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<h1 style="margin-top:0in;background:white"><span style="font-size:12.0pt;font-family:"Times New Roman",serif;color:#222222">1.
</span><span style="font-size:12.0pt;font-family:"Times New Roman",serif;color:#121212">Apple introduces non-binary emojis with new set of inclusive faces: While celebrated, some in the LGBTQ community say it reinforces a fixed idea of what gender-neutral people
should look like </span><span style="font-size:12.0pt;font-family:"Times New Roman",serif"><a href="https://www.theguardian.com/technology/2019/oct/29/apple-emoji-non-binary-lgbtq-gender-neutral">https://www.theguardian.com/technology/2019/oct/29/apple-emoji-non-binary-lgbtq-gender-neutral</a></span><span style="font-size:12.0pt;font-family:"Times New Roman",serif;color:#121212"><o:p></o:p></span></h1>
<h3 style="mso-margin-top-alt:0in;margin-right:75.0pt;margin-bottom:1.5pt;margin-left:0in;line-height:14.25pt;background:white">
<span style="font-size:12.0pt;color:#222222;font-weight:normal"><o:p> </o:p></span></h3>
<h3 style="mso-margin-top-alt:0in;margin-right:75.0pt;margin-bottom:1.5pt;margin-left:0in;line-height:14.25pt;background:white">
<span style="font-size:12.0pt;color:#222222;font-weight:normal">2. Super article:
<a href="https://dl.acm.org/citation.cfm?id=3173889"><span style="color:#660099">Let's talk about race: Identity, chatbots, and AI</span></a><o:p></o:p></span></h3>
<p class="MsoNormal" style="background:white"><span style="color:#006621"><a href="https://scholar.google.com/citations?user=rzNTGL8AAAAJ&hl=en&oi=sra"><span style="color:#006621">A Schlesinger</span></a>, <a href="https://scholar.google.com/citations?user=vfZzNC8AAAAJ&hl=en&oi=sra"><span style="color:#006621">KP
O'Hara</span></a>, <a href="https://scholar.google.com/citations?user=ecxxlucAAAAJ&hl=en&oi=sra"><span style="color:#006621">AS Taylor</span></a> - … of the 2018 CHI Conference on …, 2018 - dl.acm.org<o:p></o:p></span></p>
<p class="MsoNormal" style="background:white"><span style="color:#222222">Why is it so hard for chatbots to talk about race? This work explores how the biased contents<br>
of databases, the syntactic focus of natural language processing, and the opaque nature of<br>
deep learning algorithms cause chatbots difficulty in handling race-talk. In each of these<br>
areas, the tensions between race and chatbots create new opportunities for people and<br>
machines. By making the abstract and disparate qualities of this problem space tangible, we..<o:p></o:p></span></p>
<p class="MsoNormal" style="background:white"><span style="color:#222222"><o:p> </o:p></span></p>
<h3 style="mso-margin-top-alt:0in;margin-right:75.0pt;margin-bottom:1.5pt;margin-left:0in;line-height:14.25pt;background:white">
<span style="font-size:12.0pt;color:#222222;font-weight:normal">3. Environmental considerations:</span><span style="font-size:12.0pt;color:#222222">
</span><span style="font-size:12.0pt;color:#222222;font-weight:normal"><a href="https://arxiv.org/abs/1906.02243"><span style="color:#660099">Energy and Policy Considerations for Deep Learning in NLP</span></a><o:p></o:p></span></h3>
<p class="MsoNormal" style="background:white"><span style="color:#006621"><a href="https://scholar.google.com/citations?user=UCDMtM0AAAAJ&hl=en&oi=sra"><span style="color:#006621">E Strubell</span></a>, <a href="https://scholar.google.com/citations?user=rdXPC84AAAAJ&hl=en&oi=sra"><span style="color:#006621">A
Ganesh</span></a>, <a href="https://scholar.google.com/citations?user=yILa1y0AAAAJ&hl=en&oi=sra"><span style="color:#006621">A McCallum</span></a> - arXiv preprint arXiv:1906.02243, 2019 - arxiv.org<o:p></o:p></span></p>
