12月8日（火）、青島にてiEEE主催のイベント、 The International Conference on Awareness Science and Technology (iCAST 2020)が開催され、弊社代表の福馬が基調講演を行いました。同国際会議では、認知科学とその応用分野に関する研究者・科学者らが集まり、最新の研究発表や議論・意見交換等を行います。

同イベントは、2009年から毎年開催されており、今回が11回目となります。今年はコロナウイルスの影響で現地とオンラインの同時開催となりました。我々はオープニングの基調講演を担当し、機械学習におけるバイアスと公平性について講演を行いました。

<以下講演内容>

Fairness in AI Service and Awareness for Computational Social Science

This talk aims to present an overview of the common pitfalls for applying machine learning techniques to real-world problems from a perspective of fairness. This talk mainly highlights the importance of diversity of the data and the problem related to algorithmic bias. In the age of information overload, machine learning becomes increasingly important in everyday life. There has been a growing interest in discovering the harmful effect of bias in machine learning and a way to take fairness into service. Based on our research and experience in the industry, we discuss open questions for further application.

Fukuma is the founder and CEO of TDAI Lab, a machine learning AI startup, founded in Tokyo in 2016. He is now a Ph.D. student in the Department of Systems Innovation, School of Engineering, The University of Tokyo. The main area of his interest is learning the true quality of the content in an online platform. This includes topics in unbiased learning-to-rank, recommendation, and AI for Society. He is also a Japanese ballroom dancer, representing Japan from 2016 to 2019.