Access control technologies for Big Data management systems: literature review and future trends

Abstract Data security and privacy issues are magnified by the volume, the variety, and the velocity of Big Data and by the lack, up to now, of a reference data model and related data manipulation languages. In this paper, we focus on one of the key data security services, that is, access control, by highlighting the differences with traditional data management systems and describing a set of requirements that any access control solution for Big Data platforms may fulfill. We then describe the state of the art and discuss open research issues

Perceptions of Fairness and Trustworthiness Based on Explanations in Human vs. Automated Decision-Making

Automated decision systems (ADS) have become ubiquitous in many high-stakes domains. Those systems typically involve sophisticated yet opaque artificial intelligence (AI) techniques that seldom allow for full comprehension of their inner workings, particularly for affected individuals. As a result, ADS are prone to deficient oversight and calibration, which can lead to undesirable (e.g., unfair) outcomes. In this work, we conduct an online study with 200 participants to examine people’s perceptions of fairness and trustworthiness towards ADS in comparison to a scenario where a human instead of an ADS makes a high-stakes decision—and we provide thorough identical explanations regarding decisions in both cases. Surprisingly, we find that people perceive ADS as fairer than human decision-makers. Our analyses also suggest that people’s AI literacy affects their perceptions, indicating that people with higher AI literacy favor ADS more strongly over human decision-makers, whereas low-AI-literacy people exhibit no significant differences in their perceptions

Beliefs, politics, and environmental policy

Experts and the general public often perceive environmental problems differently. Moreover, regulatory responses to environmental issues often do not coincide with consensus expert recommendations. These two facts are mutually consistent – it is unlikely that regulations based on factual claims that are substantially different from voters’ opinions would be politically feasible. Given that the public’s beliefs constrain policy choices, it is vital to understand how beliefs are formed, whether they will be biased, and how the inevitable heterogeneity in people’s beliefs filters through the political system to affect policy. We review recent theoretical and empirical work on individual inference, social learning, and the supply of information by the media, and identify the potential for biased beliefs to arise. We then examine the interaction between beliefs and politics: can national elections and legislative votes be expected to result in unbiased collective decisions, do heterogeneous beliefs induce strategic political actors to alter their policy choices, and how do experts and lobby groups affect the information available to policy-makers? We conclude by suggesting that the relationship between beliefs and policy choices is a relatively neglected aspect of the theory of environmental regulation, and a fruitful area for further research

Evaluation of a context-aware voice interface for Ambient Assisted Living: qualitative user study vs. quantitative system evaluation

International audienceThis paper presents an experiment with seniors and people with visual impairment in a voice-controlled smart home using the SWEET-HOME system. The experiment shows some weaknesses in automatic speech recognition which must be addressed, as well as the need of better adaptation to the user and the environment. Indeed, users were disturbed by the rigid structure of the grammar and were eager to adapt it to their own preferences. Surprisingly, while no humanoid aspect was introduced in the system, the senior participants were inclined to embody the system. Despite these aspects to improve, the system has been favourably assessed as diminishing most participant fears related to the loss of autonomy