Certifying and removing disparate impact

What does it mean for an algorithm to be biased? In U.S. law, unintentional bias is encoded via disparate impact, which occurs when a selection process has widely different outcomes for different groups, even as it appears to be neutral. This legal determination hinges on a definition of a protected class (ethnicity, gender, religious practice) and an explicit description of the process. When the process is implemented using computers, determining disparate impact (and hence bias) is harder. It might not be possible to disclose the process. In addition, even if the process is open, it might be hard to elucidate in a legal setting how the algorithm makes its decisions. Instead of requiring access to the algorithm, we propose making inferences based on the data the algorithm uses. We make four contributions to this problem. First, we link the legal notion of disparate impact to a measure of classification accuracy that while known, has received relatively little attention. Second, we propose a test for disparate impact based on analyzing the information leakage of the protected class from the other data attributes. Third, we describe methods by which data might be made unbiased. Finally, we present empirical evidence supporting the effectiveness of our test for disparate impact and our approach for both masking bias and preserving relevant information in the data. Interestingly, our approach resembles some actual selection practices that have recently received legal scrutiny.Comment: Extended version of paper accepted at 2015 ACM SIGKDD Conference on Knowledge Discovery and Data Minin

Quantum Field Theory of boson mixing

We consider the quantum field theoretical formulation of boson field mixing and obtain the exact oscillation formula. This formula does not depend on arbitrary mass parameters. We show that the space for the mixed field states is unitarily inequivalent to the state space where the unmixed field operators are defined. We also study the structure of the currents and charges for the mixed fields

Strengthening functionally specific neural pathways with transcranial brain stimulation

Cortico-cortical paired associative stimulation (ccPAS) is a recently established offline dual-coil transcranial magnetic stimulation (TMS) protocol 1, 2, 3 based on the Hebbian principle of associative plasticity and designed to transiently enhance synaptic efficiency in neural pathways linking two interconnected (targeted) brain regions 4, 5. Here, we present a new ‘function-tuning ccPAS’ paradigm in which, by pairing ccPAS with the presentation of a specific visual feature, for example a specific motion direction, we can selectively target and enhance the synaptic efficiency of functionally specific, but spatially overlapping, pathways. We report that ccPAS applied in a state-dependent manner and at a low intensity selectively enhanced detection of the specific motion direction primed during the combined visual-TMS manipulations. This paradigm significantly enhances the specificity of TMS-induced plasticity, by allowing the targeting of cortico-cortical pathways associated with specific functions

Rhythmic TMS as a Feasible Tool to Uncover the Oscillatory Signatures of Audiovisual Integration

Multisensory integration is quintessential to adaptive behavior, with clinical populations showing significant impairments in this domain, most notably hallucinatory reports. Interestingly, altered cross-modal interactions have also been reported in healthy individuals when engaged in tasks such as the Sound-Induced Flash-Illusion (SIFI). The temporal dynamics of the SIFI have been recently tied to the speed of occipital alpha rhythms (IAF), with faster oscillations entailing reduced temporal windows within which the illusion is experienced. In this regard, entrainment-based protocols have not yet implemented rhythmic transcranial magnetic stimulation (rhTMS) to causally test for this relationship. It thus remains to be evaluated whether rhTMS-induced acoustic and somatosensory sensations may not specifically interfere with the illusion. Here, we addressed this issue by asking 27 volunteers to perform a SIFI paradigm under different Sham and active rhTMS protocols, delivered over the occipital pole at the IAF. Although TMS has been proven to act upon brain tissues excitability, results show that the SIFI occurred for both Sham and active rhTMS, with the illusory rate not being significantly different between baseline and stimulation conditions. This aligns with the discrete sampling hypothesis, for which alpha amplitude modulation, known to reflect changes in cortical excitability, should not account for changes in the illusory rate. Moreover, these findings highlight the viability of rhTMS-based interventions as a means to probe the neuroelectric signatures of illusory and hallucinatory audiovisual experiences, in healthy and neuropsychiatric populations

Fairness-enhancing interventions in stream classification

The wide spread usage of automated data-driven decision support systems has raised a lot of concerns regarding accountability and fairness of the employed models in the absence of human supervision. Existing fairness-aware approaches tackle fairness as a batch learning problem and aim at learning a fair model which can then be applied to future instances of the problem. In many applications, however, the data comes sequentially and its characteristics might evolve with time. In such a setting, it is counter-intuitive to "fix" a (fair) model over the data stream as changes in the data might incur changes in the underlying model therefore, affecting its fairness. In this work, we propose fairness-enhancing interventions that modify the input data so that the outcome of any stream classifier applied to that data will be fair. Experiments on real and synthetic data show that our approach achieves good predictive performance and low discrimination scores over the course of the stream.Comment: 15 pages, 7 figures. To appear in the proceedings of 30th International Conference on Database and Expert Systems Applications, Linz, Austria August 26 - 29, 201

