ITU News caught up with Chaesub Lee, Director of the ITU Telecommunication Standardization Bureau, to learn more about the latest ITU standards projects addressing AI and Machine Learning and the value of the AI for Good Global Summit.
Where do we stand today in terms of AI applications and how might that evolve?
Innovation by and of AI is accelerating, and this is evidenced by the contributions driving ITU’s work. AI and Machine Learning are gaining a larger share of the ITU standardization work programme in fields such as network orchestration and management, multimedia coding, service quality assessment, operational aspects of service provision and telecom management, cable networks, digital health, environmental efficiency, and autonomous driving.
But AI and Machine Learning are finding very practical applications across industry sectors — applications with considerable potential to act as a force for good.
The scope of debate around AI extends far beyond the scope of any single organization. This is why ITU has called for an inclusive global dialogue on the implications of AI for the future of our society — a dialogue that is anchored by the AI for Good Global Summit.
What value do ITU and the broader “AI for Good” community draw from the AI for Good Global Summit?
Alongside recent breakthroughs, new partnerships are also supporting growing confidence in AI. The AI for Good Global Summit continues to offer valuable support to the “AI for Good community” in creating and sustaining these partnerships.
Experts from different fields are coming together to align incentives for innovation and solve problems with AI. We see connections forming among AI specialists, AI users, data owners and experts in various domains to benefit from AI applications — domains where AI could make key contributions to sustainable development.
The United Nations Sustainable Development Goals (SDGs) provide the guiding light to this innovation.
Inclusive dialogue helps all stakeholders to build an understanding of their respective roles in nurturing ICT innovation. This dialogue supports the development of new partnerships and clarifies the contributions expected of various stakeholders, including the contribution expected of ITU standardization. For example, the motivations behind initiatives such as the ITU Focus Groups on “AI for Health” and “AI for autonomous and assisted driving” and the new Global Initiative on “AI and Data Commons” were first elaborated at the AI for Good Global Summit.
Could you share more insight into the aims of these initiatives?
The ITU Telecommunication Standardization Sector (ITU–T) Study Groups are where ITU members work together to develop international standards.
ITU–T Focus Groups are flexible structures that are operational for a short period of time (typically 1–2 years). They accelerate studies in fields of growing strategic relevance to the ITU membership. Open to all interested parties, these groups prepare a basis for related standardization work in ITU–T Study Groups.
Let me highlight five open platforms advancing various aspects of AI and Machine Learning.
The ITU Focus Group on “Machine Learning for Future Networks including 5G” is defining the requirements of machine learning as they relate to interfaces, protocols, algorithms, data formats and network architectures.