<p class="MsoNormal" style="background:white"><span style="color:#222222">Recent progress in hardware and methodology for training neural networks has ushered in<br>
a new generation of large networks trained on abundant data. These models have obtained<br>
notable gains in accuracy across many NLP tasks. However, these accuracy improvements<br>
depend on the availability of exceptionally large computational resources that necessitate<br>
similarly substantial energy consumption. As a result these models are costly to train and<br>
develop, both financially, due to the cost of hardware and electricity or cloud compute time …<o:p></o:p></span></p>
<p class="MsoNormal" style="background:white"><span style="color:#222222"><o:p> </o:p></span></p>
<h3 style="mso-margin-top-alt:0in;margin-right:75.0pt;margin-bottom:1.5pt;margin-left:0in;line-height:14.25pt;background:white">
<span style="font-size:12.0pt;color:#222222;font-weight:normal">4. </span><span class="gsct1"><span style="font-size:12.0pt;color:#1A0DAB">[PDF]</span></span><span style="font-size:12.0pt;color:#222222;font-weight:normal"> <a href="https://pdfs.semanticscholar.org/8140/f2a44d3bb698c6008def848c4d1f7f80b1de.pdf" id="5KNa164uASgJ"><span style="color:#660099">How
Computers See Gender: An Evaluation of Gender Classification in Commercial Facial Analysis and Image Labeling Services</span></a><o:p></o:p></span></h3>
<p class="MsoNormal" style="background:white"><span style="color:#006621"><a href="https://scholar.google.com/citations?user=BBMK69EAAAAJ&hl=en&oi=sra"><span style="color:#006621">MK SCHEUERMAN</span></a>, JM PAUL, <a href="https://scholar.google.com/citations?user=8LEH940AAAAJ&hl=en&oi=sra"><span style="color:#006621">J
BRUBAKER</span></a> - 2019 - pdfs.semanticscholar.org<o:p></o:p></span></p>
<p class="MsoNormal" style="background:white"><span style="color:#222222">MORGAN KLAUS SCHEUERMAN, JACOB M. PAUL, and JED R. BRUBAKER, University of<br>
Colorado Boulder Investigations of facial analysis (FA) technologies—such as facial detection<br>
and facial recognition—have been central to discussions about Artificial Intelligence's (AI) impact<br>
on human beings. Research on automatic </span><b><span style="color:black">gender</span></b><span style="color:#222222"> recognition, the classification of </span><b><span style="color:black">gender</span></b><span style="color:#222222"> by<br>
FA technologies, has raised potential concerns around issues of racial and </span><b><span style="color:black">gender</span></b><span style="color:#222222"> bias. In this<br>
study, we augment past work with empirical data by conducting a systematic analysis of </span><b><span style="color:black">how</span></b><span style="color:#222222"> …<o:p></o:p></span></p>
<h3 style="mso-margin-top-alt:0in;margin-right:75.0pt;margin-bottom:1.5pt;margin-left:0in;line-height:14.25pt;background:white">
<span style="font-size:12.0pt;color:#222222;font-weight:normal"><o:p> </o:p></span></h3>
<h3 style="mso-margin-top-alt:0in;margin-right:75.0pt;margin-bottom:1.5pt;margin-left:0in;line-height:14.25pt;background:white">
<span style="font-size:12.0pt;color:#222222;font-weight:normal">5. <a href="https://arxiv.org/abs/1906.11668">
<span style="color:#660099">Artificial Intelligence: the global landscape of ethics guidelines</span></a><o:p></o:p></span></h3>
<p class="MsoNormal" style="background:white"><span style="color:#006621"><a href="https://scholar.google.com/citations?user=Wbv6ytwAAAAJ&hl=en&oi=sra"><span style="color:#006621">A Jobin</span></a>, <a href="https://scholar.google.com/citations?user=lNGTwpMAAAAJ&hl=en&oi=sra"><span style="color:#006621">M
