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Organized by
Federal University of Rio de Janeiro, Brazil
CSCWD International Working Group

Co-Sponsored by
IEEE SMC Society
Yunnan University, China
Zhejiang University Institute of Computing Innovation, China
University of Tech of Compiegne, France
Kunming University, China
GLOBO COMUNICACAO E PARTICIPACOES S.A.
COMPACTOR

General Conference Chair
Adriana Vivacqua

General Conference Co-Chairs
Amy Trappey
Jano de Souza
Marco Borges
Marie-Hélène Abel
Songlin He
Yong Tang

Program Committee Co-Chairs
Weiming Shen
Jean-Paul Barthès
Junzhou Luo
Daniel Schneider
Cheng Xie

Publication Chair
Jinghui Zhang

Special Session Chair
Haibin Zhu

Finance Chair / Treasurer
Kunkun Peng

Local Arrangement Chair
Claudia Motta

International Steering Committee

Co-Chairs
Jean-Paul Barthès
Junzhou Luo
Weiming Shen

Secretary
Jinghui Zhang

Members
Pedro Antunes
Marcos Borges
Kuo-Ming Chao
Gang Chen
Jano de Souza
Susan Finger
Giancarlo Fortino
Liang Gao
Ning Gu
Anne James
Peter Kropf
Weidong Li
Xiaoping P. Liu
Xiaozhen Mi
Hugo Paredes
José A. Pino
Yanjun Shi
Amy Trappey
Chunsheng Yang
Yun Yang
Jianming Yong
Qinghua Zheng

 

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    Speaker: Cristina Bicharra Garcia, Full Professor at the Applied Informatics Department at the State of Rio de Janeiro Federal University (UNIRIO), Brazil

    Title: The Good, The Bad, and The Ethical: Exploring Artificial Intelligence in Automatic Decision-Making

     

    Abstract:

    This presentation will focus on the ethics of using artificial intelligence (AI) in automatic decision-making. Various domains use AI algorithms for decision-making, from criminal justice and healthcare to hiring and credit scoring. While these algorithms offer the potential for increased efficiency and objectivity, they also raise several ethical concerns.

    The presentation will begin with an overview of the current state of AI and automatic decision-making, including the different types of AI algorithms and their use. It will then discuss some of the key ethical considerations associated with these applications of AI. These may include issues of fairness and bias, transparency and explainability, privacy and data protection, and accountability and responsibility.

    The presentation will also explore some potential consequences of using AI in automatic decision-making, both positive and negative. For example, AI may help to reduce human error and bias, but it may also perpetuate existing social inequalities or create new ones. In addition, it may improve efficiency and productivity. However, on the other hand, it may lead to job losses or other unintended consequences.

    This presentation will address these ethical concerns and propose several guidelines and best practices for developing and deploying AI algorithms. These may include the need for transparency and explainability, ongoing monitoring and evaluation, and interdisciplinary collaboration between technical experts and other stakeholders. The presentation will also exemplify the issue of bias using our current study in loan decision-making using data from a Brazilian bank as a case study.

    The presentation will conclude by highlighting the ongoing importance of ethical considerations in using AI and automatic decision-making and the need for continued discussion and debate around these issues. Taking a proactive and ethical approach to AI can help ensure that these technologies are used in ways that benefit society.

    Biographical Sketch:

    Cristina Bicharra Garcia received a Ph.D. degree in Computer-Aided Civil Engineering from Stanford University(1992), an M.Sc. degree also from Stanford (1988), and an Engineer degree in Civil Engineering from the Federal University of Rio de Janeiro (UFRJ). She is a Full Professor at the Applied Informatics Department at the State of Rio de Janeiro Federal University (UNIRIO), a Research Affiliate of the Massachusetts Institute of Technology (MIT), and an IEEE senior member. She is currently the head of the Applied Artificial Intelligence Laboratory (SPID) at UNIRIO. She was the founder and coordinator for 21 years of the ADDLabs, where she developed over 20 AI software solutions for the petroleum domain. She is the author of over 44 journal papers and 140 conference papers. She has supervised 13 Ph.D. Thesis and 36 M.Sc. Dissertations. Her current research interests include explainable AI, algorithmic discrimination, computational intelligence methods, and applications for the social good.