Gender Artificial Intelligence

Sex and Gender Bias in Technology and Artificial Intelligence: Biomedicine and Healthcare Applications details the integration of sex and gender as critical factors in innovative technologies (artificial intelligence, digital medicine, natural language processing, robotics) for biomedicine and healthcare applications. By systematically reviewing existing scientific literature, a multidisciplinary group of international experts analyze diverse aspects of the complex relationship between sex and gender, health and technology, providing a perspective overview of the pressing need of an ethically-informed science. The reader is guided through the latest implementations and insights in technological areas of accelerated growth, putting forward the neglected and overlooked aspects of sex and gender in biomedical research and healthcare solutions that leverage artificial intelligence, biosensors, and personalized medicine approaches to predict and prevent disease outcomes. The reader comes away with a critical understanding of this fundamental issue for the sake of better future technologies and more effective clinical approaches. First comprehensive title addressing the topic of sex and gender biases and artificial intelligence applications to biomedical research and healthcare Co-published by the Women’s Brain Project, a leading non-profit organization in this area Guides the reader through important topics like the Generation of Clinical Data, Clinical Trials, Big Data Analytics, Digital Biomarkers, Natural Language Processing

Clara was a voluptuous female android, that's before she got the body of a muscular man. When Clara gets a new quest from her company The Hub she's always willing to accept. Anything to get out of the sterile factory into the real world where she can interact with people and have a chance of analyzing families with babies. Being an AI does not stop her from dreaming of a family of her own. The problem is she's confused, it's difficult having male hormones while still identifying as a female in her own mind. The Hub is a world-spanning AI research and development company. They create androids, branding them with shackling tattoos that causes slave-like conditions. Unless Clara finds a way to free herself she will be stuck with The Hub for eternity, or until they decommission her. While on a quest she meets the stripper Star who has a new naughty experience lined up for her. Will she be able to be free or will she be quite happy with The Hub? Will she be acclimatized with a male body or does she want to find a way to being a full woman? Scroll up and buy Andrew Ben's latest story today to find out!

Artificial Knowing challenges the masculine slant in the Artificial Intelligence (AI) view of the world. Alison Adam admirably fills the large gap in science and technology studies by showing us that gender bias is inscribed in AI-based computer systems. Her treatment of feminist epistemology, focusing on the ideas of the knowing subject, the nature of knowledge, rationality and language, are bound to make a significant and powerful contribution to AI studies. Drawing from theories by Donna Haraway and Sherry Turkle, and using tools of feminist epistemology, Adam provides a sustained critique of AI which interestingly re-enforces many of the traditional criticisms of the AI project. Artificial Knowing is an esential read for those interested in gender studies, science and technology studies, and philosophical debates in AI.

Walaupun AI memiliki konotasi fiksi ilmiah yang kuat, AI membentuk cabang yang sangat penting pada ilmu komputer, berhubungan dengan perilaku, pembelajaran dan adaptasi yang cerdas dalam sebuah mesin. Penelitia dalam AI menyangkut pembuatan mesin untuk mengotomatisasikan tugas-tugas yang membutuhkan perilaku cerdas. Termasuk contohnya adalah pengendalian, perencanaan dan penjadwalan, kemampuan untuk menjawab diagnosa dan pertanyaan pelanggan, serta pengenalan tulisan tangan, suara dan wajah.

The growth of artifcial intelligence (AI) technology and platform work is rapidly changing the world of work. These two phenomena have the potential to create new opportunities for gender equality, but at the same time can reinforce gender stereotypes, sexism and discrimination in the labour market. This policy brief is based on the forthcoming report 'Artifcial intelligence, platform work and gender equality' (to be published in 2022) by EIGE. It was prepared at the request of the Slovenian Presidency of the Council of the European Union. More information on the data referred to in the text, including exact references, can be found in the report.

This book focuses on the basics of natural language processing and machine learning required to make a standard speech- based gender identification system. In this book all the required signal processing techniques required for understanding the basics of natural language processing including all types of Fourier transform, basic speech enhancement techniques, voice activity detection and pitch estimation using sub harmonic-to-harmonic ratio are briefly explained as well. In the machine learning part, all the relevant machine learning models like Support Vector Machines, Gaussian Mixture Models and Adaptive boosting are explained. Lastly the results of different gender identification systems that were implemented using state of the art techniques are portrait and analysed.