Ienca</span></a>, <a href="https://scholar.google.com/citations?user=nwRZpzEAAAAJ&hl=en&oi=sra"><span style="color:#006621">E Vayena</span></a> - arXiv preprint arXiv:1906.11668, 2019 - arxiv.org<o:p></o:p></span></p>
<p class="MsoNormal" style="background:white"><span style="color:#222222">In the last five years, private companies, research institutions as well as public sector<br>
organisations have issued principles and guidelines for ethical AI, yet there is debate about<br>
both what constitutes" ethical AI" and which ethical requirements, technical standards and<br>
best practices are needed for its realization. To investigate whether a global agreement on<br>
these questions is emerging, we mapped and analyzed the current corpus of principles and<br>
guidelines on ethical AI. Our results reveal a global convergence emerging around five …<o:p></o:p></span></p>
<p class="MsoNormal"><o:p> </o:p></p>
<h3 style="mso-margin-top-alt:0in;margin-right:75.0pt;margin-bottom:1.5pt;margin-left:0in;line-height:14.25pt;background:white">
<span style="font-size:12.0pt;color:#222222;font-weight:normal">6. <a href="https://www.karger.com/Article/Abstract/499840">
<span style="color:#660099">Men Have a Stronger Monocyte-Derived Cytokine Production Response upon Stimulation with the Gram-Negative Stimulus Lipopolysaccharide than Women: A …</span></a><o:p></o:p></span></h3>
<p class="MsoNormal" style="background:white"><span style="color:#006621"><a href="https://scholar.google.com/citations?user=hhyk6VAAAAAJ&hl=en&oi=sra"><span style="color:#006621">KGM Beenakker</span></a>, RGJ Westendorp… - Journal of innate …, 2019 - karger.com<o:p></o:p></span></p>
<p class="MsoNormal" style="background:white"><span style="color:#222222">The incidence of bacterial infections and sepsis, as well as the mortality risk from sepsis, is<br>
sex specific. These clinical findings have been attributed to sex differences in immune<br>
responsiveness. The aim of the present study was to investigate sex differences in monocyte-<br>
derived cytokine production response upon stimulation with the gram-negative stimulus<br>
lipopolysaccharide (LPS) using cytokine data from 15 study populations. Individual data on<br>
ex vivo cytokine production response upon stimulation with LPS in whole blood were …<o:p></o:p></span></p>
<p class="MsoNormal" style="background:white"><a href="https://www.fda.gov/media/130971/download">https://www.fda.gov/media/130971/download</a><o:p></o:p></p>
<p class="MsoNormal" style="background:white"><o:p> </o:p></p>
<p class="MsoNormal" style="text-autospace:none">7. <b>Work–Life Conflict and Its Health Effects on Korean Gastroenterologists According to Age and Sex<o:p></o:p></b></p>
<p class="MsoNormal" style="text-autospace:none">Eun Sun Jang1 · Seon Mee Park2 · Young Sook Park3 · Jong Chan Lee1 · Nayoung Kim1<o:p></o:p></p>
<p class="MsoNormal" style="text-autospace:none">Received: 23 July 2019 / Accepted: 10 September 2019<o:p></o:p></p>
<p class="MsoNormal" style="text-autospace:none">© Springer Science+Business Media, LLC, part of Springer Nature 2019<o:p></o:p></p>
<p class="MsoNormal" style="text-autospace:none"><b>Abstract<o:p></o:p></b></p>
<p class="MsoNormal" style="text-autospace:none">Background This study aimed to evaluate the work–life pattern and prevalence of occupation-related symptoms, as well as<o:p></o:p></p>
<p class="MsoNormal" style="text-autospace:none">the effect of work–life balance on health status according to age and sex among Korean gastroenterologists.<o:p></o:p></p>
<p class="MsoNormal" style="text-autospace:none">Methods A total of 222 gastroenterologists from 44 nationwide centers in South Korea participated in an anonymized<o:p></o:p></p>
<p class="MsoNormal" style="text-autospace:none">self-responded electronic questionnaire survey about their daily activities and symptoms for 14 days. Musculoskeletal,<o:p></o:p></p>
