More women in informatics research and education

Speaker: Lynda Hardman Organiser: Time: 04/02/2015 12:30-13:30 Location: B32/3077 Abstract The challenges of addressing gender inequalities in science, technology, engineering, mathematics and medicine is widely acknowledged. We currently hold a bronze award and ECS is one of many academic units in the University which has gained Athena Swan Charter status. In this seminar, Professor Lynda Hardman, Chair of the Informatics Europe working group "Women in Informatics Research and Education” will be explaining the causes of issued underlying gender inequality and constructive routes to addressing this important agenda. In undertaking to commit to an action plan which is a prerequisite of gaining charter status, the University or academic department agreed to accept and incorporate the Athena Swan six principles listed below: * To address gender inequalities requires commitment and action from everyone, at all levels of the organisation * To tackle the unequal representation of women in science requires changing cultures and attitudes across the organisation * The absence of diversity at management and policy-making levels has broad implications which the organisation will examine * The high loss rate of women in science is an urgent concern which the organisation will address * The system of short-term contracts has particularly negative consequences for the retention and progression of women in science, which the organisation recognises * There are both personal and structural obstacles to women making the transition from PhD into a sustainable academic career in science, which require the active consideration of the organisation. This seminar is designed to provide an opportunity to explore these issues NOTE: Lynda will be basing here talk on some of the work she directed as chair of the "Women in Informatics Research and Education” working group. The purpose of the working group is to actively participate and promote actions that contribute to improve gender balance in Information and Communication Sciences and Technologies. The first concrete result of the working group's activities was the publication of the booklet "More Women in Informatics Research and Education" in 2013. The booklet is a compact source of clear and simple best practices to deans and heads of departments that aim to increase the participation of women as both students and employees in their institutions. Many tips included were also inspired by colleagues already in leading positions who have already implemented actions in their institutions to attract more women and ensure their continued participation in the organization at commensurate ratios with their male colleagues. The booklet is endorsed by the European Commission and features a foreword by Neelie Kroes, Vice-President of the European Commission, responsible for the Digital Agenda.

Hierarchical Prediction Machines and Big Data Analytics

An emerging consensus in cognitive science views the biological brain as a hierarchically-organized predictive processing system. This is a system in which higher-order regions are continuously attempting to predict the activity of lower-order regions at a variety of (increasingly abstract) spatial and temporal scales. The brain is thus revealed as a hierarchical prediction machine that is constantly engaged in the effort to predict the flow of information originating from the sensory surfaces. Such a view seems to afford a great deal of explanatory leverage when it comes to a broad swathe of seemingly disparate psychological phenomena (e.g., learning, memory, perception, action, emotion, planning, reason, imagination, and conscious experience). In the most positive case, the predictive processing story seems to provide our first glimpse at what a unified (computationally-tractable and neurobiological plausible) account of human psychology might look like. This obviously marks out one reason why such models should be the focus of current empirical and theoretical attention. Another reason, however, is rooted in the potential of such models to advance the current state-of-the-art in machine intelligence and machine learning. Interestingly, the vision of the brain as a hierarchical prediction machine is one that establishes contact with work that goes under the heading of 'deep learning'. Deep learning systems thus often attempt to make use of predictive processing schemes and (increasingly abstract) generative models as a means of supporting the analysis of large data sets. But are such computational systems sufficient (by themselves) to provide a route to general human-level analytic capabilities? I will argue that they are not and that closer attention to a broader range of forces and factors (many of which are not confined to the neural realm) may be required to understand what it is that gives human cognition its distinctive (and largely unique) flavour. The vision that emerges is one of 'homomimetic deep learning systems', systems that situate a hierarchically-organized predictive processing core within a larger nexus of developmental, behavioural, symbolic, technological and social influences. Relative to that vision, I suggest that we should see the Web as a form of 'cognitive ecology', one that is as much involved with the transformation of machine intelligence as it is with the progressive reshaping of our own cognitive capabilities.

Mandevillian Intelligence: From Individual Vice to Collective Virtue

Abstract Mandevillian intelligence is a specific form of collective intelligence in which individual cognitive vices (i.e., shortcomings, limitations, constraints and biases) are seen to play a positive functional role in yielding collective forms of cognitive success. In this talk, I will introduce the concept of mandevillian intelligence and review a number of strands of empirical research that help to shed light on the phenomenon. I will also attempt to highlight the value of the concept of mandevillian intelligence from a philosophical, scientific and engineering perspective. Inasmuch as we accept the notion of mandevillian intelligence, then it seems that the cognitive and epistemic value of a specific social or technological intervention will vary according to whether our attention is focused at the individual or collective level of analysis. This has a number of important implications for how we think about the cognitive impacts of a number of Web-based technologies (e.g., personalized search mechanisms). It also forces us to take seriously the idea that the exploitation (or even the accentuation!) of individual cognitive shortcomings could, in some situations, provide a productive route to collective forms of cognitive and epistemic success. Speaker Biography Dr Paul Smart Paul Smart is a senior research fellow in the Web and Internet Science research group at the University of Southampton in the UK. He is a Fellow of the British Computer Society, a professional member of the Association of Computing Machinery, and a member of the Cognitive Science Society. Paul’s research interests span a number of disciplines, including philosophy, cognitive science, social science, and computer science. His primary area of research interest relates to the social and cognitive implications of Web and Internet technologies. Paul received his bachelors degree in Psychology from the University of Nottingham. He also holds a PhD in Experimental Psychology from the University of Sussex.