IGF 2023 WS #571 Data analytics and ML for Sustainable Development Goals

Organizer 1: Yawri Carr, 🔒TU München
Organizer 2: João Pedro Damas Martins, EURid
Organizer 3: James Amattey, Norenson IT

Speaker 1: Paul Springer, Civil Society, Western European and Others Group (WEOG)
Speaker 2: Xu Shanshan, Technical Community, Western European and Others Group (WEOG)
Speaker 3: Peter Addo, Intergovernmental Organization, Intergovernmental Organization
Speaker 4: Raashi Saxena, Civil Society, Asia-Pacific Group

Moderator

João Pedro Damas Martins, Civil Society, Western European and Others Group (WEOG)

Online Moderator

Yawri Carr, Civil Society, Latin American and Caribbean Group (GRULAC)

Rapporteur

James Amattey, Private Sector, African Group

Format

Round Table - 60 Min

Policy Question(s)

How are the use cases you already developed as part of the Emerging Tech Lab of your organization performing accordingly to tackle SDGs and what is the response from communities where you have applied it?

How can data analytics and ML methods (including natural language processing) contribute to an international human rights tribunal to improve its justice process?

What are the biggest challenges you had to face for your projects and what best practices helped you overcome these?

What will participants gain from attending this session? They will have a technical session that is focused on humanity-related problems. Many sessions at the IGF are based on political or social sciences or law. Nevertheless, the technical aspect is essential but not so widely discussed at the IGF. Participants will get to know and ask about specific use-cases, their development, and deployment. Of course, also asking questions.

Description:

This session aims to discuss from a technical perspective how SDGs can be better tackled by implementing data analytics and machine learning methods and techniques. It is fundamental to know the technical basis.

The challenges that humanity faces grow every day, but the same methods are used. There is an urgent necessity of using the power of technology to improve processes that are slow and inefficient and don't contribute to tackle humanity-issues.

Nowadays, digital transformation is not just for profit but also has arrived to help organizations that work for sustainable development and human rights.

These organisations are now also looking forward to implementing data analytics and machine learning to get several new opportunities.

Some real use-cases in which data analytics and machine learning can be implemented for the SDGs and that will be discussed in the session are:
Human Rights: Facilitating the analysis of numerous datasets through pattern recognition and natural language processing. From human rights violations, their origins and indicators that facilitate data-based decision-making. And also contributing to human rights international tribunals to read the whole documentation and to provide a decision that is quicker and that protects the victims.
Gender violance: Applications have been made to introduce forensic data of women victime of violance in Kenya, a country with a huge issue in gender violance.
Climate change: Prediction can collaborate to warn about possible risks and impacts. This is fundamental for prevention, for instance from a traditional climate forecast to the prediction of a natural disaster or to warn about a possible deforestation or fire.
Sustainable cities: An automated road condition study using satellite images and deep learning has helped communities in Subsaharan Africa. Car accidents could be prevented, saving lives and being beneficial for every sector of society that mobilize through the roads.

Expected Outcomes

Awareness and information of new paths: Nowadays, many educational offers are teaching data analytics and ML subjects. However, is not taught that these technologies can also help humanity and how concretely it can be done.

As the organizations participating as speakers develop use cases and projects related to the SDGs and human rights with data analytics and ML, one of the outcomes is to share the best practices during the process and to provide real applications of the methods and techniques used.

Creation of partnerships for the projects or support networks to face issues and challenges during the coding, ideation, development or tests.

Hybrid Format: We will have online and in-person participation. Two speakers and a moderator will be for sure in person. The interaction will be by involving the public in real use-cases and to contribute to the use-case with feedback.