Responsible Data Science Symposium

ACEMS QUT

The Symposium brings together academics & practitioners to explore Responsible Data Science  topics and advance knowledge and opportunities

QUT Gardens Point Campus (and online)

ACEMS and the QUT Centre for Data Science ABS Co-Chair of Government Statistics will host the Responsible Data Science Symposium on 3 December.Responsible Data Science Symposium The Symposium aims to bring together:<ul><li>Academic experts to deliver presentations on key &quot;responsible data science&quot; topics from across disciplines (including statistics, computer science, ethics, law, media, and business) </li><li>Practitioners from the ABS, Defence, and other Australian Public Service organisations, to present on issues, challenges, opportunities, and proposed projects</li><li>Invited guests, including students, researchers, and practitioners, from across sectors (academia, research, industry, and government) interested in engaging in discussions and workshops, to share and advance knowledge, develop relationships, and identify and progress opportunities</li></ul>Some attendees may also want to be involved in<ul><li>ABS research projects (outlined below), or others, explored in the workshops, and/or </li><li>collaborating to create academic/practitioner outputs from the workshops;</li></ul>and the Symposium aims to support the advancement of such opportunities.QUT Hosted Hybrid Event The event will be hosted at QUT (for in-person and virtual attendance), with full catering provided for in-person attendees.Preliminary Symposium ProgramThe Symposium will officially run from 9am-4pm - with catered breaks (for morning tea, lunch, and afternoon tea) plus the option to enjoy a celebratory drink and networking on conclusion. The Symposium will open for registrations from 8:15am.Overview of Day:<ul><li>8:45am - 9:00am: Pre-Symposium - Venue Opens for Attendees to Register </li><li>9:00am -4:00pm: Symposium (featuring expert presentations, break-out discussion groups, workshops, opportunity identification, and closing remarks)</li></ul>On the eve of the Symposium, a Pre-Symposium Dinner will be hosted for guest speakers, partners and invited guests to attend.Opportunities including Projects and Publications The &quot;responsible data science&quot; theme and sub-topics including ethical AI, explainable AI, and uncertainty quantification, are opportunity-rich from a knowledge advancement and collaboration perspective.The symposium will enable some exploration of these topics, opportunities, and relationship-building for future collaborations.Speakers<ul><li>A/Professor Gentry White (ACEMS, Associate Investigator; and QUT Centre for Data Science, ABS Co-Chair Data Science in Government Systems Domain) - Welcome &amp; Exploratory Overview of &quot;Responsible Data Science&quot;</li><li>Professor Rachel Thomas (Fast.ai, Co-founder; QUT Centre for Data Science Data Scientist in Residence) - Ethical Artificial Intelligence</li><li>Professor Timothy Miller (Centre of AI and Digital Ethics, Co-Director) - Explainable Artificial Intelligence (XAI)</li><li>Professor Kevin Desouza (QUT Business School/Centre for Data Science, Professor of Business, Technology and Strategy) - AI &amp; Public Agencies: A Maturity Model</li><li>Ms. Susan Shaw (Australian Bureau of Statistics, Director, Methodology Futures, Methodology Division) - Selected ABS Methodological Development Priorities</li><li>Dr. S. Kate Devitt (Trusted Autonomous Systems (TAS-D) CRC, Chief Scientist) - Australia’s AI Governance Frameworks &amp; Pragmatic Tools Manage Ethical Risk</li><li>Professor Dan Hunter (ARC Centre of Excellence for Automated Decision-Making + Society (ADM+), Chief Investigator; QUT, Executive Dean of the Faculty of Law) - Fairness, Accountability and Transparency (FATML) in Machine Learning </li><li>Mr. Aaron Snoswell (ACEMS UQ, PhD to be conferred; Research Fellow in Computational Law at ARC ADM+S) - Overcoming AI Opacity in Civil Litigation</li><li>Dr. Tristan Perez (Boeing Research Australia, Principal Systems Engineer - Mission Systems &amp; Autonomy) - Data-driven Verification of AI - Fundamental Limitations &amp; Feasible Solutions</li></ul>ABS Research Projects:The QUT Centre for Data Science and ABS have committed to the following projects, to be explored at the Symposium, and aim to form project teams (with opportunities for other experts, students, RAs, and supervisors to join) for project commencement in 2021/2022:(1) Investigate the use of attention mechanisms for explainability;(2) Estimating uncertainty for Deep Neural Networks (DNNs) (building on earlier work);(3) Investigate applications of contrastive explanations in the ABS;(4) Efficient Sampling Techniques for Labelling Training Data for Model Building; and(5) Representivity of Training and Test Data;and others, including new opportunities which may be identified from the afternoon workshop and discussions.Register Now Please register now to attend, virtually or in person, if you have an interest in Responsible Data Science (and being kept informed of developments).We will share more details in due course

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Responsible Data Science Symposium

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