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Found 6 papers, 2 papers with code
I Want My App That Way: Reclaiming Sovereignty Over Personal Devices
Dark patterns in mobile apps take advantage of cognitive biases of end-users and can have detrimental effects on people's lives.
Human-Computer Interaction
Exploring Design and Governance Challenges in the Development of Privacy-Preserving Computation
Homomorphic encryption, secure multi-party computation, and differential privacy are part of an emerging class of Privacy Enhancing Technologies which share a common promise: to preserve privacy whilst also obtaining the benefits of computational analysis.
Human-Computer Interaction
Design of a dynamic and self adapting system, supported with artificial intelligence, machine learning and real time intelligence for predictive cyber risk analytics in extreme environments, cyber risk in the colonisation of Mars
This paper surveys deep learning algorithms, IoT cyber security and risk models, and established mathematical formulas to identify the best approach for developing a dynamic and self adapting system for predictive cyber risk analytics supported with Artificial Intelligence and Machine Learning and real time intelligence in edge computing.
Some HCI Priorities for GDPR-Compliant Machine Learning
In this short paper, we consider the roles of HCI in enabling the better governance of consequential machine learning systems using the rights and obligations laid out in the recent 2016 EU General Data Protection Regulation (GDPR)---a law which involves heavy interaction with people and systems.
Fairness and Accountability Design Needs for Algorithmic Support in High-Stakes Public Sector Decision-Making
Calls for heightened consideration of fairness and accountability in algorithmically-informed public decisions---like taxation, justice, and child protection---are now commonplace.
Like trainer, like bot? Inheritance of bias in algorithmic content moderation
This paper provides some exploratory methods by which the normative biases of algorithmic content moderation systems can be measured, by way of a case study using an existing dataset of comments labelled for offence.
