Fairness in Socio-technical Systems: a Case Study of Wikipedia

Problems broadly known as algorithmic bias frequently occur in the context of complex socio-technical systems (STS), where observed biases may not be directly attributable to a single automated decision algorithm. As a first investigation of fairness in STS, we focus on the case of Wikipedia. We systematically review 75 papers describing different types of bias in Wikipedia, which we classify and relate to established notions of harm from algorithmic fairness research. By analysing causal relationships between the observed phenomena, we demonstrate the complexity of the socio-technical processes causing harm. Finally, we identify the normative expectations of fairness associated with the different problems and discuss the applicability of existing criteria proposed for machine learning-driven decision systems

Towards Securing Peer-to-peer SIP in the MANET Context: Existing Work and Perspectives

The Session Initiation Protocol (SIP) is a key building block of many social applications, including VoIP communication and instant messaging. In its original architecture, SIP heavily relies on servers such as proxies and registrars. Mobile Ad hoc NETworks (MANETs) are networks comprised of mobile devices that communicate over wireless links, such as tactical radio networks or vehicular networks. In such networks, no fixed infrastructure exists and server-based solutions need to be redesigned to work in a peer-to-peer fashion. We survey existing proposals for the implementation of SIP over such MANETs and analyze their security issues. We then discuss potential solutions and their suitability in the MANET context

Distributed Wikis: A Survey

International audienceSUMMARY "Distributed Wiki" is a generic term covering various systems, including "peer-to-peer wiki," "mobile wiki," "offline wiki," "federated wiki" and others. Distributed wikis distribute their pages among the sites of autonomous participants to address various motivations, including high availability of data, new collaboration models and different viewpoint of subjects. Although existing systems share some common basic concepts, it is often difficult to understand the specificity of each one, the underlying complexities or the best context in which to use it. In this paper, we define, classify and characterize distributed wikis. We identify three classes of distributed wiki systems, each using a different collaboration model and distribution scheme for its pages: highly available wikis, decentralized social wikis and federated wikis. We classify existing distributed wikis according to these classes. We detail their underlying complexities and social and technical motivations. We also highlight some directions for research and opportunities for new systems with original social and technical motivations

“It would be pretty immoral to choose a random algorithm”:Opening up algorithmic interpretability and transparency

Purpose The purpose of this paper is to report on empirical work conducted to open up algorithmic interpretability and transparency. In recent years, significant concerns have arisen regarding the increasing pervasiveness of algorithms and the impact of automated decision-making in our lives. Particularly problematic is the lack of transparency surrounding the development of these algorithmic systems and their use. It is often suggested that to make algorithms more fair, they should be made more transparent, but exactly how this can be achieved remains unclear. Design/methodology/approach An empirical study was conducted to begin unpacking issues around algorithmic interpretability and transparency. The study involved discussion-based experiments centred around a limited resource allocation scenario which required participants to select their most and least preferred algorithms in a particular context. In addition to collecting quantitative data about preferences, qualitative data captured participants’ expressed reasoning behind their selections. Findings Even when provided with the same information about the scenario, participants made different algorithm preference selections and rationalised their selections differently. The study results revealed diversity in participant responses but consistency in the emphasis they placed on normative concerns and the importance of context when accounting for their selections. The issues raised by participants as important to their selections resonate closely with values that have come to the fore in current debates over algorithm prevalence. Originality/value This work developed a novel empirical approach that demonstrates the value in pursuing algorithmic interpretability and transparency while also highlighting the complexities surrounding their accomplishment

Kinematics of Ten Early-Type Galaxies from HST and Ground-Based Spectroscopy

We present stellar kinematics for a sample of 10 early-type galaxies observed using the STIS aboard the Hubble Space Telescope, and the Modular Spectrograph on the MDM Observatory 2.4-m telescope. The spectra are used to derive line-of-sight velocity distributions (LOSVDs) of the stars using a Maximum Penalized Likelihood method. We use Gauss-Hermite polynomials to parameterize the LOSVDs and find predominantly negative h4 values (boxy distributions) in the central regions of our galaxies. One galaxy, NGC 4697, has significantly positive central h4 (high tail weight). The majority of galaxies have a central velocity dispersion excess in the STIS kinematics over ground-based velocity dispersions. The galaxies with the strongest rotational support, as quantified with v_MAX/sigma_STIS, have the smallest dispersion excess at STIS resolution. The best-fitting, general, axisymmetric dynamical models (described in a companion paper) require black holes in all cases, with masses ranging from 10^6.5 to 10^9.3 Msun. We replot these updated masses on the BH/sigma relation, and show that the fit to only these 10 galaxies has a slope consistent with the fits to larger samples. The greatest outlier is NGC 2778, a dwarf elliptical with relatively poorly constrained black hole mass. The two best candidates for pseudobulges, NGC 3384 and 7457, do not deviate significantly from the established relation between black hole and sigma. Neither do the three galaxies which show the most evidence of a recent merger, NGC 3608, 4473, and 4697.Comment: 43 pages, accepted for publication in the Astrophysical Journal, high resolution version found at http://hoku.as.utexas.edu/~gebhardt/pinkney.p