the information on Internet in designing new intelligent systems that exploit this heterogeneous source of information?

    Description: Considering the large amount of the information we already have on Internet, how we will take advantage of it in designing new intelligent systems that exploit this heterogeneous source of information.

  22. Is it the time to look for innovative architectures combining networking protocols, application level communication protocols etc., for catering to the needs of different applications demanding high quality data transmission and user experience on web?
  23. Is it possible to have “Internet of Thinking”?

    Description: From computer to internet (network of computers), then to Internet of things (IoT). But the indeed wisdom and intelligence is created in human brain. Today, we are walking forward to a new era that its start stage is "internet of thoughts/ideas (IoTh)", while the challenge is "internet of thinking (IoTk)". IoTk can implement human wisdom sharing and thinking cooperatively and creatively (also including the sharing and cooperation between human brain thinking and things/machine intelligence). IoTk can surpass the human brain ability and break the limit of space/time limit in the physical world.

  24. Is emergent computing likely to occur in the cloud computing environment?

    Description: If we regard the cloud computing environment as a single big machine, it has no central control and no sequential or determinant input. Some people think some innovations can be made by the vast number of processes or computing components in such an environment. But the virtualization and separation are the main design objective and implementation technology in cloud computing environment, and without enough interactions or cooperation, is the emergent result possible? Can the big cloud computing machine outdo the Turing machine in terms of the emergent computing capability?

  25. How do we observe and analyze online human and social behaviour?
  26. Can we use the semantics of things for organizing resources?
  27. Can we mine the knowledge from database automatically?
  28. In a hyperworld, the merging world of the real world and cyber worlds, how human intelligence, system intelligence, machine intelligence, and software intelligence can meet, interact, and work seamlessly together?
  29. Can the cloud support Human as a Service?

    Description: It is time for all human beings to equally benefit from computing. The cloud could economically empower citizens of knowledge societies as well as 3rd world.

  30. Is cloud computing destined to be simply a much more powerful Internet?

    Description: An Internet offering communication, information, platforms and services? If so, let us work hard & quick on their convergence.

  31. Can cloud think? Is it possible to build thinking cloud?
  32. Can we infer the commonalities among these networks based applications and accommodate them in the existing underlying core networking protocols?
  33. How could we effectively apply user modeling techniques and methodologies to Cyber space and its applications?
  34. How do we take advantage of high speed networks and growing capacity of networking devices? Does it require development of new networking protocol stack?
  35. The computer processing power is increasing with the invention of new hardware devices, does this mean that the computation processing power is infinite and are humans able to achieve it?
  36. Heuristic approaches vs. sampling + exhaustive approaches, which are better for pattern mining?

    Description: People have proposed many algorithms to mine patterns directly from large datasets. Respective problems include feature selection, clustering, decision rule mining, association rule mining, etc. These algorithms might be efficient, however the results may be not good enough.

  37. How can we benefit from multi-relational data mining?
  38. How do we define these patterns hidden in multi-relational databases and make use of them?
  39. How to implement the intelligent data-cycle system as a practical way to realize the harmonious symbiosis of humans, Web (information) and things?
  40. How do we implement efficient and definite psychophysiological inference?
  41. What is the basic algorithm in the cognitive domain? And how does the basic algorithm work on the level between implementational detail and psychology?
  42. How to build a Life Model for each of human individual?
  43. What is the total data amount of a person experienced in one’s whole life? Can we keep all of the data? What the data can be used for?
  44. What is the definition of thinking? What are the elements composed of thinking? What are the necessary conditions of machine thinking?
  45. What is the relationship of thinking and intelligence in machine? What are they differences?
  46. The machine’s thinking independent of people or dependent of people?
  47. As we known, human have two basic attributions: nature attribution and society attribution. Does machine also have these two attributions?
  48. Will machines ever have common sense?
  49. Will machines ever have sense of humor to invent and appreciate jokes?
  50. Can security be really enhanced if machines have the capability of thinking?

    Description: Security is a big challenge in current computer world. For a computer system, human is always a critical factor in affecting its security. Based on this observation, if machines can think and act as a human, is the impact the same?

