Towards a legal definition of machine intelligence: the argument for artificial personhood in the age of deep learning.

The paper dissects the intricacies of Automated Decision Making (ADM) and urges for refining the current legal definition of AI when pinpointing the role of algorithms in the advent of ubiquitous computing, data analytics and deep learning. ADM relies upon a plethora of algorithmic approaches and has already found a wide range of applications in marketing automation, social networks, computational neuroscience, robotics, and other fields. Our main aim here is to explain how a thorough understanding of the layers of ADM could be a first good step towards this direction: AI operates on a formula based on several degrees of automation employed in the interaction between the programmer, the user, and the algorithm; this can take various shapes and thus yield different answers to key issues regarding agency. The paper offers a fresh look at the concept of "Machine Intelligence", which exposes certain vulnerabilities in its current legal interpretation. Most importantly, it further helps us to explore whether the argument for "artificial personhood" holds any water. To highlight this argument, analysis proceeds in two parts: Part 1 strives to provide a taxonomy of the various levels of automation that reflects distinct degrees of Human - Machine interaction and can thus serve as a point of reference for outlining distinct rights and obligations of the programmer and the consumer: driverless cars are used as a case study to explore the several layers of human and machine interaction. These different degrees of automation reflect various levels of complexities in the underlying algorithms, and pose very interesting questions in terms of agency and dynamic tasks carried out by software agents. Part 2 further discusses the intricate nature of the underlying algorithms and artificial neural networks (ANN) that implement them and considers how one can interpret and utilize observed patterns in acquired data. Is "artificial personhood" a sufficient legal response to highly sophisticated machine learning techniques employed in decision making that successfully emulate or even enhance human cognitive abilities

A study into the layers of automated decision-making: emergent normative and legal aspects of deep learning

The paper dissects the intricacies of automated decision making (ADM) and urges for refining the current legal definition of artificial intelligence (AI) when pinpointing the role of algorithms in the advent of ubiquitous computing, data analytics and deep learning. Whilst coming up with a toolkit to measure algorithmic determination in automated/semi-automated tasks might be proven to be a tedious task for the legislator, our main aim here is to explain how a thorough understanding of the layers of ADM could be a first good step towards this direction: AI operates on a formula based on several degrees of automation employed in the interaction between the programmer, the user, and the algorithm. The paper offers a fresh look at AI, which exposes certain vulnerabilities in its current legal interpretation. To highlight this argument, analysis proceeds in two parts: Part 1 strives to provide a taxonomy of the various levels of automation that reflects distinct degrees of human–machine interaction. Part 2 further discusses the intricate nature of AI algorithms and considers how one can utilize observed patterns in acquired data. Finally, the paper explores the legal challenges that result from user empowerment and the requirement for data transparency

Monitoring the impact of desert dust outbreaks for air quality for health studies

We review the major features of desert dust outbreaks that are relevant to the assessment of dust impacts upon human health. Our ultimate goal is to provide scientific guidance for the acquisition of relevant population exposure information for epidemiological studies tackling the short and long term health effects of desert dust. We first describe the source regions and the typical levels of dust particles in regions close and far away from the source areas, along with their size, composition, and bio-aerosol load. We then describe the processes by which dust may become mixed with anthropogenic particulate matter (PM) and/or alter its load in receptor areas. Short term health effects are found during desert dust episodes in different regions of the world, but in a number of cases the results differ when it comes to associate the effects to the bulk PM, the desert dust-PM, or non-desert dust-PM. These differences are likely due to the different monitoring strategies applied in the epidemiological studies, and to the differences on atmospheric and emission (natural and anthropogenic) patterns of desert dust around the world. We finally propose methods to allow the discrimination of health effects by PM fraction during dust outbreaks, and a strategy to implement desert dust alert and monitoring systems for health studies and air quality management.The systematic review was funded by WHO with as part of a Grant Agreement with Ministry of Foreign Affairs, Norway. Thanks are also given to the Spanish Ministry for the Ecological Transition for long term support in the last 2 decades to our projects on African dust effects on air quality over Spain; to the Spanish Ministry of Science, Innovation and Universities and FEDER Funds for the HOUSE project (CGL2016-78594-R), and to the Generalitat de Catalunya (AGAUR 2017 SGR41). Carlos Pérez García-Pando acknowledges long-term support from the AXA Research Fund, as well as the support received through the Ramón y Cajal program (grant RYC-2015-18690) of the Spanish Ministry of Science, Innovation and Universities.Peer ReviewedPostprint (published version

Estimation of the road dust contribution in the urban aerosol

The urban area of Madrid (Spain), as in many other cities worldwide, is characterized by poor ambient air quality. Previous studies in the area have pointed out traffic as the main source of fine particles, while dust resuspension was found to be responsible for elevated levels of coarse particles (Querol et al, 2004). Street washing is one of the methods that might reduce the dust resuspension. The aim of this study was to quantify the contribution of road dust to particulate matter and evaluate the effects of street washing on the strength of resuspensio

Thermal-optical analysis for the measurement of elemental carbon (EC) and organic carbon (OC) in ambient air a literature review

