Uncertainties of facial emotion recognition technologies and the automation of emotional labour

ABSTRACT

Automated detection and recognition of faces have been implemented in a broad range of media environments. Following that development, what concerns us in this article is the analysis of emotions from facial expressions using computer-based systems, in relation to which we critically investigate the use of theories of basic emotions. We explore in depth the company Affectiva’s attempts to translate, represent and schematize human emotions, as they raise a variety of problems and issues of uncertainty. We analyse the uncertainties concerning the processing of the human face ‘as image’ due to issues concerning temporality and static images as well as polyphony and modulations of the spectrum of expressions. One of our key arguments concerns the temporal character of human emotions, and we address how algorithmically regulated protocols of discretization may be said to prompt specific patterns of emotional responses and expressions based on an ideal of eliminating uncertainty. Through discussions via art pieces by Lauren McCarthy and Kyle McDonald, we question what happens when the protocols of computer systems start to perform aspects of emotional labour for us, making judgments by predicting adequate emotional responses based on the use of the strict metrics criticized in the article.     

TimeLapseAnalyzer: multi-target analysis for live-cell imaging and time-lapse microscopy

The direct observation of cells over time using time-lapse microscopy can provide deep insights into many important biological processes. Reliable analyses of motility, proliferation, invasive potential or mortality of cells are essential to many studies involving live cell imaging and can aid in biomarker discovery and diagnostic decisions. Given the vast amount of image- and time-series data produced by modern microscopes, automated analysis is a key feature to capitalize the potential of time-lapse imaging devices. To provide fast and reproducible analyses of multiple aspects of cell behaviour, we developed TimeLapseAnalyzer. Apart from general purpose image enhancements and segmentation procedures, this extensible, self-contained, modular cross-platform package provides dedicated modalities for fast and reliable analysis of multi-target cell tracking, scratch wound healing analysis, cell counting and tube formation analysis in high throughput screening of live-cell experiments. TimeLapseAnalyzer is freely available (MATLAB, Open Source) at http://www.informatik.uni-ulm.de/ni/mitarbeiter/HKestler/tla.     

Verifying Temporal Properties of Reactive Systems: A STeP Tutorial

We review a number of formal verification techniques supported by STeP, the Stanford Temporal Prover, describing how the tool can be used to verify properties of several versions of the Bakery Mutual exclusion algorithm for mutual exclusion. We verify the classic two-process algorithm and simple variants, as well as an atomic parameterized version. The methods used include deductive verification rules, verification diagrams, automatic invariant generation, and finite-state model checking and abstraction.     

Legal reasoning with subjective logic

Judges and jurors must make decisions in an environment of ignoranceand uncertainty for example by hearing statements of possibly unreliable ordishonest witnesses, assessing possibly doubtful or irrelevantevidence, and enduring attempts by the opponents to manipulate thejudge's and the jurors' perceptions and feelings. Three importantaspects of decision making in this environment are the quantificationof sufficient proof, the weighing of pieces of evidence, and therelevancy of evidence. This paper proposes a mathematical frameworkfor dealing with the two first aspects, namely the quantification ofproof and weighing of evidence. Our approach is based on subjectivelogic, which is an extension of standard logic and probability theory,in which the notion of probability is extended by including degrees ofuncertainty. Subjective Logic is a framework for modelling humanreasoning and we show how it can be applied to legalreasoning.     

Prediction of the binding mode of biarylpropylsulfonamide allosteric AMPA receptor modulators based on docking, GRID molecular interaction fields and 3D-QSAR analysis

A novel approach of combining flexible molecular docking, GRID molecular interaction fields, analysis of ligand-protein hydrogen bond interactions, conformational energy penalties and 3D-QSAR analysis was used to propose a binding mode in the dimer interface of the iGluR2 receptor for the biarylpropylsulfonamide class of positive allosteric AMPA modulators. Possible binding poses were generated by flexible molecular docking. GRID molecular interaction fields of the binding site, ligand-protein hydrogen bonding interactions and conformational energy penalties were used to select the most likely binding mode. The selected binding poses were subjected to a 3D-QSAR analysis using previously published activity data. The resulting model (2 LVs, R2=0.89, q2=0.61) predicted the activities of the compounds in the test set with a standard deviation on error of prediction of 0.17. The proposed binding mode was validated by interpretation of the PLS-coefficient regions from the 3D-QSAR analysis in terms of interactions between the receptor and the modulators.     

Internal locus of control and choice in health service shift workers

This study examined the relationship between shift work-specific locus of control (SH-LOC), active choice of work schedule and health outcomes, personal initiatives and coping behaviours in 1611 Danish Health Service shift workers. The 20-item SH-LOC scale was administered as part of a battery of measures. Multivariate analysis of covariance (controlling for age, workplace experience and weekly work hours) tested for differential responses to shift working and coping strategies. Interactive effects of internality and type of work rota were examined. Higher internality was linked to better tolerance to shift work. This did not appear to be a result of greater personal action in higher internals. The importance of control as a potential moderating factor to shift work exposure and the possible use of this measure in the process of shift worker monitoring is highlighted.     

Robust pose estimation and recognition using non-gaussian modeling of appearance subspaces

We present an original appearance model that generalizes the usual Gaussian visual subspace model to non-Gaussian and nonparametric distributions. It can be useful for the modeling and recognition of images under difficult conditions such as large occlusions and cluttered backgrounds. Inference under the model is efficiently solved using the mean shift algorithm     

Patient views of adverse events: comparisons of self-reported healthcare staff attitudes with disclosure of accident information

In the present paper, we report results of surveys in 2003 in Japan and Denmark about patients' views about adverse events, focusing on the actions of healthcare staff involved in a medical accident. Results show that patients were more likely to indicate negative expectations to a doctor's reactions after a medical accident when asked in general terms than when asked in relation to concrete case stories. When asked in general terms, 66% (47%) of Japanese (Danish) respondents expected that doctors sometimes hold back on providing information to patients about a medical accident, while 37% (7%) did so when asked about a concrete, mild-outcome case. We examine some possible reasons for the relatively high level of distrust of Japanese patients, and we discuss whether the seemingly lower level of disclosure in Japan than in Denmark and the negative stories in the Japanese press may have an impact. We also suggest some implications for introducing a patient-centred or customer-centred approach to risk management in healthcare and other domains.