The future of Artificial Intelligence

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1 The future of Artificial Intelligence The Role of Web and Emerging Technologies Babak Loni May 2011 Abstract In this paper we will try to predict the future of artificial intelligence by relying on the current researches of AI. Following current trends of AI and intelligent applications, reveals that the world is going to introduce highly intelligent and personalized machines that can interact with human. We will argue that techniques in natural languages processing highly influence the future of AI. In fact natural language understanding is the bottleneck of creating intelligent interacting machines. By tackling some challenges in this area of AI together with intelligent techniques such as personalization and emotion recognition on the back of powerful infrastructure of the Web, we will see highly intelligent machines in near future. 1 Introduction Today computers and devices are going to be more and more intelligent. It is not surprising to see computer systems that can play chess, predict weather, recognize your voice, understand images, process natural language and many other abilities which need some sort of intelligence. The question is now how intelligent a computer system can be? Can a computer system be more intelligent than human? If yes then is it an opportunity for human or it s a treat? Many studies have been done to predict the future of Artificial Intelligent (AI) [1, 9]. Professor Hugo, the head of artificial brains group in Utah University, in his book The Artilect war [4] said: I m very worry that in the second half of our century the consequence of the work that I do, may have such a negative impact upon humanity that I truly fear for the feature. Vernor Vinge the author of The Singularity [14] also believes that acceleration of technologies will lead to creating machines with greater than human intelligence ability and a super-humanism era. On the other hand Mark Humphyrs, in his paper [6], argues that AI is a sample of science that has been deviated from its main goal. He has 1

2 a pessimistic view about future of AI. He believes that even if it became possible for human to create truly artificial intelligence (which in his definition is machines that can think like human), then at least it is not possible to create such machine in the current century and today s technologies are quite weak to be able to innovate such a great machines. We however have different view concerning the future of AI. Instead of a fanciful view, we discuss about the research fields that highly influence the future of AI. We would like to call the Web as a phenomenon that highly influences the future of AI. In fact by emerging social networks and intelligent applications on the web the world is going to build highly intelligent applications which finally would lead to creating human-like machines in near future. We will argue how that s possible and how intelligent these machines can be. By emerging the web and its rapid growth rate, a huge source of knowledge have been created which can be used to create the next generation of intelligent machines. This machines that we would like to call them interacting machines are such intelligent that can interact with human just like human. You can talk to these machines and ask them any question you need, you can manage all your personal and daily activities by consulting with these machines and they can even be a friend-like machines that you can even share your secrets with them. We believe that the underlying techniques and technologies for creating such machines have been already created and by overcoming some current challenges in artificial intelligence in near future we will see such intelligent machine. In this paper we first give an introduction to the concept of intelligent and review the current challenges in AI. In section 3 we will argue about the future of AI in accord to current researches in AI and finally we will discuss whether the future of AI is an opportunity or it s a threat for human. 2 Intelligence Before we discuss whether a computer can be as intelligent as human or not, we need to first define the meaning of intelligence. Different definitions for intelligence have been proposed. The most common definition of intelligence is the ability of abstract thought. However, abstract though is usually referred as the abilities of learning and reasoning. Some other human abilities such as emotional intelligence sometimes are also considered as a factor of intelligence [11]. Therefore if human succeeded to create machines which can do learning and reasoning then it s possible to create machines which are at least as intelligent as human. But the problem is not that simple. There is an open problem in artificial intelligence and that s the problem of artificial consciousness. In fact what makes humans different from intelligent machine is consciousness. The question is that is it necessary for an 2

