Hosted by the University of Sydney, the international conference on the Ethics of Data Science brings together world-renowned experts from multiple disciplines to discuss the use and misuse of our data
The conference is hosted by the Centre for Translational Data Science (CTDS) at the University of Sydney with partners from The Gradient Institute and the Humanising Machine Intelligence group from the Australian National University.
The aim is to advance the understanding of ethical aspects of algorithms, assess limitations, and showcase progress on the topic among different areas of Philosophy, Law, Data Science, and beyond. This conference is an exciting opportunity to exchange views on the viability, legitimacy, and complexity of algorithmic decision-making.
We'd like to invite you to submit your full-length paper to the second edition of the international conference on the Ethics of Data Science on 25-27 March 2020 at the University of Sydney.
Decision Making using complex data science methods, machine learning and artificial intelligence is becoming ubiquitous. In the previous edition of this conference, we identified a number of ethical challenges in ensuring these decisions are made ethically, including Transparency, Fairness, Interpretability, Accountability and the potentially discriminatory impact of data-driven automated decisionmaking.
The understanding of these issues continues to grow in the public sphere and scholarly debate, and there is an imperative to accelerate knowledge in this area to reduce the gap between the ease of using AI systems and the hardness of ensuring such use is ethical.
We are calling for high-quality full-length papers which will be assessed by a multidisciplinary Program Committee composed of experts in philosophy, law, computer science and other areas. We will have two tracks in the conference, including paper presentations and poster sessions.
The overarching aim is to advance the understanding of ethical aspects of algorithmic decision making, assess limitations, and showcase progress on the topic among different areas, such as Philosophy, Law, Computer Science, Data Science, and beyond. This conference is an exciting opportunity to exchange views and engage across disciplines on the viability, legitimacy, and potential of algorithmic decision-making to create good.
Deadline for submission is 1 December 2019. Acceptance will be via double blinded review process. Full-length papers should be submitted to the Open Review conference system, with a strict limit of 6 pages. Papers will be assessed for their ability to engage with and inspire researchers in a broad range of disciplines, and to learn from and make an impact on real data science practice and/or its real world application.
Notification of acceptance is 10 January 2020.
Topics of interest include, but are not restricted to:
Papers in computer science, law, philosophy, and beyond, including interdisciplinary collaborations, are welcome.
The conference will provide 5 travel grants of AUD$2,000.00, awarded to early career researchers from overseas institutions with the best accepted papers.
The conference will give a Best Paper prize, based on the potential impact of the research. This paper will receive the special opportunity to present in an extended session oriented to attendees from government and industry.
$40000, 1 available
6 delegate passes to all 3 days
Full-page advertisement on the inside front cover of the forum booklet being distributed to all attendees; Logo and 100-word organisational profile in conference booklet; Approved piece of marketing collateral; Two pull- up banners, supplied by the partner; logo on the event website and registration page linking to partner website; logo on event pull-up banner on stage reflecting partnership level; recognition as platinum partner on event social media releases; acknowledgement during opening ceremony
3 delegate passes to all 3 days
Full- page advertisement on the inside front cover of the forum booklet being distributed to all attendees; Logo and 70-word organisational profile in conference booklet; One pull-up banner, supplied by the partner; logo on the event website and registration page linking to partner website; logo on event pull-up banner on stage reflecting partnership level; acknowledgement during opening ceremony
2 delegate passes to all 3 days
Half-page advertisement on the inside front cover of the forum booklet being distributed to all attendees; Logo and 40-word organisational profile in conference booklet; Logo on the event website and registration page linking to partner website; logo on event pull-up banner on stage reflecting partnership level; acknowledgement during opening ceremony
"The previous edition of EDSC was a highly stimulating event for all involved, and we have received incredibly positive feedback that shows just how vibrant and relevant ethics in data science is across a broad range of realms. Planning for March 2020 is well underway." Dr Roman Marchant, Post-Doctoral Fellow, Centre for Translational Data Science, organising committee.
“This conference is a vehicle to support the community in achieving a prosperous and ethical future“. Tiberio Caetano, Chief Scientist, The Gradient Institute, organising committee.
“This conference will help us address decisions around the use of new data science technology, where and how are they are appropriate to be used.” Professor Kimberlee Weatherall, Associate Dean Research, The University of Sydney, organising committee.
“The conference will satisfy core rigorous academic research and simultaneously link to industry and government with core tutorials.” Professor Seth Lazar, Head of School, Australian National University, organising committee.
The conference provides a unique opportunity for students, academics and practitioners to exchange views on the ethics of data science. This year we are bringing world leaders in research related to various aspects of ethical data science, including fairness, decision making, accountability, privacy and transparency. Draft program will be released soon.
The high calibre keynotes and paper presentations raise fundamental questions and principles for ethical data science including purpose, diversity, fairness, transparency, accountability, and bias. Developers and practitioners must continuously reflect on these issues while they are designing, implementing and deploying the data science systems that will ultimately affect society. The workshop series will link government and industry needs with academics.