Making a case for introspection

Defending first-person introspective access to own mental states, we argue against Carruthers' claim of mindreading being prior to meta-cognition and for a fundamental difference between how we understand our own and others' mental states. We conclude that a model based on one mechanism but involving two different kinds of access for self and other is sufficient and more consistent with the evidence

Search for evidence of trend slow-down in the long-term TOMS/SBUV total ozone data record: the importance of instrument drift uncertainty and fingerprint detection

International audienceWe have developed a merged ozone data (MOD) data set for the period October 1978 through October 2005 combining total ozone measurements (version 8 retrieval) from the TOMS (Nimbus 7, Meteor 3, and Earth Probe) and SBUV/SBUV2 (Nimbus 7, NOAA 9/11/16) series of satellite instruments. We use MOD to search for evidence of ozone recovery in response to the observed leveling off of chlorine compounds in the stratosphere. A crucial step in any time series analysis is the evaluation of uncertainties. In addition to the standard statistical time-series uncertainties, we evaluate the possible instrumental drift uncertainty for the MOD data set. We combine these two sources of uncertainty and apply them to a cumulative sum of residuals (CUSUM) analysis for trend slow-down. For the quasi-global mean between 60° S and 60° N, the apparent slow-down in trend is found to be clearly significant if instrument uncertainties are ignored. When instrument uncertainties are added, the slow-down becomes marginally significant at the 2? level. For the mid-latitudes of the northern hemisphere (30° to 60° N) the trend slow-down is significant. For the mid-latitudes of the southern hemisphere (30° to 60° S) it is not significant. The fingerprint of ozone recovery expected from model calculations suggests both northern and southern mid-latitude total ozone levels should recover together. Our result fails this fingerprint test and is therefore not a demonstration of the response of total ozone to the leveling off of chlorine

Mindblind eyes: an absence of spontaneous theory of mind in Asperger syndrome

Adults with Asperger syndrome can understand mental states such as desires and beliefs (mentalizing) when explicitly prompted to do so, despite having impairments in social communication. We directly tested the hypothesis that such individuals nevertheless fail to mentalize spontaneously. To this end, we used an eye-tracking task that has revealed the spontaneous ability to mentalize in typically developing infants. We showed that, like infants, neurotypical adults’ (n = 17 participants) eye movements anticipated an actor’s behavior on the basis of her false belief. This was not the case for individuals with Asperger syndrome (n = 19). Thus, these individuals do not attribute mental states spontaneously, but they may be able to do so in explicit tasks through compensatory learning

Functional specialization within rostral prefrontal cortex (Area 10): a meta-analysis

One of the least well understood regions of the human brain is rostral prefrontal cortex, approximating Brodmann's area 10. Here, we investigate the possibility that there are functional subdivisions within this region by conducting a meta-analysis of 104 functional neuroimaging studies (using positron emission tomography/functional magnetic resonance imaging). Studies involving working memory and episodic memory retrieval were disproportionately associated with lateral activations, whereas studies involving mentalizing (i.e., attending to one's own emotions and mental states or those of other agents) were disproportionately associated with medial activations. Functional variation was also observed along a rostral-caudal axis, with studies involving mentalizing yielding relatively caudal activations and studies involving multiple-task coordination yielding relatively rostral activations. A classification algorithm was trained to predict the task, given the coordinates of each activation peak. Performance was well above chance levels (74% for the three most common tasks; 45% across all eight tasks investigated) and generalized to data not included in the training set. These results point to considerable functional segregation within rostral prefrontal cortex

Impaired Competence for Pretense in Children with Autism: Exploring Potential Cognitive Predictors.

Lack of pretense in children with autism has been explained by a number of theoretical explanations, including impaired mentalising, impaired response inhibition, and weak central coherence. This study aimed to empirically test each of these theories. Children with autism (n=60) were significantly impaired relative to controls (n=65) when interpreting pretense, thereby supporting a competence deficit hypothesis. They also showed impaired mentalising and response inhibition, but superior local processing indicating weak central coherence. Regression analyses revealed that mentalising significantly and independently predicted pretense. The results are interpreted as supporting the impaired mentalising theory and evidence against competing theories invoking impaired response inhibition or a local processing bias. The results of this study have important implications for treatment and intervention

Mitigating Gender Bias in Machine Learning Data Sets

Artificial Intelligence has the capacity to amplify and perpetuate societal biases and presents profound ethical implications for society. Gender bias has been identified in the context of employment advertising and recruitment tools, due to their reliance on underlying language processing and recommendation algorithms. Attempts to address such issues have involved testing learned associations, integrating concepts of fairness to machine learning and performing more rigorous analysis of training data. Mitigating bias when algorithms are trained on textual data is particularly challenging given the complex way gender ideology is embedded in language. This paper proposes a framework for the identification of gender bias in training data for machine learning.The work draws upon gender theory and sociolinguistics to systematically indicate levels of bias in textual training data and associated neural word embedding models, thus highlighting pathways for both removing bias from training data and critically assessing its impact.Comment: 10 pages, 5 figures, 5 Tables, Presented as Bias2020 workshop (as part of the ECIR Conference) - http://bias.disim.univaq.i

Estimating Uncertainty in Long Term Total Ozone Records from Multiple Sources

Total ozone measurements derived from the TOMS and SBUV backscattered solar UV instrument series cover the period from late 1978 to the present. As the SBUV series of instruments comes to an end, we look to the 10 years of data from the AURA Ozone Monitoring Instrument (OMI) and two years of data from the Ozone Mapping Profiler Suite (OMPS) on board the Suomi National Polar-orbiting Partnership satellite to continue the record. When combining these records to construct a single long-term data set for analysis we must estimate the uncertainty in the record resulting from potential biases and drifts in the individual measurement records. In this study we present a Monte Carlo analysis used to estimate uncertainties in the Merged Ozone Dataset (MOD), constructed from the Version 8.6 SBUV2 series of instruments. We extend this analysis to incorporate OMI and OMPS total ozone data into the record and investigate the impact of multiple overlapping measurements on the estimated error. We also present an updated column ozone trend analysis and compare the size of statistical error (error from variability not explained by our linear regression model) to that from instrument uncertainty

Branes: cosmological surprise and observational deception

Using some supernovae and CMB data, we constrain the Cardassian, Randall-Sundrum, and Dvali-Gabadadze-Porrati brane-inspired cosmological models. We show that a transient acceleration and an early loitering period are usually excluded by the data. Moreover, the three models are equivalent to some usual quintessence/ghost dark energy models defined by a barotropic index $\gamma_\phi$ depending on the redshift. We calculate this index for each model and show that they mimic a universe close to a $\Lambda CDM$ model today.Comment: 29 pages, 25 figure

Moebius strip enterprises and expertise in the creative industries: new challenges for lifelong learning?

The paper argues that the emergence of a new mode of production – co-configuration is generating new modes of expertise that EU policies for lifelong learning are not designed to support professionals to develop. It maintains that this change can be seen most clearly when we analyse Small and Medium Size (SMEs) enterprises in the creative industries. Drawing on concepts from Political Economy - ‘Moebius strip enterprise/expertise’ and Cultural Historical Activity Theory - project-object’ and the ‘space of reasons’, the paper highlights conceptually and through a case study of an SME in the creative industries what is distinctive about the new modes of expertise, before moving on to reconceptualise expertise and learning and to consider the implications of this reconceptualisation for EU policies for lifelong learning. The paper concludes that the new challenge for LLL is to support the development of new forms expertise that are difficult to credentialise, yet, are central to the wider European goal of realising a knowledge economy