Hacking Democracy Conference
Using Data Science to Innovate Advocacy Approaches

The Case of Transitional Justice in Taiwan
English poster for Hacking Democracy Conference on December 9

FNF’s Hacking Democracy Conference will invite practitioners to show us how they use data science to innovate the approaches for advocacy for democracy, freedom, and human rights. Click here to join us on Dec. 9, 2022, UTC 8-10am via webex! Mandarin Chinese-English two-way simultaneous interpretation will be provided.

Hacking Democracy Conference

For democracy to thrive, it is important that all citizens are well-informed and have the right to participation in the decision-making process of public affairs. However, the rising trend of global democracy backsliding demonstrates: democracy becomes inaccessible to the people. In addition to the suppression through authoritarian regimes, long-existing representative democracy and government bureaucracy somehow turn democracy into something similar to a complicated program that only engineers are able to read and use.

That’s why we initiated our "Hacking Democracy Conference" Series. Learning from the spirit of hackers, we hope this conferences explore, gather, and inspire innovative ideas that enable people to break anything obstructing them from understanding and accessing democracy.

How Data Science Can Help

This year, we will focus on how data science can innovate approaches of advocacy for democracy, human rights, and freedom. Data is an important resource and basis for advocacy of every topic for democracy and human rights. With data, the people, government, advocacy groups, and all the stakeholders can discuss a thing or a policy based on facts, transparency, and mutual trust. But how to collect data in a systematic way? How to process huge amounts of data in order to turn it into informative evidence? How to correctly interpret data? Data science, which means the knowledge and methodology to collect, process, and analyze data, will help us find the answers.

The Case of Transitional Justice in Taiwan

To closer explore these questions, we will look at the example of Taiwan's Ill-gotten Party Assets Settlement Committee. The committee uses data science to facilitate transitional justice: Members of the Committee and data scientists in Taiwan have been working together to innovate methods to process and analyze massive amounts of historic documents in a short time. By applying methods such as Natural Language Processing and Digital Storytelling, they successfully processed and analyzed documents in a shorter time and thus inspired more initiatives on investigating and visualizing data and documentations about the history of authoritarian rule. Their work makes it easy to track how much and what assets should be returned to the government. It also sheds some light on the decision-making process behind tremendous unfair trials. The Committee’s work empowers people to investigate Taiwan’s time under authoritarian rule. Transitional Justice can thus be facilitated in a transparent and participatory way. In our conference, they will share their experience with the audience, on how data science can become a force to facilitate democracy, human rights, and freedom.

Meet our Panelists

  • Tsong-Shyan Lin, Full-time Commissioner of the Ill-Gotten Party Assets Settlement Committee 

Mr. Lin has been contributing his expertise in law to civil society. Before joining Ill-Gotten Party Assets Settlement Committee, he served as Deputy CEO for the Legal Aid Foundation and  Public Defender for Taiwan High Court Taichung Branch and Hsinchu District Court. He also taught in universities. He was a lecturer of Chung Yuan Christian University and Adjunct Professor Rank Specialist, Business Administration, National Taiwan University.

  • Helene Chien, Data Journalist

Ms. Chien enjoys exploring and looking into inspiring projects of data journalism and  interactive news from different country around the world.Working in a long standing media, she tends to optimize lengthy articles by implementing digital techniques. Through technology, she believes it is possible to bring social issues closer to the public and explore the diversity of storytelling.

  • Chun-Yin Lee, Research Assistant, Institution of Sociology, Academia Sinica.

Graduating with a master degree in Sociology from National Taipei University, Mr. Lee is a research assistant whose work focuses on data management and statistical analysis in Institution of Sociology, Academia Sinica. His research interests lie in life course and social stratification, and he is the co-authors of Rebirth from the Quake: Scientific Investigations of Risk and Institutional Resilience after the 1999 Chi-Chi Earthquake in Taiwan.

  • Yen-Ting Su, Data Scientist

Currently working as a data scientist in the chemical industry, Mr. Su applies data science methods to improve factory productivity. He likes to use his professional ability to help others and learn how to solve all kinds of problems through the power of data.

Click here to register for the event.

Click here to download the agenda.