Joining the 2020 IEEE/ITU International Conference on “AI for Good”

Great honored to join the 2020 IEEE/ITU International Conference on “AI for Good” as the Master of Ceremony as well as a member of the organizing committee.

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Appointment as an advisory committee member on the Sustainable Smart City Partner Program @NTT

I’m thrilled and honored to be appointed as an advisory committee member on the Sustainable Smart City Partner Program @NTT

Privileged to work for the smart city with such an outstanding group of distinguished people.

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Interviewed by Professor Cécile Dejoux from Paris for the MOOC, “AI for All”

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Talk on “Society 5.0: the future of AI and Robots” at the Italy-Japan Workshop 2019

Prof Paolo Dario from Scuola Superiore Sant’Anna

I enjoyed talking about “Society 5.0: the future of AI and Robots” at the Italy-Japan Workshop 2019 on “the Robots and the Future” @Waseda University.

I’m honored to Join such distinguished scientists and Engineers as Prof Paolo Dario from Scuola Superiore Sant’Anna (photo: right) and Prof Toshio Fukuda, President of IEEE (photo: left)😃.

Prof Toshio Fukuda, President of IEEE

Italy-Japan Workshop 2019

Italy-Japan Workshop is an initiative, supported by the Embassy of Italy in Japan, and the Association of Italian Researchers in Japan, in which a specific theme related to robotics is discussed and analysed involving the government, universities, research centres, and industries of both countries. The idea is to brainstorm around important issues in modern Robotics using a Participatory Design approach, involving all stakeholders of both countries.

Italy-Japan Workshop has been organised since 2001 by Waseda University, one of the most important scientific partners for Italy, in collaboration with Scuola Superiore Sant’Anna. In this event, distinguished Italian and Japanese speakers share their experiences and their vision, while a selected number of Japanese and Italian companies are yearly invited to show and demonstrate their products.

The theme of this year, on the occasion of the re-launch of the collaboration between Sant’Anna and Waseda, is “Robots and the future”, and the technological innovation of the last decades will be explored, analyzing strategies and winning methods of methodological reform, for to identify the new technical, but also social, challenges that Robotics will face in the coming years.

It is important to underline the multidisciplinary, indeed transdisciplinary nature of this workshop. Unlike previous years, in fact, where a focus has been privileged at the level of robotic applications in specific fields, to increase and improve the ties of academic collaborations in the development of ad-hoc applications in various sectors, starting this year, in harmony with the times of technological innovation that sees robots increasingly present in everyday life, it was decided to explore the relationship between robot and man, starting from the basic mechanisms, often inspired by nature, of Leonardo Da Vinci’s works and of the great scientists and naturalists of his time.

This workshop marks the beginning of a new cycle in which issues related to man-robot symbiosis will be explored and explored, in view of a future society where robots will no longer be controlled by expert technicians and relegated to the industrial sector, but will live and be of concrete help in carrying out the modern man’s daily activities.

Japanese Humanoid, Wabot-2 playing the piano in 1984

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Talk on “the future of AI & Robots” @IEEE Press Seminar

Great honored to talk about “the future of AI & Robots” @IEEE Press Seminar

After introducing “the complexity model of communication” as a theoretical framework for a deeper understanding of the social impact of AI, I demonstrate the Society 5.0 for SDGs within a Japanese context.

I investigate the opportunities and risks of AI from my ongoing four projects, “robot engagement”, “AI and global communication”, “Global AI Narratives and “Youth and AI” project.

To a brief summary of both theoretical and empirical approaches, AI could provide diversity and inclusion for the community well-being, however AI could also create new risks of exclusion and discrimination.

For the sustainability of human societies with AI, I give some suggestion which I call “Human First Innovation”, that is, human first approach, cross-discipline innovation and self-creation.

I hope this study could help to understand the complexity and dynamism on the process of the paradigm shift of a global community in the AI age.

 

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Talk on social impact of AI @IEEE TEMS Innovation and Entrepreneurship in Zhejiang University, Hangzhou, China

My first visit in China 🇨🇳 Enjoyed talking about social impact of AI @IEEE TEMS Innovation and Entrepreneurship in Zhejiang University, Hangzhou in China.
Many thanks to our moderator, Neil Sahota for his great support on our panel!

Special thanks to Andy Chen, President of IEEE TEMS for his kind invitation😃

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Appointment as an expert advisor of the AI Impact Alliance

I’m honored and thrilled to be appointed as an expert advisor of the AI Impact Alliance with such distinguished scholars as Yoshua Benjio, Pioneer of AI. Congratulations on the 2018 ACM A. M. Turning Award.

 

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Just published: my article entitled “the Opportunities and Risks of AI” in WHITE PAPER Information and Communications in Japan by Ministry of Internal Affairs and Communications

On July 9th, 2019.  My article entitled “the Opportunities and Risks of AI” has been just published in the WHITE PAPER Information and Communications in Japan by Ministry of Internal Affairs and Communications (in Japanese)

 

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Interviewed by Stephen Ibaraki, ACM

 

On June 20th, 2019.  I was interviewed by Stephen Ibaraki, the founder of UN ITU AI for Good Global Summit.

I talked about my recent interview with Prof. Yoshua Bengio, MILA and how I think about the AGI and the future of AI.

Stephen also asked me about my childhood as well as higher education I had among Japan, US and UK and how I adapt to cultural differences between Japan and the West.

