Charles Ovink

Associate Political Affairs Officer, United Nations Regional Centre for Peace and Disarmament in Asia and the Pacific


Now an Associate Political Affairs Officer with the United Nations Office for Disarmament Affairs and its Regional Centre for Peace and Disarmament in Asia and the Pacific, Charles Ovink specializes in disarmament and nonproliferation issues in the region, with a particular interest in emerging concerns, including Lethal Autonomous Weapons Systems and AI. Prior to his current post, he has been a Programme Manager for the United Nations World Institute for Development Economics Research, and a consultant for the United Nations University and Creative Environmental Networks. He received his Master’s Degree from Waseda University, focusing on political security and power transition.


Avoiding Bias in AI: Across Ethics and Diversity


The applications of AI across industries and public sector are mostly based on the category of algorithms known as deep learning, and how deep-learning algorithms find patterns in data. The simple narrative is the data we feed it is biased and subsequently we have to be careful in applying AI to real life scenarios. The way we frame problems and manage the data becomes crucial and if we add adaptability, localization and social context things become even harder. This expert panel composed of national and international public sector officials, academia and industry researchers will discuss what is the best way, if any, to address this problem and how to move in the right direction.




1-5-1 Marunouchi, Chiyoda-ku, Tokyo
Shin-Marunouchi Building, Room 902


April 24, 2019 at 11:00AM - 11:50AM