What is Interpretability?

Funder: Ernest Oppenheimer Memorial Trust (ZA)Funder: Williamson, Rausing and Lipton HPS Trust Fund (GB)Funder: Wellcome Trust; doi: https://doi.org/10.13039/100004440Funder: Cambridge Commonwealth, European and International Trust; doi: https://doi.org/10.13039/501100003343Funder: Cambridge Commonwealth Trust; doi: https://doi.org/10.13039/501100003342Funder: Social Sciences and Humanities Research Council of Canada; doi: https://doi.org/10.13039/501100000155We argue that artificial networks are explainable and offer a novel theory of interpretability. Two sets of conceptual questions are prominent in theoretical engagements with artificial neural networks, especially in the context of medical artificial intelligence: (1) Are networks explainable, and if so, what does it mean to explain the output of a network? And (2) what does it mean for a network to be interpretable? We argue that accounts of "explanation" tailored specifically to neural networks have ineffectively reinvented the wheel. In response to (1), we show how four familiar accounts of explanation apply to neural networks as they would to any scientific phenomenon. We diagnose the confusion about explaining neural networks within the machine learning literature as an equivocation on "explainability," "understandability" and "interpretability." To remedy this, we distinguish between these notions, and answer (2) by offering a theory and typology of interpretation in machine learning. Interpretation is something one does to an explanation with the aim of producing another, more understandable, explanation. As with explanation, there are various concepts and methods involved in interpretation: Total or Partial, Global or Local, and Approximative or Isomorphic. Our account of "interpretability" is consistent with uses in the machine learning literature, in keeping with the philosophy of explanation and understanding, and pays special attention to medical artificial intelligence systems

Quantitative characterization of plastic deformation of single diamond crystals: A high pressure high temperature (HPHT) experimental deformation study combined with electron backscatter diffraction (EBSD)

We report the results of a high-pressure high-temperature (HPHT) experimental investigation into the deformation of diamonds using the D-DIA apparatus. Electron backscatter diffraction (EBSD) data confirm that well-defined 300–700 nm wide {111} slip lamellae are in fact deformation micro-twins with a 60° rotation around a axis. Such twins formed at high confining pressures even without any apparatus-induced differential stress; mechanical anisotropy within the cell assembly was sufficient for their formation with very little subsequent lattice bending ( slip system dominates as expected for the face-centred cubic (FCC) structure of diamond. Slip occurs on multiple {111} planes resulting in rotation around axes. Deformation microstructure characteristics depend on the orientation of the principal stress axes and finite strain but are independent of confining pressure and nitrogen content. All of the uniaxially deformed samples took on a brown colour, irrespective of their initial nitrogen characteristics. This is in contrast to the two quasi-hydrostatic experiments, which retained their original colour (colourless for nitrogen free diamond, yellow for single substitutional nitrogen, Type Ib diamond) despite the formation of {111} twin lamellae. Comparison of our experimental data with those from two natural brown diamonds from Finsch mine (South Africa) shows the same activation of the dominant slip system. However, no deformation twin lamellae are present in the natural samples. This difference may be due to the lower strain rates experienced by the natural samples investigated. Our study shows the applicability and potential of this type of analysis to the investigation of plastic deformation of diamonds under mantle conditions

Confidentiality and public protection: ethical dilemmas in qualitative research with adult male sex offenders

This paper considers the ethical tensions present when engaging in in-depth interviews with convicted sex offenders. Many of the issues described below are similar to those found in other sensitive areas of research. However, confidentiality and public protection are matters that require detailed consideration when the desire to know more about men who have committed serious and harmful offences is set against the possibility of a researcher not disclosing previously unknown sensitive information that relates to the risk of someone being harmed.</p

What do the JAMA editors say when they discuss manuscripts that they are considering for publication? Developing a schema for classifying the content of editorial discussion

<p>Abstract</p> <p>Background</p> <p>In an effort to identify previously unrecognized aspects of editorial decision-making, we explored the words and phrases that one group of editors used during their meetings.</p> <p>Methods</p> <p>We performed an observational study of discussions at manuscript meetings at <it>JAMA</it>, a major US general medical journal. One of us (KD) attended 12 editorial meetings in 2003 as a visitor and took notes recording phrases from discussion surrounding 102 manuscripts. In addition, editors attending the meetings completed a form for each manuscript considered, listing the reasons they were inclined to proceed to the next step in publication and reasons they were not (DR attended 4/12 meetings). We entered the spoken and written phrases into NVivo 2.0. We then developed a schema for classifying the editors' phrases, using an iterative approach.</p> <p>Results</p> <p>Our classification schema has three main themes: science, journalism, and writing. We considered 2,463 phrases, of which 87 related mainly to the manuscript topic and were not classified (total 2,376 classified). Phrases related to science predominated (1,274 or 54%). The editors, most of whom were physicians, also placed major weight on goals important to JAMA's mission (journalism goals) such as importance to medicine, strategic emphasis for the journal, interest to the readership, and results (729 or 31% of phrases). About 16% (n = 373) of the phrases used related to writing issues, such as clarity and responses to the referees' comments.</p> <p>Conclusion</p> <p>Classification of editorial discourse provides insight into editorial decision making and concepts that need exploration in future studies.</p