  51. How can machines recognize human-like information?
  52. How can science establish a machine quotient (MQ)?
  53. What are fundamental mathematical and cognitive problems to be solved for modeling the mind?

    Description: 60 years of difficulties in artificial intelligence, pattern recognition, neural networks, etc, can not be ignored. Fundamental mathematical and cognitive difficulties have been identified. Mathematical difficulties have been reduced to computational complexity equivalent to Gödel difficulties in logic. In every paradigm learning includes a logical step, e.g.: ‘this is a chair.’ Logic leads to combinatorial complexity (1000!), an Internet network of a mere trillion computers will not help even with moderately complex problems (100!). Cognitive unsolved problems include role of emotions in thinking (art, beautiful, music, emotions of voice), language-cognition interaction, abstract concepts (all of these are 100! to 1000! complex). Attempts to solve these questions one by one are futile: only humans have human intelligence, and we have it all. Should we give up? No, the mind solves these problems. How?

  54. Can computers exhibit the dynamics of the financial market , rather can we a) Model the financial market b) Make the computers to exhibit the same
  55. If your computer told you it was "having fun", would you believe it?
  56. Can we put the brain of a robot in the cloud? Can we put the brains of all robots in the cloud?
  57. Can robots/machines have feelings, emotions, or even love?
  58. Can programs behind robots/machines evolve like a living thing?
  59. A human’s social behavior in the cyberworld and that in the real world are often different. How to model, analyze, and make use of the relationship between them?
  60. The fast increasing application of the cyberworld makes significant impacts on human being’s life. What are the good impacts and bad impacts? Is the development and application of the cyberworld and related technologies (which lead to information explosion, connection explosion, service explosion, intelligence explosion, etc.) to be carried on and on without a limit, or is there a balance point?
  61. What is thinking? Do we already have the model of thinking? Is there one general model of thinking or are there many different models to consider?
  62. Given that machines can think, do we want them to do this for us? What are the benefits? What are the risks in the short term and long term?
  63. How do we teach computers about our concepts of right and wrong?

    Description: We all know that it is wrong to kill or hurt others, but computers would feel no regret to destroy all carbon-based life forms in order to improve their efficiency.

  64. Whether the physiological signals could reflect the psychological states efficiently?

    Description: Physiological Computing represents a category of affective computing that incorporates real-time software adaptation to the psychophysiological activity of the user. This computing method can be used to aware psychological variables, such as emotion (joy, sad), cognition (attention, cortical activation), motivation (mental effort) and mental state (psychosis, schizophrenia).

  65. The complexity of relationship between physiology and psychology (i.e. several physiological variables may be associated with several psychological elements). How to implement efficient and definite psychophysiological inference?

    Description: The internal relations among multiple physiological signals and the fusion and modeling techniques for more efficient psychophysiological inference. If these important problems are solved, Physiological Computing would prompt human-computer communication greatly.

  66. Can computer correctly understand our instructions?
  67. How can we live if we couldn’t tolerate security and privacy offenses from Internet?
  68. Can machine intelligence be as one of important ubiquitous individual intelligence (humans, machines, Cyber-I....) in the future?
  69. Is there a possibility that a dichotomy of machine and human intelligence is too difficult to be clarified in the future because they might be strongly coupled and dependent as important individual intelligence for the emergence of future 'social' intelligence?
  70. Can machines believe?
  71. Brains study brains - a self-referencing?
  72. How to exceed Turing machine-like models?
  73. Is it a general user model necessary? How to integrate various user models to make the general user model standard for intelligent personalized services?
  74. How to holistically investigate intelligence in the hyper world?

    Description: A new world, called "hyper world", is emerging by coupling and empowering humans in the social world, information/computers in the cyber world, and things in the physical world. It is sure that the intelligence is a core to make the hyper world really smart.

