From Implausible Artificial Neurons to Idealized Cognitive Models: Rebooting Philosophy of Artificial Intelligence

There is a vast literature within philosophy of mind that focuses on artificial intelligence, but hardly mentions methodological questions. There is also a growing body of work in philosophy of science about modeling methodology that hardly mentions examples from cognitive science. Here these discussions are connected. Insights developed in the philosophy of science literature about the importance of idealization provide a way of understanding the neural implausibility of connectionist networks. Insights from neurocognitive science illuminate how relevant similarities between models and targets are picked out, how modeling inferences are justified, and the metaphysical status of models

Cognitive Mechanisms and Computational Models: Explanation in Cognitive Neuroscience

Cognitive Neuroscience seeks to integrate cognitive psychology and neuroscience. I critique existing analyses of this integration project, and offer my own account of how it ought to be understood given the practices of researchers in these fields. A recent proposal suggests that integration between cognitive psychology and neuroscience can be achieved `seamlessly' via mechanistic explanation. Cognitive models are elliptical mechanism sketches, according to this proposal. This proposal glosses over several difficulties concerning the practice of cognitive psychology and the nature of cognitive models, however. Although psychology's information-processing models superficially resemble mechanism sketches, they in fact systematically include and exclude different kinds of information. I distinguish two kinds of information-processing model, neither of which specifies the entities and activities characteristic of mechanistic models, even sketchily. Furthermore, theory development in psychology does not involve the filling in of these missing details, but rather refinement of the sorts of models they start out as. I contrast the development of psychology's attention filter models with the development of neurobiology's models of sodium channel filtering. I argue that extending the account of mechanisms to include what I define as generic mechanisms provides a more promising route towards integration. Generic mechanisms are the in-the-world counterparts to abstract types. They thus have causal-explanatory powers which are shared by all the tokens that instantiate that type. This not only provides a way for generalizations to factor into mechanistic explanations, which allows for the `upward-looking' explanations needed for integrating cognitive models, but also solves some internal problems in the mechanism literature concerning schemas and explanatory relevance. I illustrate how generic mechanisms are discovered and used with examples from computational cognitive neuroscience. I argue that connectionist models can be understood as approximations to generic brain mechanisms, which resolves a longstanding philosophical puzzle as to their role. Furthermore, I argue that understanding scientific models in general in terms of generic mechanisms allows for a unified account of the types of inferences made in modeling and in experiment

From Implausible Artificial Neurons to Idealized Cognitive Models: Rebooting Philosophy of Artificial Intelligence

There is a vast literature within philosophy of mind that focuses on artificial intelligence, but hardly mentions methodological questions. There is also a growing body of work in philosophy of science about modeling methodology that hardly mentions examples from cognitive science. Here these discussions are connected. Insights developed in the philosophy of science literature about the importance of idealization provide a way of understanding the neural implausibility of connectionist networks. Insights from neurocognitive science illuminate how relevant similarities between models and targets are picked out, how modeling inferences are justified, and the metaphysical status of models

A feeling for the algorithm: Diversity, expertise and artificial intelligence

Diversity is often announced as a solution to ethical problems in artificial intelligence (AI), but what exactly is meant by diversity and how it can solve those problems is seldom spelled out. This lack of clarity is one hurdle to motivating diversity in AI. Another hurdle is that while the most common perceptions about what diversity is are too weak to do the work set out for them, stronger notions of diversity are often defended on normative grounds that fail to connect to the values that are important to decision-makers in AI. However, there is a long history of research in feminist philosophy of science and a recent body of work in social epistemology that taken together provide the foundation for a notion of diversity that is both strong enough to do the work demanded of it, and can be defended on epistemic grounds that connect with the values that are important to decision-makers in AI. We clarify and defend that notion here by introducing emergent expertise as a network phenomenon wherein groups of workers with expertise of different types can gain knowledge not available to any individual alone, as long as they have ways of communicating across types of expertise. We illustrate the connected epistemic and ethical benefits of designing technology with diverse groups of workers using the examples of an infamous racist soap dispenser, and the millimeter wave scanners used in US airport security

Fife Local Energy Masterplan

The way we generate and use energy has constantly changed. In recent decades it has become the role of the National Grid, gas network, and multinational energy companies to deliver nearly all the energy: heat, electricity and transport fuels. We interact with energy via familiar light switches, gas boilers and petrol stations. In the future, delivery of and demand for energy in Scotland will be transformed. The Scottish Government’s ambition is to see an increasing number of new sustainable energy and district heating networks developed across the country to make the best use of natural energy sources including unused and renewable heat. This can help cut carbon emissions, reduce fuel bills and combat fuel poverty. Energy Masterplanning can assist developers and local authorities plan this process better, provide for ‘future proofing’ for communities and assist in using energy more efficiently

Do High Frequency Ultrasound Images Support Clinical Skin Assessment?

