Sami Haddadin and myself are co-rapporteurs in the AI HLEG for the group working on « World Class Resarch ». To improve our section we would like to have your input on a number of questions. Feel free to reply only to some of them. Short messages and longer thesis will be appreciated equally.
- Specific examples of the benefits of AI to the citizens where research is needed
- Specific examples of where the lack of data has been an issue for doing research
- Examples of successful industry-academia-government research collaboration models
- Specific and concrete research topics (short, medium and long term)
Thanks!
Fredrik
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In reply to 1. The combination between by Anonymous (not verified)
Thank you Laurentiu, yes, AI-robotics is a fruitful and important research area. In the current version of our document, this is lifted as one important and strong area for Europe.
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In reply to Hello , Mr Heintz by Anonymous (not verified)
Thank you Kai. I completely agree with you. Smaller languages, including my native Swedish, are important to European research. We have included the following opportunity "The multi-cultural, multi-language reality of Europe provides an ideal opportunity to explore alternative methods and theories for learning and perception that focus on small data and on the semantics of data."
Best regards,
Fredrik
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In reply to Dear Fredik, by Anonymous (not verified)
Thank you Andres, I agree, health is really important and to coordinate with existing initiatives is important to get the most out of the work.
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In reply to 1) A benefit would be to have by Anonymous (not verified)
Thank you Pinar. Detecting and mitigating bias in data is an important research topic. Whether truly bias-free data/systems are possible, I'm not sure about. In any case, removing unwanted and unintended bias is crucial. There are also interesting questions related to the normative aspects of di-bias data. Should data represent the true world or the world we want? In the later case, who should decided which world we want? What if different people/groups want different worlds?
The questions of accountability, traceability and transparence are important and are covered at great length in our work (but not explicitly in the part on World Class Research that I am working on).
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Hi,
We are trying to predict some labels in the area of palntation (Avocado, Mango). My answers will refer to this subject.
1. Specific examples of the benefits of AI to the citizens where research is needed
- If we could provide future information on outputs (size, quality) for fruit growers it would help them better plan the distribution to the market and negotiate on prices.
2. Specific examples of where the lack of data has been an issue for doing research
- We experience a problem when we want to ןמאקערשאק information from different sources, such as soil type, weather, irrigation , size of the plot and yield for 20 years.
3. Examples of successful industry-academia-government research collaboration models
- None
4.Specific and concrete research topics (short, medium and long term)
- We are trying to predict some labels in the area of palntation (Avocado, Mango). My answers will refer to this subject.
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Dear Fredrik,
Your questions are very interesting and valuable,
I can suggest two interesting research domains, question 4:
Misinformation, using IA to tackle FakeNews and misinformation, as you know this is an hot topic in EC at the moment; I think this is also a new interesting topic at scientific level, including synergies in many different domains: IA, but also data science, complex system physics, social network and social media studies
IA and 5G, this is a valuable research domains, with deep business impact, in two directions how use IA to support network configuration in 5G; but also how 5G can support IA (with a strong usage of edge computing to solve computational problems at local level)
Naturally, both aspects need more investigation and, even, more space to be explained better; but for the moment these are my 2cents
Ciao Francesco
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In reply to Dear Fredrik, by Norbert JASTROCH
I agree that these two topics have high relevance for many domains, for instance for IT Services or the Internet of Things. At IBM Global Technology Services, we have applied AI Technologies to the service lifecycle, with good results but some unique challenges.
(1) One of the big challenges e.g. of incident management in complex IT systems is separating signal from noise, determining what are 'true, actionable' events and determining the best remediation. Data is generally very noisy, and a balance needs to be struck between outright automation and supporting subject matter experts to resolve the most complex problems. All approaches require a taxonomy of the problem space, and this is directly related to (2).
(2) Managing the lifecycle of organizational knowledge is a key challenge for all knowledge-based organizations, in our case the community of IT experts. This has both technological implications (like the role of ontologies, standardizing ontologies and federating them across domains), as well as social ones (expert engagement, social curation of knowledge). Acceptance of AI generated advice is directly related to transparency or 'explainability'.
We have published our insights in a short monograph ("Transforming the IT Services Lifecycle with AI Technologies")
https://www.springer.com/de/book/9783319940472
If used in the right way, AI can have a huge impact on the two areas you point out, but much more research is required. We are still at the beginning.
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Dear Fredrik,
my suggestion is research into
(1) the management of complex systems and
(2) the interrelation between knowledge and innovation.
Regards, Norbert
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Hi Fredrik, All,
Here are some of my thoughts with regard to the questions you put up:
1. Specific examples of the benefits of AI to the citizens where
research is needed
In order for AI to be fully trustworthy, it must be explainable.
The ML hype today is fine, but ML usually lacks automated explanation.
It can leave end users puzzled.
2. Specific examples of where the lack of data has been an issue for
doing research
All areas where regulations such as GDPR restrict the usage of data. Take, for instance, pre-school education (a very sensitive area).
4. Specific and concrete research topics (short, medium and long term)
XAI, XAI and XAI :)
Regards,
Vladan
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In reply to 1./4. Explanations in machine by Anonymous (not verified)
Thank you Marco,
I agree that explainability should help people understand what they can do in order to influence the outcome. A special thanks for the refernce!
Regards,
Fredrik
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