  75. A little but difficult problem: combinatorial optimization of words. In this optimization problem, a mainly objective is to explore those sentences that can stimulate human to get new ideas.
  76. Can we make a digital copy, i.e., a digital clone, for a person?
  77. How will the Mobile Computing change the process of Artificial Intelligence?
  78. Does a system become always smarter by integrating smart sub-systems or smart components together? If no, in what cases it becomes smarter, and in what cases it becomes not smarter even stupid? How to make a system smarter when integrating smart elements?
  79. It is sure that there are many different aspects between machine/system intelligence and human intelligence. In their merging environments, how to fuse them, i.e., how to take both their essences in problems solving? What are necessary technologies and challenging issues?
  80. Ethically, how shall we fit the developing steps of machine intelligence? / Ethically, how shall we implement the challenges from machine intelligence created by ourselves?

    Description: In the movies of AVATAR and HUNGRY GAME, you will be shakened for the real man/woman has real reactions and actions including hungry, pain, blood and death in the virtual environment which is governed by any professions. It would be horrible when the actions are realized and be applied around our sociality. In fact, we cannot block or stop the steps of the machine intelligence. What shall we to do? To change the attitude to the machine intelligence, or to strengthen our power, or to become a machine, etc….

  81. Can an electronic digital computer be conscious?
  82. Would we be justified in considering a specific software application as an independent legal person?
  83. Can a natural process (e.g., a process occurring in a vegetal or animal organism) perform computations?
  84. Is there any metric for moral values such as truthfulness, justice, love, righteousness, beauty, generosity, kindness, hospitality, etc.? Making decisions without considering these factors may result in "wrong" decisions.
  85. How can social computing help us to achieve world peace and prosperity?
  86. How can we recall things through computers?

    Description: Currently, search engine can help people search things on the internet. It is not enough compared to our daily uses. Most often we have to search things in our memory. How do we recall things? We have an amazing brain that every clue is possible to retrieve the answer. These clues include sound, logic, image, tastes, time, location and so on. Our memory is multi-view and multi-dimension. Now we have better computers to store every single media separately. How can we build a model to process them all together and satisfy people's recall needs? For example, we can input every clue we have remembered and retrieve the exact things we have forgotten. There are several questions: How to represent the recall clues? How to index the different media associated with a certain events? How to design a search algorithm to effectively give the exact answer? Which application of recall is easy to implement, e.g., maybe document retrieval first or friend name retrieval?

  87. Is intelligence an individual or a social-related attribute?

    Description: Nowadays agents can communicate, so an agent who cannot answer a question might search for someone else who can. Should we distinguish between agents who rely on their intrinsic intelligence for such tasks and those who are able to find the answer from someone else, by employing their social abilities?

  88. Is the unrestricted Turing Test a "moving target"?

    Description: The computers' performances already match those of humans in a number of tasks which assume intelligence, e.g., expert systems, IBM Deep Blue chess player or Watson Jeopardy! winner. However, each time an AI application outperforms humans in a specific domain, another domain is invoked as "still resisting stronghold of human-like intelligence", thus virtually transforming the unrestricted Turing Test accomplishment into a "moving target". Could this process continue indefinitely, of is there a moment when a computer matches the human performances in EVERY field believed to demand intelligence (does a series of Feigenbaum Tests converge to the Turing Test)?

  89. Is it rational / consistent for an agent to have as a goal "learn something in order to improve yourself as a task performer"?

    Description: An agent can chose between two direct actions with small and medium rewards respectively, but s/he knows that, if performing the action of acquiring a SPECIFIC piece of knowledge, s/he would be able to perform a third action, with a high reward. What should a rational agent do?

  90. Can machine replace the professor (teacher) in all tasks in the education process like: Creating Course Material, Preparing lesson by lesson, Generating Questions, Generating Homework, Generating Exams, Performing Assessment and Providing Feedback especially in open essay questions?
  91. Can human and machine intelligence be equally replaced and/or exchanged?
  92. Can machine intelligence be almighty (do everything)?
  93. Can machine intelligence naturally evolve?
  94. Can machines have subjective experience and learn from experience?
  95. Can machines self-control?
  96. How can machine intelligence enhance human well-being?
  97. Is there such thing as biological life? Could it be that the concept of biological life is yet another misconception, as the centrality of the earth was thought for centuries with the Ptolemaic system?