High frequency ultrasound imaging has been reported as a potential method of identifying the suspected tissue damage in patients “at risk” of pressure ulceration. The aim of this study was to explore whether ultrasound images supported the clinical skin assessment in an inpatient population through identification of subcutaneous tissue damage. Skin on the heels and/or sacral coccygeal area of fifty vascular surgery inpatients was assessed clinically by tissue viability nurses and with ultrasound pre operatively and at least every other day until discharge. Images were compared to routine clinical skin assessment outcomes. Qualitative classification of ultrasound images did not match outcomes yielded through the clinical skin assessment. Images corresponding to 16 participants were classified as subgroup 3 damage at the heels (equivalent to grade 2 pressure ulceration); clinical skin assessment rated no heels as greater than grade 1a (blanching erythema). Conversely, all images captured of the sacral coccygeal area were classified as normal; the clinical skin assessment rated two participants as grade 1b (non-blanching erythema). Ultrasound imaging is a potentially useful adjunct to the clinical skin assessment in providing information about the underlying tissue. However, further longitudinal clinical assessment is required to characterise images against actual and “staged” pressure ulceration

Owning an overweight or underweight body: distinguishing the physical, experienced and virtual body

Our bodies are the most intimately familiar objects we encounter in our perceptual environment. Virtual reality provides a unique method to allow us to experience having a very different body from our own, thereby providing a valuable method to explore the plasticity of body representation. In this paper, we show that women can experience ownership over a whole virtual body that is considerably smaller or larger than their physical body. In order to gain a better understanding of the mechanisms underlying body ownership, we use an embodiment questionnaire, and introduce two new behavioral response measures: an affordance estimation task (indirect measure of body size) and a body size estimation task (direct measure of body size). Interestingly, after viewing the virtual body from first person perspective, both the affordance and the body size estimation tasks indicate a change in the perception of the size of the participant’s experienced body. The change is biased by the size of the virtual body (overweight or underweight). Another novel aspect of our study is that we distinguish between the physical, experienced and virtual bodies, by asking participants to provide affordance and body size estimations for each of the three bodies separately. This methodological point is important for virtual reality experiments investigating body ownership of a virtual body, because it offers a better understanding of which cues (e.g. visual, proprioceptive, memory, or a combination thereof) influence body perception, and whether the impact of these cues can vary between different setups

VectorBase: a home for invertebrate vectors of human pathogens

VectorBase () is a web-accessible data repository for information about invertebrate vectors of human pathogens. VectorBase annotates and maintains vector genomes providing an integrated resource for the research community. Currently, VectorBase contains genome information for two organisms: Anopheles gambiae, a vector for the Plasmodium protozoan agent causing malaria, and Aedes aegypti, a vector for the flaviviral agents causing Yellow fever and Dengue fever

Measuring coverage in MNCH: population HIV-free survival among children under two years of age in four African countries

BACKGROUND: Population-based evaluations of programs for prevention of mother-to-child HIV transmission (PMTCT) are scarce. We measured PMTCT service coverage, regimen use, and HIV-free survival among children ≤24 mo of age in Cameroon, Côte D'Ivoire, South Africa, and Zambia. Methods and FINDINGS: We randomly sampled households in 26 communities and offered participation if a child had been born to a woman living there during the prior 24 mo. We tested consenting mothers with rapid HIV antibody tests and tested the children of seropositive mothers with HIV DNA PCR or rapid antibody tests. Our primary outcome was 24-mo HIV-free survival, estimated with survival analysis. In an individual-level analysis, we evaluated the effectiveness of various PMTCT regimens. In a community-level analysis, we evaluated the relationship between HIV-free survival and community PMTCT coverage (the proportion of HIV-exposed infants in each community that received any PMTCT intervention during gestation or breastfeeding). We also compared our community coverage results to those of a contemporaneous study conducted in the facilities serving each sampled community. Of 7,985 surveyed children under 2 y of age, 1,014 (12.7%) were HIV-exposed. Of these, 110 (10.9%) were HIV-infected, 851 (83.9%) were HIV-uninfected, and 53 (5.2%) were dead. HIV-free survival at 24 mo of age among all HIV-exposed children was 79.7% (95% CI: 76.4, 82.6) overall, with the following country-level estimates: Cameroon (72.6%; 95% CI: 62.3, 80.5), South Africa (77.7%; 95% CI: 72.5, 82.1), Zambia (83.1%; 95% CI: 78.4, 86.8), and Côte D'Ivoire (84.4%; 95% CI: 70.0, 92.2). In adjusted analyses, the risk of death or HIV infection was non-significantly lower in children whose mothers received a more complex regimen of either two or three antiretroviral drugs compared to those receiving no prophylaxis (adjusted hazard ratio: 0.60; 95% CI: 0.34, 1.06). Risk of death was not different for children whose mothers received a more complex regimen compared to those given single-dose nevirapine (adjusted hazard ratio: 0.88; 95% CI: 0.45, 1.72). Community PMTCT coverage was highest in Cameroon, where 75 of 114 HIV-exposed infants met criteria for coverage (66%; 95% CI: 56, 74), followed by Zambia (219 of 444, 49%; 95% CI: 45, 54), then South Africa (152 of 365, 42%; 95% CI: 37, 47), and then Côte D'Ivoire (3 of 53, 5.7%; 95% CI: 1.2, 16). In a cluster-level analysis, community PMTCT coverage was highly correlated with facility PMTCT coverage (Pearson's r  = 0.85), and moderately correlated with 24-mo HIV-free survival (Pearson's r  = 0.29). In 14 of 16 instances where both the facility and community samples were large enough for comparison, the facility-based coverage measure exceeded that observed in the community. CONCLUSIONS: HIV-free survival can be estimated with community surveys and should be incorporated into ongoing country monitoring. Facility-based coverage measures correlate with those derived from community sampling, but may overestimate population coverage. The more complex regimens recommended by the World Health Organization seem to have measurable public health benefit at the population level, but power was limited and additional field validation is needed. Please see later in the article for the Editors' Summar