Japan’s NICT claims 1st prize at Kaleidoscope 2018 for research on automated 5G network slicing
Automated 5G network slicing, gender dimensions of Artificial Intelligence, and the interplay of ethics and Machine Learning – the three best papers of Kaleidoscope 2018 embody the meeting of technical and social sciences that has come to form a staple feature of ITU Kaleidoscope academic conferences.
Kaleidoscope 2018: Machine Learning for a 5G Future, the tenth edition of ITU’s flagship academic event, was held in Santa Fe, Argentina, hosted by Universidad Tecnológica Nacional.
The final day of Kaleidoscope 2018 honoured the authors of the conference’s three best papers and presented eight researchers under 30 years’ old with ‘young author recognition certificates’.
A special mention was made of eleven graduate students and their Professor from Universidad Distrital Francisco José de Caldas, Bolívar, Colombia – an ITU Academia member – for their outstanding contribution to Kaleidoscope conferences as well as university projects that have achieved strong social impact.
For media coverage of Kaleidoscope 2018 in Spanish, see El Litoral, Santa Fe Government Portal and Diario la Opinion.
< Download all Kaleidoscope 2018 presentations from the event programme >
1st prize: Automated 5G network slicing
The winning paper highlights Machine Learning’s potential to offer valuable support to automated 5G network slicing, contributing to the allocation and adjustment of network slices’ computing and network resources in tune with different service requirements and time-varying network workloads.
Titled ‘Consideration on Automation of 5G Network Slicing with Machine Learning’, the paper was authored by Ved P. Kafle, Yusuke Fukushima, Pedro Martinez-Julia and Takaya Miyazawa (National Institute of Information and Communications Technology, Japan).
2nd prize: Gender dimensions of Artificial Intelligence
The 2nd prize paper proposes three actions to correct imbalanced power structures in Artificial Intelligence: develop standards for Artificial Intelligence incorporating the concept of ‘fairness by design’; invest in research and development to formulate technical tools to translate ethical principles into practice; and strive towards datasets free of bias.
Titled ‘A Gendered Perspective on Artificial Intelligence’, the paper was authored by Smriti Parsheera (National Institute of Public Finance and Policy, New Delhi, India).
3rd prize: Ethics and Machine Learning
The paper analyzes the interplay of ethics and Machine Learning with a view to preventing machines from inadvertently adopting unethical behaviour. The paper proposes the introduction of an ‘ethical algorithm’ in the Machine Learning domain as well as a conceptual framework to resolve ethical dilemmas.
Titled ‘Ethical Framework for Machine Learning’, the paper was authored by Charru Malhotra (Indian Institute of Public Administration, India), Vinod Kotwal (Department of Telecommunications, India) and Surabhi Dalal (India Centre for Migration, India).
Stay in tune with Kaleidoscope
The papers presented at Kaleidoscope 2018 were selected by an 83-member Technical Programme Committee using a double-blind peer-review process, under the leadership of a Steering Committee.
All papers selected for presentation will be published in the ‘Kaleidoscope 2018 Proceedings’ as well as the IEEE Xplore Digital Library.
Authors of outstanding papers have been invited to contribute to the work of the ITU Focus Group on ‘Machine Learning for Future Networks including 5G’.
Extended versions of selected papers will be considered for publication in the ITU Journal: ICT Discoveries and IEEE Communications Standards Magazine, as well as the International Journal of Technology Marketing, the International Journal of Standardization Research and the Journal of ICT Standardization.
Kaleidoscope events are peer-reviewed academic conferences that increase dialogue between academics and ICT standardization experts. The conference identifies emerging trends in ICT research and associated implications for international standardization.