3 intelligent machine to be conscious in order to be as intelligent as human or not. Many studies discussed whether it is possible to create artificial consciousness or not. Mark Humphrys [6] believes it s not possible to create artificial intelligence without artificial consciousness. He believes consciousness is an important factor for a machine to be truly intelligent. AI researches have not yet came to a common achievement concerning whether it is possible to create an intelligent machine which is conscious or aware of itself or not. We however, argue that consciousness and intelligence are completely two different concepts. Regardless of being conscious or not, an intelligent machine need not to be necessarily conscious to be more intelligent than human. On the other hand intelligent only depend on the primitive factors of intelligence which are abilities of learning and reasoning. Peter Mind in his paper [10] provides a simple example for distinguishing between intelligence and consciousness. He argues that intelligence is a kind of ordinal scale concept whereas consciousness is a kind of you have it or you don t have it thing. In other words, it s possible to say something is more intelligent than other but it s not possible to say something is more conscious than other. In fact what makes human more intelligent than animals is not being conscious or self aware but it is simply having higher amount of intelligence. Researches on animal intelligence also confirm this claim that intelligence does not need consciousness. Paul Patton [12] argues that animals are also conscious as humans are, but they are not as intelligent as human. The abilities of learning and reasoning are two main components of intelligence. It is not obvious for human whether they can create self-aware or conscious machines. But evidences show that it is possible for human to create machines that have higher abilities of learning and reasoning compare to human. We therefore focus on how the current researches of AI lead to create machines which are more intelligent than human, i.e., they would have higher abilities of learning and reasoning. Therefore in spite to the view of Humphrys [6] which believes AI is not achieved yet because of unsuccessful attempt on artificial consciousness, we think on the other hand, that the reason lies on the fact that current intelligent machines still are not intelligent enough to learn and reason like human. According to our view the bottleneck of creating super-human machines is the lack power of learning and reasoning. In other words by improving the learning and reasoning abilities, we can create machines that are more intelligent than human. An ability which we want to call it unlimited learning is the key feature that should be reached to create machines with higher intelligence. Unlimited learning means that the machine can learn any content given to it regardless of the type of knowledge the content has. In addition to this ability, a comprehensive source of knowledge is also needed to teach these 3

4 machines. In the next section we will show how the current researches of AI will lead to create such machines. 3 Future of AI: human-like intelligent interacting machines The best way to consider the future of AI is to consider the current researches on AI. Branches of AI which is about Machine Learning together with powerful infrastructure which have been evolved by the web, are key factors which highly influence the future of artificial intelligence. We believe that the future of AI is concern with creating machines that can interact with human and this can be concluded from the direction of current researches of AI. Therefore the ability of higher intelligence than human will be appeared in human interacting machines 1. We will show how human interacting machines can reflect the long desire of human to create artificial intelligence. The study to build interacting machines backs to early 1960s when Green et. al. [5] tried to made a question answering (QA) system. They build a simple machine which was able to answer question written in natural language which was about the baseball league matches over one season. The study for building question answering systems was a major attempt to create human-like interacting machines. However, due to lack of enough back-end knowledge most of early QA systems were unsuccessful. There was not a comprehensive source of knowledge bases which can be used to teach intelligent machines. The study to build human interacting systems lay dormant for two decades till emerging the web. The huge amount of data on the web in one hand and the need to querying the web on the other hand brings again the study of QA interacting systems into focus. In 1999 the first successful QA system namely START [7] was created. This system is able to answer many questions in natural language. The TrueKnowledge 2 was another successful QA project which was launched in Although none of these systems are perfect enough to be able to answer any open-domain natural language questions, but there are enough evidences which shows that in very near future human will be able to create machines that can process free form text in the web, understand it and interact with human [13]. As we stated before a key feature to build truly interacting machines is the ability of unlimited learning and a comprehensive source of knowledge. By emerging web the second issue has been solved. Web as Tim Berners Lee, 1 We mean by interacting machines an intelligent application which can interact with human. Physical hardware of these machines are not really a big deal as robotic already solve this issue

5 the founder of it states [2], is a powerful source of knowledge that can be exploited to build intelligent applications. Therefore if machines be able to understand documents in the web as humans do, and be able to reason the contents of documents then the main challenge to build human interacting machines will be resolved. Consider only Wikipedia, a subset of web documents and consider a machine that can learn any content on it. If a machine can understand all the content in it, then imagine how powerful this machine will be. It will be a machine that has all knowledge about the world, people, events and etc. Understanding all documents in the web can give this machine even more power. If that be possible then the power of such machine will exponentially improve by learning from new documents and this technique is in fact what we called the ability of unlimited learning. Now the question is that is it possible to create applications to understand the contents of documents on the web? Current researches on natural language processing succeeded to understand part of content in a web document, those contents which are represented in structured format [3]. Human have not been succeeded to build machines that understand natural language content completely but if that happens then a big step to build interacting machines will be passed. Understanding a natural language document is what we would like to call the bottleneck of building truly artificial intelligence. Researchers developed several statistical learning approaches which can understand part of knowledge available in a web document [3]. It is expected that by developing more powerful mathematical infrastructure, in very near future human will be succeeded to develop approaches to fully understand the content of a document. Other challenges to build human interacting machines have been already resolved. Human succeeded to transfer text to speech and vise versa. Therefore an interacting machine can transfer its inferred knowledge into speech and talk to human. On the other hand many personalization techniques on the web have been evolved that enables document to provide the user information that most likely match to his interests and tastes. Combing personalization techniques with interacting machines will create intelligent machines that are not only intelligent but also can learn your interest and be customized according to your interest. In this way it is not far away to build machines you can consult with them. Furthermore, recently researchers developed emotion recognition systems which enable machine to have emotion similar to human. Imagine a personalized interacting system which also has emotion: yes! a machine can behave like your friend. You can even share your emotions with these machines. It is not far away for human to build such machines. Machines are going to be more and more intelligent. Personalization techniques together with emotion recognition systems can even create more intelligent machines. By 5