Thermal-optical analysis is currently under consideration by the European standardization body (CEN) as the reference method to quantitatively determine organic carbon (OC) and elemental carbon (EC) in ambient air. This paper presents an overview of the critical parameters related to the thermal-optical analysis including thermal protocols, critical factors and interferences of the methods examined, method inter-comparisons, inter-laboratory exercises, biases and artifacts, and reference materials. The most commonly used thermal protocols include NIOSH-like, IMPROVE_A and EUSAAR_2 protocols either with light transmittance or reflectance correction for charring. All thermal evolution protocols are comparable for total carbon (TC) concentrations but the results vary significantly concerning OC and especially EC concentrations. Thermal protocols with a rather low peak temperature in the inert mode like IMPROVE_A and EUSAAR_2 tend to classify more carbon as EC compared to NIOSH-like protocols, while charring correction based on transmittance usually leads to smaller EC values compared to reflectance. The difference between reflectance and transmittance correction tends to be larger than the difference between different thermal protocols. Nevertheless, thermal protocols seem to correlate better when reflectance is used as charring correction method. The difference between EC values as determined by the different protocols is not only dependent on the optical pyrolysis correction method, but also on the chemical properties of the samples due to different contributions from various sources. The overall conclusion from this literature review is that it is not possible to identify the "best" thermal-optical protocol based on literature data only, although differences attributed to the methods have been quantified when possible.This work was undertaken under Mandate M/503 “Standardisation mandate to CEN, CENELEC and ETSI in support of the implementation of the Ambient Air Quality Legislation”, ENX “Ambient air – Measurement of airborne lemental carbon (EC) and organic carbon (OC) in PM 2.5 deposited on filters”.EUR 1,920 APC fee funded by the EC FP7 Post-Grant Open Access PilotPeer reviewe

ECOC comparison exercise with identical thermal protocols after temperature offset correction - Instrument diagnostics by in-depth evaluation of operational parameters

© Author(s) 2015. A comparison exercise on thermal-optical elemental carbon/organic carbon (ECOC) analysers was carried out among 17 European laboratories. Contrary to previous comparison exercises, the 17 participants made use of an identical instrument set-up, after correcting for temperature offsets with the application of a recently developed temperature calibration kit (Sunset Laboratory Inc, OR, US). Temperature offsets reported by participants ranged from -93 to +100 °C per temperature step. Five filter samples and two sucrose solutions were analysed with both the EUSAAR2 and NIOSH870 thermal protocols. z scores were calculated for total carbon (TC); nine outliers and three stragglers were identified. Three outliers and eight stragglers were found for EC. Overall, the participants provided results between the warning levels with the exception of two laboratories that showed poor performance, the causes of which were identified and corrected through the course of the comparison exercise. The TC repeatability and reproducibility (expressed as relative standard deviations) were 11 and 15% for EUSAAR2 and 9.2 and 12% for NIOSH870; the standard deviations for EC were 15 and 20% for EUSAAR2 and 20 and 26% for NIOSH870. TC was in good agreement between the two protocols, TCNIOSH870 =0.98 × TCEUSAAR2 (R2 = 1.00, robust means). Transmittance (TOT) calculated EC for NIOSH870 was found to be 20% lower than for EUSAAR2, ECNIOSH870 = 0.80 × ECEUSAAR2 (R2 = 0.96, robust means). The thermograms and laser signal values were compared and similar peak patterns were observed per sample and protocol for most participants. Notable deviations from the typical patterns indicated either the absence or inaccurate application of the temperature calibration procedure and/or pre-oxidation during the inert phase of the analysis. Low or zero pyrolytic organic carbon (POC), as reported by a few participants, is suggested as an indicator of an instrument-specific pre-oxidation. A sample-specific pre-oxidation effect was observed for filter G, for all participants and both thermal protocols, indicating the presence of oxygen donors on the suspended particulate matter. POC (TOT) levels were lower for NIOSH870 than for EUSAAR2, which is related to the heating profile differences of the two thermal protocols

Emission factors from road dust resuspension in a Mediterranean freeway

Particulate matter emissions from paved roads are currently one of the main challenges for a sustainable transport in Europe. Emissions are scarcely estimated due to the lack of knowledge about the resuspension process severely hampering a reliable simulation of PM and heavy metals concentrations in large cities and evaluation of population exposure. In this study the Emission Factors from road dust resuspension on a Mediterranean freeway were estimated per single vehicle category and PM component (OC, EC, mineral dust and metals) by means of the deployment of vertical profiles of passive samplers and terminal concentration estimate. The estimated PM10 emission factors varied from 12 to 47 mg VKT?1 (VKT: Vehicle Kilometer Traveled) with an average value of 22.7 ? 14.2 mg VKT?1. Emission Factors for heavy and light duty vehicles, passenger cars and motorbikes were estimated, based on average fleet composition and EPA ratios, in 187e733 mg VKT?1, 33e131 VKT?1, 9.4e36.9 VKT?1 and 0.8e3.3 VKT?1, respectively. These range of values are lower than previous estimates in Mediterranean urban roads, probably due to the lower dust reservoir on freeways. PM emitted material was dominated by mineral dust (9e10 mg VKT?1), but also OC and EC were found to be major components and approximately 14 e25% and 2e9% of average PM exhaust emissions from diesel passenger cars on highways respectively