Experimental and Numerical Performance Survey of a MW-Scale Supercritical CO2 Compressor Operating in Near-Critical Conditions

Closed power cycles based on carbon dioxide in supercritical conditions (sCO2 in the following) are experiencing a growing scientific, technical and industrial interest, due to the high energy conversion efficiency and components compactness. Despite these advantages, the use of a working fluid operating in proximity to the critical point, especially for the compressor, entails multidisciplinary challenges related to the severe non-ideality of the supercritical fluid, which includes the potential onset of phase change at the impeller intake. On the technical and industrial grounds, the phase-transition might dramatically affect the aerodynamics, the performance and the rangeability of the compressor. On the scientific ground, the modelling of two-phase flows in transonic/supersonic conditions still remains an open issue that demands a thorough experimental assessment. This work illustrates the results of a wide experimental campaign focused on the evaluation of the operative map of a MW-scale high-load sCO2 compressor operating in plant-representative conditions, i.e. in proximity to the critical point (P = 79.8 bar, T = 33°C), designed in the frame of the sCO2Flex project, EU Horizon 2020 funded program (grant agreement #764690). In the design process, the machine had been object of a thorough computational investigation, performed by using a homogeneous equilibrium model equipped with a barotropic equation of state, which revealed a significant impact of the phase change on the compressor aerodynamics and on its rangeability for flow rates higher than the design one. Such phenomena are connected to the sudden drop of the speed of sound, originated when the fluid thermodynamic condition crosses the saturation line, and they weaken as the compressor loading reduces. Experiments carried out on a first of a kind 5 MW sCO2 prototype compressor manufactured and tested by Baker Hughes in 2021 remarkably well matched the predicted compressor performance and, especially, the anticipated and sudden choking of the compressor at nominal peripheral Mach number. Results demonstrates experimentally, for the first time ever, the effects of the phase-change on the operation of a realistic sCO2 compressor, also providing significant insights on the predictive capabilities of the physical models employed for the calculation of two-phase flows in this class of machines

Neurophysiological Markers of Premotor–Motor Network Plasticity Predict Motor Performance in Young and Older Adults

Aging is commonly associated with a decline in motor control and neural plasticity. Tuning cortico–cortical interactions between premotor and motor areas is essential for controlling fine manual movements. However, whether plasticity in premotor–motor circuits predicts hand motor abilities in young and elderly humans remains unclear. Here, we administered transcranial magnetic stimulation (TMS) over the ventral premotor cortex (PMv) and primary motor cortex (M1) using the cortico–cortical paired-associative stimulation (ccPAS) protocol to manipulate the strength of PMv-to-M1 connectivity in 14 young and 14 elderly healthy adults. We assessed changes in motor-evoked potentials (MEPs) during ccPAS as an index of PMv-M1 network plasticity. We tested whether the magnitude of MEP changes might predict interindividual differences in performance in two motor tasks that rely on premotor-motor circuits, i.e., the nine-hole pegboard test and a choice reaction task. Results show lower motor performance and decreased PMv-M1 network plasticity in elderly adults. Critically, the slope of MEP changes during ccPAS accurately predicted performance at the two tasks across age groups, with larger slopes (i.e., MEP increase) predicting better motor performance at baseline in both young and elderly participants. These findings suggest that physiological indices of PMv-M1 plasticity could provide a neurophysiological marker of fine motor control across age-groups

Increasing associative plasticity in temporo-occipital back-projections improves visual perception of emotions

The posterior superior temporal sulcus (pSTS) is a critical node in a network specialized for perceiving emotional facial expressions that is reciprocally connected with early visual cortices (V1/V2). Current models of perceptual decision-making increasingly assign relevance to recursive processing for visual recognition. However, it is unknown whether inducing plasticity into reentrant connections from pSTS to V1/V2 impacts emotion perception. Using a combination of electrophysiological and neurostimulation methods, we demonstrate that strengthening the connectivity from pSTS to V1/V2 selectively increases the ability to perceive facial expressions associated with emotions. This behavior is associated with increased electrophysiological activity in both these brain regions, particularly in V1/V2, and depends on specific temporal parameters of stimulation that follow Hebbian principles. Therefore, we provide evidence that pSTS-to-V1/V2 back-projections are instrumental to perception of emotion from facial stimuli and functionally malleable via manipulation of associative plasticity. Temporo-occipital areas are involved in perceiving emotional faces