6 tackling the most important challenge of interacting machines, the ability of unlimited learning, we will see amazing intelligent interacting machines in near future. 4 Intelligent Machines: Opportunity or Threat We believe there is no reason to be worry about the direct threat of intelligent interacting machines. As long as human cannot create machines which are conscious or self-aware, these machines cannot be a threat for human and no super-humanism can happen. As we described earlier this interacting machines do not need to be selfaware, it not need to be consciousness and it is not a threat for human since its huge intelligence does not lead to be necessarily consciousness. Therefore there is no need for intelligent machines to compete with human. Since there is no motivation for machines to compete with human, there is no such threat from intelligent machines as it stated in Singularity theories [13, 8]. At least the machines that we talked about in this paper have not such a threat for human. It is in fact an opportunity for human if we can create such intelligent machines. Many human tasks can be left to these machines and many human challenges can be solved by consulting with these machines. Of course creating such machines can influence the social behavior of human and lead to some kind of individualism. If interacting machines became such intelligent and personalized, a new competitor for human will be appeared in the case of communication. References [1] Anthony J. Bell. Levels and loops: the future of artificial intelligence and neuroscience, [2] Tim Berners-Lee, James Hendler, and Ora Lassila. The Semantic Web (Berners-Lee et. al 2001). May [3] Chia-Hui Chang, Mohammed Kayed, Moheb Ramzy Girgis, and Khaled Shaalan. A survey of web information extraction systems, [4] Hugo de Garis. The Artilect War: Cosmists vs. Terrans. A Bitter Controversy Concerning Whether Humanity Should Build Godlike Massively Intelligent Machines [5] B.F. Green, A.K. Wolf, C. Chomsky, and K. Laughery. Baseball: An automatic question answerer. In Proceedings Western Computing Conference, volume 19, pages ,

7 [6] Mark Humphrys. Ai is possible.. but ai won t happen: The future of artificial intelligence. Published in Neo magazine, June [7] Boris Katz, Sue Felshin, Deniz Yuret, Ali Ibrahim, Jimmy Lin, Gregory Marton, Alton Jerome McFarland, and Baris Temelkuran. Omnibase: Uniform access to heterogeneous data for question answering. In In proceeding of the 7th international workshop on applications of natural language to information systems (NLDB), [8] Ray Kurzweil. The Singularity Is Near: When Humans Transcend Biology. Penguin (Non-Classics), September [9] John Markoff. The coming superbrain. Published in The New York Times Magazine, [10] Peter Mind. Consciousness and intelligence. Published in On Philosophy Website, June URL: [11] Ulric Neisser, Gwyneth Boodoo, Thomas J. Bouchard, Wade A. Boykin, Nathan Brody, Stephen J. Ceci, Diane F. Halpern, John C. Loehlin, Robert Perloff, Robert J. Sternberg, and Susana Urbina. Intelligence: Knowns and Unknowns,. American Psychologist, 51(2):77 101, February [12] Paul Patton. One world, many minds: Intelligence in the animal kingdom. Published in Scientific American Magazine, December URL: [13] José Luis Vicedo and Diego Mollá. Open-domain question-answering technology: State of the art and future trends, [14] Vernor Vinge. The singularity. Presented in VISION-21 Symposium sponsored by NASA Lewis Research Center and the Ohio Aerospace Institute, March