I also talked about my current cross-cultural and cross-disciplinary projects on social impact of AI and the potential of AI for Good.  I’ve been working for some different collaborative projects in US and UK such as CFI, University of Cambridge, Columbia University and Harvard Berkman Klein Center for the Internet & Society.  Finally I talk about the future work.

After all, it became long interview over 40 minutes but I really enjoyed talking with Stephen and I really appreciate his great support!!

 http://stephenibaraki.com/acm/interviews…

 

 

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Interview with Yoshua Bengio, Pioneer of AI

Prof. Yoshua Bengio at the MILA

On June 7th, 2019 at the MILA (Montreal Institute for Learning Algorithms) in Montreal, Canada, I conducted my interview with Professor Yoshua Bengio, who is one of the pioneers of AI (Artificial Intelligence).  He is well-known as the “father of AI” for his great contribution to developing so-called deep learning.  He has received the 2018 ACM A.M. Turing Award with Geoffrey Hinton and Yann LeCun for major breakthroughs in AI.

In my interview, I asked him about the possibilities of AGI (Artificial General Intelligence), biased data, people’s concerns about GAFA (Google, Amazon, Facebook, Apple) and China, the opportunities and risks of AI and the future of AI.  All these questions are based on my previous experiences in the University of Cambridge as well as many international summits and conferences on AI I have been invited to recently. 

Bengio is also noteworthy because he chooses to remain as an academic, staying at the University of Montreal as head of the MILA, while other AI leaders such as Geoffrey Hinton have left academia and now work for Google.  Bengio continues to contribute to teaching students as well as engaging with local communities. He believes the education of future generations and people’s engagement with AI is crucial for the creation of a better society including AI. This is because he is aware of not only the opportunities but also the risks of AI.  As he owns his startup, so-called Element AI, he is instrumental in building a bridge between academia and the business world.  

This is my interview with Yoshua.

The Road to AGI

Yoshua Bengio           Did you have some questions for me?

Toshie Takahashi        Yes, of course.  Thank you for taking the time.  I’d like to ask you about AGI.

YB             Okay.

TT              I watched some of your videos and I understand you are very positive about AGI.

YB             No.

TT             No? I thought you showed a…

YB             I’m positive that we can build machines as intelligent as humans, but completely general intelligence is a different story. I’m not positive as to how humans might use it because we’re not very wise.

TT             Okay. So can you show a road map of how you could create AGI?

YB             Yes, the one I have chosen to explore.

TT             I spent some time in Cambridge, and some scholars, for example Professor John Daugman, the head of Artificial Intelligence Group at the University of Cambridge, said that AGI is an illusion created by science fiction because he said that we don’t even understand a single neuron so how can we create AGI?

YB             Yes, I disagree with him. 

TT             Okay, so could you tell me about that?

YB             Sure. Having worked for decades on AI and machine learning I feel strongly that we have made very substantial progress, and in particular we have uncovered some principles, which today allow us to build very powerful systems. I also recognise that there’s a long way towards human level AI, and I don’t know how long it’s going to take. So I didn’t say we’ll find human level AI in five years, or ten years or 50 years. I don’t know how much time it’s going to take, but the human brain is a machine. It’s a very complex one and we don’t fully understand it, but there’s no reason to believe that we won’t be able to figure out those principles.

TT              I see. Mr. Tom Everitt at DeepMind said that he could create AGI in a couple of decades, maybe 20 or 30 years.  Not too far in the future.

 YB             How does he know?

 TT              I don’t know. I asked him but he didn’t answer it.

 YB             Nobody knows.

 TT              Nobody knows. Yes, of course. When I met Professor Sheldon Lee Glashow, a Nobel Prize winning American theoretical physicist, he told us that we won’t have AGI. Or even if we have it, it’d be very far away.

 YB             Possibly, so we don’t know. It could be ten years, it could be 100 years.

 TT              Oh really?

 YB             Yes.

 TT              Okay.

 YB             It’s impossible to know these things. There’s a beautiful analogy that I heard my friend Yann LeCun mention first. As a researcher, our progress is like climbing a mountain and as we approach the peak of that mountain we realise there’s some other mountains behind.

 TT              Yes, exactly.

 YB             And we don’t know what other higher peak is hidden from our view right now.

 TT              I see.

 YB             So it might be that the obstacles that we’re currently working on are going to be the last ones to reach human level AI or maybe there will be ten more big challenges that we don’t even perceive right now, so I don’t think it’s plausible that we could really know when, how many years, how many decades, it will take to reach human level AI.

 TT              I see.  But some people also say that we need a different breakthrough to create AGI. We need a kind of paradigm shift from our current approach.  Do you think that you can see the road to reach if you keep on with deep learning? So this is a right road?

 YB             We have understood as I said some very important principles through our work on deep learning and I believe those principles are here to stay, but we need additional advances that are going to be combined with things we have already figured out. I think deep learning is here to stay, but as is, it’s obviously not sufficient to do, for example, higher-level cognition that humans are doing. We’ve made a lot of progress on what psychologists call System 1 cognition, which is everything to do with intuitive tasks. Here is an example of what we’ve discovered, in fact one of the central ideas in deep learning: the notion of distributed representation. I’m very, very sure that this notion will stay because it’s so powerful.

 TT              Wonderful! I’m happy to hear that.

 YB             Yes.

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