    Description: Suppose we reach the stage where self-consciousness and self-awareness can be attributed to some mechanism, e.g. some software program or some cyber-physical "thing". This machine would perceive its environment through a set of machine sensors. As for the men in Plato's cave, it is likely that what the machine would perceive through its mechanical sensors would be considered by it as a true picture of "the world" and of "life". Could then such a machine begin questioning whether its form of life is unique or just an emergent property appearing in a system designed by some programmer? Could it be that this is what we are doing here and now? Could it be then that there is no such thing as a physical world and that we are programs running in someone else's "computer"? What if programs would start writing their own programs, and these programs-of-programs would achieve self-awareness and self-consciousness? Could it be that what we call as biological life and physical world are just a layer in a complex hierarchy of virtual worlds? Who sits in the top layer then? Who's the unmoved mover, the unprogrammed programmer?

  98. Human seems a balanced system like the conservation of energy, some weaker aspects make or show some other aspects stronger. Can an intelligent system be a similar balanced system too?

    Description: A human has many different aspect capabilities and some phenomena show some aspects are weak, which could make some other aspects stronger, even outstanding. It looks human as a whole is a balanced system like the conservation of energy. How about intelligent systems? Will they have similar phenomena or how we simulate these phenomena in intelligent systems?

  99. How will "growing" systems for general intelligence look like?

    Description: Rich intelligence (such as general AI) comes from rich and complex experience, hardly suitable for per-scripting, plus requires ongoing growth. Systems may learn faster, but they still have to learn from us, and we remain slower. Will they accompany us for years as they "grow up"? Will they fast forward through years of video? Will we have a library of base characters that we then customize with less time?

  100. Thinking about "Do I 'feel' like Watson is actually intelligent?", I wonder how much "creativity", or maybe even "personality", a system needs before we perceive it as intelligent, no matter how good it answers questions? Maybe even further, do we need to perceive it as self-aware before perceiving it as intelligent?
  101. Can machines have mind?
  102. Can a cashless society eliminate corruption, influence peddling, insider trading, tax evasion, and other economic crimes?
  103. How will machines achieve human-like autonomy?
  104. Is the intelligence in "Artificial intelligence" a real intelligence or it is something which is called as intelligence?
  105. Can machines have emotions?
  106. What are the roles of cognition and emotion in thinking machines?
  107. Is cloud-computing ready to solve information-overload problem?
  108. Are existing web intelligence techniques matured to combat crimes in Cyberspace?
  109. Are social networking platforms affecting our social interactions and behaviors?
  110. Are social networking platforms really social?
  111. If the intelligence of computers transcends that of humans, how can we present us from being dominated by the computers?
  112. How can I be sure that I am communicating with right person when I am using Internet especially social networking platforms etc?
  113. As we know, human have excellent immune system against diseases. How to design intelligent machines and systems which have similar immune functions like human? What are the challenges? Are the ubiquitous intelligence computing technologies and other technologies ready to really tackle this problem?
  114. Could simple algorithms trained on large amounts of data offer a behavior that is accepted as "intelligent", but we still remain unable to really explain or understand how intelligence emerges?
  115. Is blacklisting an effective punishment for deviant ontologies?
  116. Is Artificial Intelligence beneficial to humanity?
  117. Can we argue with a machine and can machines argue with each other?
  118. On the relationship between "Human Intelligence" and "Machine Intelligence" -- Are they always mutually promoting each other, or will the latter cause the former to degrade?

    Description: It is no double that "Human Intelligence" helps promote the "Machine Intelligence", as evidenced by the successful history of computing/IT development. However, it is unclear if the other direction holds or not. Along with the ever increasing "machine IQ" resulted from the fast development of information technology (including, e.g., cloud computing, big data, quantum computing etc.), do majority of the human beings (direct/indirect IT users) become smarter, or actually more dumb because they're getting lazier and become more dependent on IT appliances and tools? Can the positive impacts brought up by the fast IT development always outweigh the negative impacts on us (as human beings) and our society, or quite often the opposite direction?