Selective-logging and oil palm: Multitaxon impacts, biodiversity indicators, and trade-offs for conservation planning

Strong global demand for tropical timber and agricultural products has driven large-scale logging and subsequent conversion of tropical forests. Given that the majority of tropical landscapes have been or will likely be logged, the protection of biodiversity within tropical forests thus depends on whether species can persist in these economically exploited lands, and if species cannot persist, whether we can protect enough primary forest from logging and conversion. However, our knowledge of the impact of logging and conversion on biodiversity is limited to a few taxa, often sampled in different locations with complex land-use histories, hampering attempts to plan cost-effective conservation strategies and to draw conclusions across taxa. Spanning a land-use gradient of primary forest, once- and twice-logged forests, and oil palm plantations, we used traditional sampling and DNA metabarcoding to compile an extensive data set in Sabah, Malaysian Borneo for nine vertebrate and invertebrate taxa to quantify the biological impacts of logging and oil palm, develop cost-effective methods of protecting biodiversity, and examine whether there is congruence in response among taxa. Logged forests retained high species richness, including, on average, 70% of species found in primary forest. In contrast, conversion to oil palm dramatically reduces species richness, with significantly fewer primary-forest species than found on logged forest transects for seven taxa.Using a systematic conservation planning analysis, we show that efficient protection of primary-forest species is achieved with land portfolios that include a large proportion of logged-forest plots. Protecting logged forests is thus a cost-effective method of protecting an ecologically and taxonomically diverse range of species, particularly when conservation budgets are limited. Six indicator groups (birds, leaf-litter ants, beetles, aerial hymenopterans, flies, and true bugs) proved to be consistently good predictors of the response of the other taxa to logging and oil palm. Our results confidently establish the high conservation value of logged forests and the low value of oil palm. Cross-taxon congruence in responses to disturbance also suggests that the practice of focusing on key indicator taxa yields important information of general biodiversity in studies of logging and oil palm

Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur

Sex differences in the movement patterns of free-ranging chimpanzees (Pan troglodytes schweinfurthii): foraging and border checking

Most social primates live in cohesive groups, so travel paths inevitably reflect compromise: decision processes of individuals are obscured. The fission-fusion social organisation of the chimpanzee, however, allows an individual’s movements to be investigated independently. We followed 15 chimpanzees (8 male and 7 female) through the relatively flat forest of Budongo, Uganda, plotting the path of each individual over periods of 1-3 days. Chimpanzee movement was parsed into phases ending with halts of more than 20 minutes, during which individuals fed, rested or engaged in social activities. Males, lactating or pregnant females, and sexually receptive females all travelled similar average distances between halts, at similar speeds, and along similarly direct beeline paths. Compared to lactating or pregnant females, males did travel for a significantly longer time each day and halted more often, but the most striking sex differences appeared in the organisation of movement phases into a day’s path. After a halt, males tended to continue in the same direction as before. Lactating or pregnant females showed no such strategy and often retraced the preceding phase, returning to previously visited food patches. We suggest that female chimpanzee movements approximate an optimal solution to feeding requirements, whereas the paths of males allow integration of foraging with territorial defence. The ‘continually moving forwards’ strategy of males enables them to monitor their territory boundaries – border checking – whilst foraging, generally avoiding the explicit boundary patrols observed at other chimpanzee study sites

Negotiation in strategy making teams : group support systems and the process of cognitive change

This paper reports on the use of a Group Support System (GSS) to explore at a micro level some of the processes manifested when a group is negotiating strategy-processes of social and psychological negotiation. It is based on data from a series of interventions with senior management teams of three operating companies comprising a multi-national organization, and with a joint meeting subsequently involving all of the previous participants. The meetings were concerned with negotiating a new strategy for the global organization. The research involved the analysis of detailed time series data logs that exist as a result of using a GSS that is a reflection of cognitive theory

Revision and Update of the Consensus Definitions of Invasive Fungal Disease From the European Organization for Research and Treatment of Cancer and the Mycoses Study Group Education and Research Consortium.

BACKGROUND: Invasive fungal diseases (IFDs) remain important causes of morbidity and mortality. The consensus definitions of the Infectious Diseases Group of the European Organization for Research and Treatment of Cancer and the Mycoses Study Group have been of immense value to researchers who conduct clinical trials of antifungals, assess diagnostic tests, and undertake epidemiologic studies. However, their utility has not extended beyond patients with cancer or recipients of stem cell or solid organ transplants. With newer diagnostic techniques available, it was clear that an update of these definitions was essential. METHODS: To achieve this, 10 working groups looked closely at imaging, laboratory diagnosis, and special populations at risk of IFD. A final version of the manuscript was agreed upon after the groups' findings were presented at a scientific symposium and after a 3-month period for public comment. There were several rounds of discussion before a final version of the manuscript was approved. RESULTS: There is no change in the classifications of "proven," "probable," and "possible" IFD, although the definition of "probable" has been expanded and the scope of the category "possible" has been diminished. The category of proven IFD can apply to any patient, regardless of whether the patient is immunocompromised. The probable and possible categories are proposed for immunocompromised patients only, except for endemic mycoses. CONCLUSIONS: These updated definitions of IFDs should prove applicable in clinical, diagnostic, and epidemiologic research of a broader range of patients at high-risk