Dealing with biases in Artificial Intelligence


A discussion on the types of biases and on the importance of tackling them

When businesses fail to develop a strong awareness about biases in AI it can land them in serious trouble. Biases can have a negative effect on society as well as on individual well-being, they can reveal weaknesses in design, and be counterproductive to the goal the AI was initially designed to achieve. And they can be detrimental for the businesses. Taking biases seriously means actively incorporating ethics into your business and taking proactive steps to address the problem. This webinar is a first step in that direction.

About the AI Ethics Lab: 

AI Ethics Lab aims to detect and solve ethical issues in building and using AI systems to enhance technology development. A pioneer in the field, AI Ethics Lab became active in 2017 and developed its PiE (puzzle-solving in ethics) Model, a unique approach in the industry to integrate ethics solutions into the innovation process. The Lab offers consulting to businesses on ethics related challenges—including, ethics risks analyses, developing ethics strategies for companies, and providing ethics training and courses. The Lab also conducts practice-oriented original research.

Content of the webinar: 

In this webinar, we will explore algorithmic bias, starting from its definition and consequences all the way to its solutions. What do we mean when we talk about “biases in AI”? Why is it important to reduce and eliminate them both for our societal and individual well-being and for the success of the technology and the business? We will define the categories of algorithmic bias illustrating them with use-cases. 

It is crucial to understand the core problems around algorithmic bias, but how do we move on to solving them? We will examine the stages of innovation and the bias-related questions we should ask at each stage. Often answering these questions require two types of work to be done: technical and ethical. We will point to these solutions and explain our model for effective and successful problem solving through integrating ethics analysis into the innovation process. 

In our webinar, Cansu Canca (Founder and Director of AI Ethics Lab), Laura Haaber (Visiting Research Fellow at Harvard University) and Julia Zacharias (VP Delivery & Customer Success at Applause) will discuss biases in Artificial Intelligence.


  • What algorithmic bias is
  • What we mean when we talk about "bias in AI"
  • Why it is important to limit and eliminate them both

Speakers of this webinar

Cansu Canca

Cansu Canca

Founder and Director • AI Ethics Lab

Cansu is a philosopher and the founder+director of the AI Ethics Lab, where she leads teams of computer scientists, philosophers, and legal scholars to provide ethics analysis and guidance to researchers and practitioners. She has a Ph.D. in philosophy specializing in applied ethics. She primarily works on ethics of technology, having previously worked on ethics and health. Prior to the AI Ethics Lab, she was a lecturer at the University of Hong Kong, and a researcher at the Harvard Law School, Harvard School of Public Health, Harvard Medical School, National University of Singapore, Osaka University, and the World Health Organization.

Laura Haaber Ihle

Laura Haaber Ihle

Visiting Research Fellow • Harvard University

Laura is a research fellow at the Harvard Department of Philosophy, where she focuses on the questions that arise in the intersection between AI, ethics and knowledge production and dissemination. She has a Ph.D. in philosophy and political theory and works on how ethics can be more strongly integrated into the tech world in a manner that is useful and meaningful for the companies, the end consumers and the broader society as a whole.

Julia Zacharias

Julia Zacharias

VP Delivery & Customer Success • Applause

Julia leads the EU Solution Delivery and Testing Services department at Applause EU since 2017. She ensures that customers receive a smooth onboarding and achieve their digital quality goals through working with Applause. In supporting the roll-out of AI and voice testing, Julia has gained insights into the challenges of building and testing AI-based applications. She is actively encouraging women to enter the tech world and make an impact on how digital products are designed, developed and tested. Julia previously worked as a project portfolio manager and management consultant, among others at Kearney.


Applause is the worldwide leader in enabling digital quality. With the Product Excellence Platform, Applause provides a harmonized approach to quality that drastically improves testing coverage, reduces costs and speeds time-to-market for websites, mobile apps, IoT and in-store experiences.