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  1. Algorithmic impact assessments (AIA) are increasingly being proposed as a mechanism for algorithmic accountability. These assessments are seen as potentially useful for anticipating, avoiding, and mitigating the negative consequences of algorithmic decision-making systems (ADS). At the same time, what an AIA would entail remains under-specified. While promising, AIAs raise as many questions as they answer. Choices about the methods, scope, and purpose of impact assessments structure the possible governance outcomes. Decisions about what type of effects count as an impact, when impacts are assessed, whose interests are considered, who is invited to participate, who conducts the assessment, the public availability of the assessment, and what the outputs of the assessment might be all shape the forms of accountability that AIA proponents seek to encourage. These considerations remain open, and will determine whether and how AIAs can function as a viable governance mechanism in the broader algorithmic accountability toolkit, especially with regard to furthering the public interest. Because AlAs are still an incipient governance strategy, approaching them as social constructions that do not require a single or universal approach offers a chance to produce interventions that emerge from careful deliberation.
  2. Algorithmic impact assessments (AIAs) are an emergent form of accountability for entities that build and deploy automated decision-support systems. These are modeled after impact assessments in other domains. Our study of the history of impact assessments shows that "impacts" are an evaluative construct that enable institutions to identify and ameliorate harms experienced because of a policy decision or system. Every domain has different expectations and norms about what constitutes impacts and harms, how potential harms are rendered as the impacts of a particular undertaking, who is responsible for conducting that assessment, and who has the authority to act on the impact assessment to demand changes to that undertaking. By examining proposals for AIAs in relation to other domains, we find that there is a distinct risk of constructing algorithmic impacts as organizationally understandable metrics that are nonetheless inappropriately distant from the harms experienced by people, and which fall short of building the relationships required for effective accountability. To address this challenge of algorithmic accountability, and as impact assessments become a commonplace process for evaluating harms, the FAccT community should A) understand impacts as objects constructed for evaluative purposes, B) attempt to construct impacts as close as possible to actual harms,more »and C) recognize that accountability governance requires the input of various types of expertise and affected communities. We conclude with lessons for assembling cross-expertise consensus for the co-construction of impacts and to build robust accountability relationships.« less
  3. Abstract We measure the low- J CO line ratios R 21 ≡ CO (2–1)/CO (1–0), R 32 ≡ CO (3–2)/CO (2–1), and R 31 ≡CO (3–2)/CO (1–0) using whole-disk CO maps of nearby galaxies. We draw CO (2–1) from PHANGS-ALMA, HERACLES, and follow-up IRAM surveys; CO (1–0) from COMING and the Nobeyama CO Atlas of Nearby Spiral Galaxies; and CO (3–2) from the James Clerk Maxwell Telescope Nearby Galaxy Legacy Survey and Atacama Pathfinder Experiment Large APEX Sub-Millimetre Array mapping. All together, this yields 76, 47, and 29 maps of R 21 , R 32 , and R 31 at 20″ ∼ 1.3 kpc resolution, covering 43, 34, and 20 galaxies. Disk galaxies with high stellar mass, log ( M ⋆ / M ⊙ ) = 10.25 – 11 , and star formation rate (SFR) = 1–5 M ⊙ yr −1 , dominate the sample. We find galaxy-integrated mean values and a 16%–84% range of R 21 = 0.65 (0.50–0.83), R 32 = 0.50 (0.23–0.59), and R 31 = 0.31 (0.20–0.42). We identify weak trends relating galaxy-integrated line ratios to properties expected to correlate with excitation, including SFR/ M ⋆ and SFR/ L CO . Within galaxies, we measure centralmore »enhancements with respect to the galaxy-averaged value of ∼ 0.18 − 0.14 + 0.09 dex for R 21 , 0.27 − 0.15 + 0.13 dex for R 31 , and 0.08 − 0.09 + 0.11 dex for R 32 . All three line ratios anticorrelate with galactocentric radius and positively correlate with the local SFR surface density and specific SFR, and we provide approximate fits to these relations. The observed ratios can be reasonably reproduced by models with low temperature, moderate opacity, and moderate densities, in good agreement with expectations for the cold interstellar medium. Because the line ratios are expected to anticorrelate with the CO (1–0)-to-H 2 conversion factor, α CO 1 − 0 , these results have general implications for the interpretation of CO emission from galaxies.« less
    Free, publicly-accessible full text available March 1, 2023