  119. The questions are about the role of the distributed agents' knowledge sharing in NP- hard problem solving.

    Description:: Let us assume that a team of agent has to solve an NP-hard search problem. Agents can exchange the knowledge they possess about the area of location of optimal solution(s). Let us assume, for simplicity, that their knowledge is consistent (no contradiction!). No agent is capable to solve efficiently the problem alone while using only own knowledge. Let the agents use a distributed version of branch-and-bound search algorithm or some other one.
    1. Do there exist a protocol (agent interaction protocol) for distributed NP-hard problem solving with reduced theoretical complexity for given distribution of partial knowledge among the agents that are capable to share their current knowledge (including that received in solution process) using the aforementioned protocol?
    2. Does it possible to formulate some minimal requirements to the agents' knowledge distribution to find the optimal solution(s) of an NP-hard problem efficiently?
    3. In general, what new, in comparison with classical complexity-related results including Turing's results, can be provided with distributed agents' knowledge exchange intended for NP-hard problem solving (if any)?

  120. Is it possible that some aspects of human intelligence, such as emotions or consciousness, are based on currently unknown quantum mechanisms?
  121. Can robot have their own social behaviors? Can they construct their own social network?
  122. Is there possible the robot have ability to think independently and then cause it out of control?
  123. When can the artificial intelligence filter out the useless or incorrect data from flood information on the Internet?
  124. Can data science combined with neurosciences solve the mind body problem?

    Description: The mind body problem is one of the oldest philosophical queries of all time and likely assumed to have no verifiable answer. But with recent advances in machine learning and neurosciences we can tell with great accuracy what a person is thinking when certain areas of the brain "light-up". Can data science combined with neuroscience, psychology, philosophy, linguistics, etc. come together to solve the mind body problem?

  125. When can a robot replace the role of the airplane's flight attendant or even pilot?
  126. When can the driving/safety control system in a vehicle like that in an airplane such that the probability of vehicles' accidents is as low as that of air flight?
  127. What is the difference between Turing test and Socratic method?

    Description: For me, revival of Turing test means a new Platonism for pursuing human intelligence with machine intelligence.

  128. When can cyber intelligence and biotech copy memory from human brains and edit the new memory and put into human brains?


Sixty years ago, Alan M. Turing, raised the essential question, "Can machines think?" in his article "Computing Machinery and Intelligence", which can be regarded as one of seeds for AI and other intelligent computing. He believed machines could think and also believed that "at the end of the century the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted". Actually, since the end of the last century, the essential question has become "Can things think?" as proposed by the TTT consortium at MIT.

Computer and networks have brought profound changes not only as revolutionary information technologies but also a digital space for creating a new world called cyberworld, whose impacts to our human beings have just begun. Following the information explosion, we are experiencing in connection explosion and service explosion. Sooner or later we will face the next one - Intelligence Explosion! The initial signs of such intelligence explosion have been appearing, such as Web Intelligence (WI) as one representative development of Web, AI, agent technology, neural networks, nature-inspired computing, cloud computing and so forth, and Ubiquitous Intelligence (UI) because of active media, sensor technology, embedded devices, pervasive computing, smart objects, Internet of things, etc.

The Important Questions

Perhaps no single person can do all these, but the intelligence exists in the crowd with their collective efforts. Therefore, the open forum is trying to offer a common platform for all of us to work together to think about the basic questions and further figure out Top 10 Questions in Intelligent Informatics/Computing (TOP10Qi).


Top10Qi Open Forum will be organized with a series of events/outputs by dividing into four stages:

Call for Your Participation

The success of the Top10Qi Open Forum will greatly depend on your participation and voluntary work as well as your comments. Hence, besides calling for TOP10Qi, we also sincerely call for your support and joining the special event.

If you have any comments or are interested in becoming a committee member, please feel free to send an email (with a biography when applying for a committee member) at top10Qi@gmail.com.