<p class="MsoNormal" style="text-autospace:none">gastrointestinal and mental symptoms were scored using a numerical scale. The Maslach Burnout Inventory was used to<o:p></o:p></p>
<p class="MsoNormal" style="text-autospace:none">measure the burnout score.<o:p></o:p></p>
<p class="MsoNormal" style="text-autospace:none">Results Korean gastroenterologists (124 men and 98 women) spent 71.5 ± 19.0 h/week for work (54.0 ± 16.2 in-hospital and<o:p></o:p></p>
<p class="MsoNormal" style="text-autospace:none">17.5 ± 9.5 out-of-hospital), without any differences regarding sex. However, women spent more time performing housework<o:p></o:p></p>
<p class="MsoNormal" style="text-autospace:none">and parenting (20.7 ± 19.0) compared to men (14.3 ± 13.3,
<i>P </i>= 0.007). Musculoskeletal pain was found in 199 respondents<o:p></o:p></p>
<p class="MsoNormal" style="text-autospace:none">(89.6%), and women had a higher total pain score compared to men in all age groups (<i>P
</i>= 0.016). Gastrointestinal and mental<o:p></o:p></p>
<p class="MsoNormal" style="text-autospace:none">symptoms were found in 119 (53.6%) and 153 (68.9%), respectively. Work–life ratio was significantly correlated with<o:p></o:p></p>
<p class="MsoNormal" style="text-autospace:none">musculoskeletal (<i>P </i>< 0.001), gastrointestinal (<i>P
</i>= 0.048) and mental symptoms (<i>P </i>= 0.003). Using the Maslach Burnout<o:p></o:p></p>
<p class="MsoNormal" style="text-autospace:none">Inventory, 64.4% of the respondents demonstrated burnout. Moreover, emotional exhaustion, depersonalization and personal<o:p></o:p></p>
<p class="MsoNormal" style="text-autospace:none">accomplishment scores were worst in women in their 30s or 40s.<o:p></o:p></p>
<p class="MsoNormal" style="text-autospace:none">Conclusion Korean gastroenterologists suffered from musculoskeletal, gastrointestinal and mental symptoms and were<o:p></o:p></p>
<p class="MsoNormal" style="text-autospace:none">highly prone to burnout due to long and laboring work. Work–life imbalance and burnout were most severe in young women<o:p></o:p></p>
<p class="MsoNormal" style="background:white">doctors due to their domestic demands.<o:p></o:p></p>
<p class="MsoNormal" style="background:white"><o:p> </o:p></p>
<p class="MsoNormal">8. There are more male than female specimens in natural history museums: Sex biases in bird and mammal natural history collections<o:p></o:p></p>
<p class="MsoNormal"><a href="https://royalsocietypublishing.org/doi/pdf/10.1098/rspb.2019.2025">https://royalsocietypublishing.org/doi/pdf/10.1098/rspb.2019.2025</a>;
<a href="https://www.nhm.ac.uk/discover/news/2019/october/more-male-than-female-specimens-in-natural-history-collections.html">
https://www.nhm.ac.uk/discover/news/2019/october/more-male-than-female-specimens-in-natural-history-collections.html</a><span style="color:#222222"><o:p></o:p></span></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">All best, Londa <o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Londa Schiebinger<o:p></o:p></p>
<p class="MsoNormal">Director, EU/US Gendered Innovations in Science, Health & Medicine, Engineering, and Environment Project
<o:p></o:p></p>
<p class="MsoNormal">John L. Hinds Professor of History of Science, Stanford University
<o:p></o:p></p>
<p class="MsoNormal"><a href="http://www.stanford.edu/dept/HPST/schiebinger.html"><span style="color:#0563C1">http://www.stanford.edu/dept/HPST/schiebinger.html</span></a><o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">______________________________________________________________________<o:p></o:p></p>
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