  4. ABSTRACT When completed, the PHANGS–HST project will provide a census of roughly 50 000 compact star clusters and associations, as well as human morphological classifications for roughly 20 000 of those objects. These large numbers motivated the development of a more objective and repeatable method to help perform source classifications. In this paper, we consider the results for five PHANGS–HST galaxies (NGC 628, NGC 1433, NGC 1566, NGC 3351, NGC 3627) using classifications from two convolutional neural network architectures (RESNET and VGG) trained using deep transfer learning techniques. The results are compared to classifications performed by humans. The primary result is that the neural network classifications are comparable in quality to the human classifications with typical agreement around 70 to 80 per cent for Class 1 clusters (symmetric, centrally concentrated) and 40 to 70 per cent for Class 2 clusters (asymmetric, centrally concentrated). If Class 1 and 2 are considered together the agreement is 82 ± 3 per cent. Dependencies on magnitudes, crowding, and background surface brightness are examined. A detailed description of the criteria and methodology used for the human classifications is included along with an examination of systematic differences between PHANGS–HST and LEGUS. The distribution of data points in a colour–colour diagram is used as a ‘figure ofmore »merit’ to further test the relative performances of the different methods. The effects on science results (e.g. determinations of mass and age functions) of using different cluster classification methods are examined and found to be minimal.« less
  5. Abstract We present PHANGS–ALMA, the first survey to map CO J = 2 → 1 line emission at ∼1″ ∼100 pc spatial resolution from a representative sample of 90 nearby ( d ≲ 20 Mpc) galaxies that lie on or near the z = 0 “main sequence” of star-forming galaxies. CO line emission traces the bulk distribution of molecular gas, which is the cold, star-forming phase of the interstellar medium. At the resolution achieved by PHANGS–ALMA, each beam reaches the size of a typical individual giant molecular cloud, so that these data can be used to measure the demographics, life cycle, and physical state of molecular clouds across the population of galaxies where the majority of stars form at z = 0. This paper describes the scientific motivation and background for the survey, sample selection, global properties of the targets, Atacama Large Millimeter/submillimeter Array (ALMA) observations, and characteristics of the delivered data and derived data products. As the ALMA sample serves as the parent sample for parallel surveys with MUSE on the Very Large Telescope, the Hubble Space Telescope, AstroSat, the Very Large Array, and other facilities, we include a detailed discussion of the sample selection. We detail the estimationmore »of galaxy mass, size, star formation rate, CO luminosity, and other properties, compare estimates using different systems and provide best-estimate integrated measurements for each target. We also report the design and execution of the ALMA observations, which combine a Cycle 5 Large Program, a series of smaller programs, and archival observations. Finally, we present the first 1″ resolution atlas of CO emission from nearby galaxies and describe the properties and contents of the first PHANGS–ALMA public data release.« less
  6. ABSTRACT The spatial distribution of metals reflects, and can be used to constrain, the processes of chemical enrichment and mixing. Using PHANGS-MUSE optical integral field spectroscopy, we measure the gas-phase oxygen abundances (metallicities) across 7138 H ii regions in a sample of eight nearby disc galaxies. In Paper I, we measure and report linear radial gradients in the metallicities of each galaxy, and qualitatively searched for azimuthal abundance variations. Here, we examine the 2D variation in abundances once the radial gradient is subtracted, Δ(O/H), in order to quantify the homogeneity of the metal distribution and to measure the mixing scale over which H ii region metallicities are correlated. We observe low (0.03–0.05 dex) scatter in Δ(O/H) globally in all galaxies, with significantly lower (0.02–0.03 dex) scatter on small (<600 pc) spatial scales. This is consistent with the measurement uncertainties, and implies the 2D metallicity distribution is highly correlated on scales of ≲600 pc. We compute the two-point correlation function for metals in the disc in order to quantify the scale lengths associated with the observed homogeneity. This mixing scale is observed to correlate better with the local gas velocity dispersion (of both cold and ionized gas) than with the star formation rate. Selecting onlymore »H ii regions with enhanced abundances relative to a linear radial gradient, we do not observe increased homogeneity on small scales. This suggests that the observed homogeneity is driven by the mixing introducing material from large scales rather than by pollution from recent and on-going star formation.« less