In this workshop, we aim to bring together ongoing research on the Web and the Digital Divide and on what to do about it. Apart from empirically grounded (case) studies and theoretical analyses of mechanisms behind digital inequalities, we also seek, in view of recent initiatives such as Digital Humanism or Tim Berners Lee’s SOLID initiative, programmatic or solution design-oriented work from multiple disciplines, and concrete experiences on what scientists and professionals can do to help redress matters of digital inequality and exclusion. We encourage work rooted in the Global South, as both topics of interest for and authors from the Global South are underrepresented in Web Science, but also welcome work addressing matters of the Digital Divide and underprivileged communities in the Global North.
This year the AI3SD Network+ (Artificial Intelligence and Augmented Intelligence for Automated Investigations for Scientific Discovery) will be running a workshop at the WebSci20 Conference in Southampton, UK. Artificial and Augmented Intelligence systems have the potential to make a real difference in the scientific discovery domain however this brings a new wealth of ethical and societal implications to consider with regards to this research (e.g. human enhancement, algorithmic biases, risk of detriment). This workshop looks to explore the ethical and societal issues centered around using intelligent technologies (Artificial Intelligence, Augmented Intelligence, Machine Learning, and in general Semantic Web Knowledge Technologies) to further scientific discovery, with a strong consideration of data ethics and algorithmic accountability. Advances in technology and software are rarely inherently bad in themselves, however that unfortunately does not preclude them from being subverted to ill intent by others; furthermore, as demonstrated by the examples above, even an unintentional lack of care towards ethical codes and algorithmic accountability can lead to societal and ethical implications of scientific discovery. It is our responsibility as researchers to consider these issues in our research; are we conducting studies ethically? What ethical codes can we put in place for scientific discovery research to mitigate against ethical and societal issues. These are really important issues, and they require an interdisciplinary focus between scientists, social scientists and technical experts in order to be comprehensively addressed.
W3 Personalisation and Community: User Modelling and Social Connections in Web Science, Healthcare and Education7th July, 14:00 – 17:30
This workshop, for Web Scientists engaged in user-centred endeavours, will bring together people who are working to
model (profile) and personalise (tailor) for different user groups across digital offerings, and / or
foster community and personal connection throughout user groups.
We are particularly interested in healthcare and education, although all approaches to user modelling and community building are of interest. Attendees will discuss tools and techniques for user modelling/personalisation and for building community online, and share case studies showcasing such tools and techniques in action.
This workshop (hosted by the WebSci’20 conference) will focus on socially-sensitive decisions made or assisted by AI systems which often involve more complex (e.g. machine learning) and opaque forms (also referred to as black-box algorithms) of underlying decision-making processes. The aim is to stimulate a lively debate on whether explanations for AI are computable or not by bringing together researchers, practitioners and representatives of AI (or AI-assisted) decision-making systems.
This workshop (hosted by WebSci’20 conference) will bring together a mixture of inter-disciplinary researchers and practitioners working in defence, cybercrime and cybersecurity application areas to discuss and explore the challenges and future research directions around socio-technical AI systems. The aim is to showcase where the state of the art is in socio-technical AI, charting a path around issues including transparency, trustworthiness, explaining bias and error, incorporating human judgment and ethical frameworks for deployment of socio-technical AI in the future.
We are moving towards a world in which data have a life beyond the individual; where the value and potential of data are ever-changing as technological developments bring new possibilities. This immortality of data raises new ethical and societal issues that have not yet been fully articulated, and consequently we are unprepared to deal with. The challenges of dealing with large volumes of personal data are increasingly apparent in many fields of practice, although they may manifest in different ways. Rather than addressing this within the boundaries of our own disciplines a holistic approach is needed that focuses on the commonalities in the issues that arise.
This symposium provides an opportunity to explore the challenges presented by working with big personal data from different perspectives, and stimulate debates about how we might work collaboratively to anticipate, manage and prevent future problems. The presentations and discussions will be used to prepare a summary white paper/symposium briefing document to be disseminated more widely.
The Web has been the subject of compelling biological metaphors that liken it to an evolving ecosystem. Analogies of this kind could benefit from further theoretical and empirical examination through the lens of evolutionary and cognitive approaches. This half-day workshop (hosted by the Web Science conference) aims to bring together researchers who work at the intersection of evolution and the Web. Evolutionary approaches are increasingly crossing disciplinary boundaries, including (but not limited to) fields such as network and complexity sciences, anthropology, computer science and social psychology. This workshop provides an opportunity for researchers from these diverse disciplines to come together, exchange views and establish collaboration.