Diversity and Inclusion

Starting in 2021, the Data Management community begins an integrated effort to promote diversity and inclusion in all aspects of our professional activities. MDM 2023 participates in this effort (alongside SIGMOD, VLDB, SoCC, ICDE and EDBT/ICDT) which celebrates the diversity in our community and welcomes everyone regardless of age, sex, gender identity, race, ethnicity, socioeconomic background, country of origin, religion, sexual orientation, physical ability, education, work experience, etc. It also welcomes people and opinions of all political persuasions, as long as they abide by the ACM policy against hate speech and harassment. Specific information can be found in the following, dedicated web site: https://dbdni.github.io


Navigating the Social and Ethical Responsibilities of Computing

- Gill Dobbie, Professor, University of Auckland, New Zealand

Abstract

In today's interconnected world, computing technologies play a central role, shaping diverse aspects of human existence. From artificial intelligence to social media platforms, the power of computing continues to evolve and influence the ways we communicate, work, and make decisions. As these technologies advance, it is paramount to examine the social and ethical responsibilities inherent in their design, deployment, and usage. This keynote talk aims to shed light on the multifaceted dimensions of the social and ethical responsibilities of computing and emphasize the urgent need for conscientious action. Furthermore, the talk will delve into the ethical considerations that emerge with the rapid progression of computing technologies. It will highlight the pressing need to address issues such as the potential for automated decision-making to reinforce existing social inequalities. Additionally, the speaker will underline the significance of fostering transparency, accountability, and inclusivity in the design and deployment of computing systems.

Bio

Professor Gillian Dobbie is widely recognised for her research in database systems and artificial intelligence. She holds a PhD in Computer Science from the University of Melbourne, where she specialized in database theory and design. Her research interests encompass a wide range of topics, including conceptual modeling, knowledge representation, query optimization, data privacy, data stream mining, continual learning, and adversarial learning. She has published over 160 papers in top-tier conferences and journals, such as SIGCSE, ICDM, SIGIR, CIKM, ICDE, SIGMOD, TODS, ACM Computing Surveys. She was awarded the DASFAA 10+ Year Best Paper Award for her research contribution with Prof Ling Tok Wang and Prof Mengchi Liu. Professor Dobbie is a Fellow of the Royal Society of New Zealand.

Throughout her career Professor Dobbie has been a catalyst for collaboration and interdisciplinary work, which has led to leading projects such as Precision Driven Health, receiving the MinterEllisonRuddWatts Research & Business Partnership Award. She has also built bridges between academia and industry through her leadership of the Auckland ICT Graduate School.

Beyond her academic pursuits, Professor Dobbie is actively engaged in promoting diversity and inclusivity in STEM fields. She is passionate about encouraging underrepresented groups to pursue careers in computer science, and fostering an environment where everyone can thrive.