Jianhua Ma, Hosei University, Japan
Jiming Liu, Hong Kong Baptist University, HK
Ning Zhong, Maebashi Institute of Technology, Japan

Working Committee:
Runhe Huang, Hosei University, Japan
Erzhong Zhou, The International WIC Institute, Beijing University of Technology, China
Yuxin Meng, City University of Hong Kong, Hong Kong
Juzhen Dong, Web Intelligence Lab., Japan

Technical Committee:
Jeffrey Bradshaw, UWF/Institute for Human and Machine Cognition, USA
Nick Cercone, York University, Canada
Phalguni Gupta, Indian Institute of Technology, India
Sven Koenig, University of Southern California, USA
Toyoaki Nishida, Kyoto University, Japan
Vijay Raghavan, University of Louisiana at Lafayette, USA
Andrzej Skowron, Warsaw University, Poland
Bin Hu, Lanzhou University, China and ETH Zurich
Xindong Wu, University of Vermont, USA
Fabio Massimo Zanzotto, University of Rome "Tor Vergata", Italy
Chengqi Zhang, University of Technology, Sydney, Australia
Li Weigang, University of Brasilia, Brazil
Siti Mariyam Shamsuddin, Universiti Teknologi Malaysia, Malaysia
Hedia Mhiri Sellami, University of Tunisia, Tunisia
Christian Becker, Mannheim University, Germany
Julien Bourgeois, Carnegie Mellon University, USA
Zaki Brahmi, Manouba University, Tunisia
Jiannong Cao, Hong Kong Polytechnic University, HK
Jinjun Chen, University of Technology, Australia
Zhong Chen, Peking University, China
Marco Gori, University of Siena, Italy
Bin Guo, Northwestern Polytechnical Univ., China
Sumi Helal, University of Florida, USA
Frank Hsu, Fordham University, USA
Hui-Huang Hsu, Tamkang University, Taiwan
Robert C. Hsu, Chung Hua University, Taiwan
Chung-Ming Huang, National Cheng Kung University, Taiwan
Deshuang Huang, Tongji University, China
Runhe Huang, Hosei University, Japan
Sozo Inoue, Kyushu University and DFKI, Japan
Yichuan Jiang, Southeast University, China
Qun Jin, Waseda University, Japan
Qing Li, City University of Hong Kong, HK
Tianrui Li, Southwest Jiaotong University, China
Yinsheng Li, Fudan University, China
Fuhua (Oscar) Lin, Athabasca University, Canada
Xiangfeng Luo, Shanghai university, China
Huan Liu, Arizona State University, USA
Lu Liu, University of Derby, UK
Christian Muller-Schloer, Leibniz Univ. Hannover, Germany
Huansheng Ning, Beihang University, China
Gang Pang, Zhejiang University, China
David M W Powers, Flinders University, Australia
Wolfgang Reif, University of Augsburg, Germany
Frode Eika Sandnes, Oslo University College, Norway
Hartmut Schmeck, Karlsruhe Inst. of Tech., Germany
Timothy K. Shih, National Central University, Taiwan
Vincent S. Tseng, National Cheng Kung University, Taiwan
Lai Tu, Huazhong Univ. of Science and Technology, China
Theo Ungerer, University of Augsburg, Germany
Cho-li Wang, The University of Hong Kong, HK
Ying-Hong Wang, Tamkang University, Taiwan
Laurence T. Yang, St. Francis Xavier Univ., Canada
Daqing Zhang, Institut Telecom SudParis, France
Yanchun Zhang, Victoria University, Australia
Qiangfu Zhao, The University of Aizu, Japan
Peidong Zhu, NUDT, China
Martin Dimkovski, York University in Toronto, Canada
Vincenzo De Florio, University of Antwerp, Belgium
Zhiguo Gong, University of Macau, Macau
Jingsheng Lei, Shanghai Univ. of Electric Power, China
Ramon Lopez de Mantaras, Spanish National Research Council, Spain
Leonid Perlovsky, Harvard University, USA
Bo Yang, Univ. of Electronic Science and Technology, China
Shusaku Tsumoto, Shimane University, Japan
Selim Erol, Vienna University of Technology, Austria
Shaozi Li, Xiamen University, China

WI 2012 Program Committee Members
IAT 2012 Program Committee Members
AMT 2012 Program Committee Members
BI 2012 Program Committee Members
ISMIS 2012 Program Committee Members

Cooperation with Web Intelligence Consortium and IEEE-CS TC on Intelligent Computing Informatics