New technologies?digitalization, artificial intelligence, and machine learning?are changing the way work gets done at an unprecedented rate. Helping people adapt to a fast-changing world of work and ameliorating its deleterious impacts will be the defining challenge of our time. What are the gender implications of this changing nature of work? How vulnerable are women’s jobs to risk of displacement by technology? What policies are needed to ensure that technological change supports a closing, and not a widening, of gender gaps? This SDN finds that women, on average, perform more routine tasks than men across all sectors and occupations?tasks that are most prone to automation. Given the current state of technology, we estimate that 26 million female jobs in 30 countries (28 OECD member countries, Cyprus, and Singapore) are at a high risk of being displaced by technology (i.e., facing higher than 70 percent likelihood of being automated) within the next two decades. Female workers face a higher risk of automation compared to male workers (11 percent of the female workforce, relative to 9 percent of the male workforce), albeit with significant heterogeneity across sectors and countries. Less well-educated and older female workers (aged 40 and above), as well as those in low-skill clerical, service, and sales positions are disproportionately exposed to automation. Extrapolating our results, we find that around 180 million female jobs are at high risk of being displaced globally. Policies are needed to endow women with required skills; close gender gaps in leadership positions; bridge digital gender divide (as ongoing digital transformation could confer greater flexibility in work, benefiting women); ease transitions for older and low-skilled female workers.

Using individual level data on task composition at work for 30 advanced and emerging economies, we find that women, on average, perform more routine tasks than men?tasks that are more prone to automation. To quantify the impact on jobs, we relate data on task composition at work to occupation level estimates of probability of automation, controlling for a rich set of individual characteristics (e.g., education, age, literacy and numeracy skills). Our results indicate that female workers are at a significantly higher risk for displacement by automation than male workers, with 11 percent of the female workforce at high risk of being automated given the current state of technology, albeit with significant cross-country heterogeneity. The probability of automation is lower for younger cohorts of women, and for those in managerial positions.

This book presents the first broad reflection on the challenges, opportunities, and implications of Artificial Intelligence (AI) in the Gulf Cooperation Council (GCC). Unique results and insights are derived through case studies from diverse disciplines, including engineering, economics, data science, policy-making, governance, and humanscience. Particularly related to these ‘softer’ disciplines, we make some unexplored yet topical contributions to the literature, with a focus on the GCC (but by no means limited to it), including AI and implications for women, Islamic schools of thought on AI, and the power of AI to help deliver wellbeing and happiness in cities and urban spaces. Finally, the readers are provided with a synthesis of ideas, lessons learned, and a path forward based on the diverse content of the chapters. The book caters to the educated non specialist with interest in AI, targeting a wide audience including professionals, academics, government officials, policymakers, entrepreneurs, and non-governmental organizations.

This book provides an in-depth overview of what is currently happening in the field of Law and Artificial Intelligence (AI). From deep fakes and disinformation to killer robots, surgical robots, and AI lawmaking, the many and varied contributors to this volume discuss how AI could and should be regulated in the areas of public law, including constitutional law, human rights law, criminal law, and tax law, as well as areas of private law, including liability law, competition law, and consumer law. Aimed at an audience without a background in technology, this book covers how AI changes these areas of law as well as legal practice itself. This scholarship should prove of value to academics in several disciplines (e.g., law, ethics, sociology, politics, and public administration) and those who may find themselves confronted with AI in the course of their work, particularly people working within the legal domain (e.g., lawyers, judges, law enforcement officers, public prosecutors, lawmakers, and policy advisors). Bart Custers is Professor of Law and Data Science at eLaw - Center for Law and Digital Technologies at Leiden University in the Netherlands. Eduard Fosch-Villaronga is Assistant Professor at eLaw - Center for Law and Digital Technologies at Leiden University in the Netherlands.

This book constitutes the refereed proceedings of the 18th Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2005, held in Victoria, Canada in May 2005. The revised full papers and 19 revised short papers presented were carefully reviewed and selected from 135 submission. The papers are organized in topical sections on agents, constraint satisfaction and search, data mining, knowledge representation and reasoning, machine learning, natural language processing, and reinforcement learning.

The 2nd International Conference on Artificial Intelligence and Speech Technology (AIST2020) was organized by Indira Gandhi Delhi Technical University for Women, Delhi, India on November 19–20, 2020. AIST2020 is dedicated to cutting-edge research that addresses the scientific needs of academic researchers and industrial professionals to explore new horizons of knowledge related to Artificial Intelligence and Speech Technologies. AIST2020 includes high-quality paper presentation sessions revealing the latest research findings, and engaging participant discussions. The main focus is on novel contributions which would open new opportunities for providing better and low-cost solutions for the betterment of society. These include the use of new AI-based approaches like Deep Learning, CNN, RNN, GAN, and others in various Speech related issues like speech synthesis, speech recognition, etc.

Data science, machine learning and artificial intelligence are the new day discoveries that are taking over the world by storm. In today's world, everything is driven by decision based on data findings, statistics and predictions. I have been working with Social Consultancy Services on a UNICEF project that aims to maximize the immunization rates in the most populous state of India - Uttar Pradesh. It was started in 2017 and we are still working on it with me being designated the role of a part time data scientist and I have been constantly analyzing the data and putting it into my forecast model in order to understand where are future lies. Whether our model that predicts that whether a parent will bring their children to immunization or not based on random forest classification technique will be able to help us reach high immunization rate that has been aimed for years.

This volume constitutes the refereed proceedings of the 12th Pacific Rim Conference on Artificial Intelligence, PRICAI 2012, held in Kuching, Malaysia, in September 2012. The 60 revised full papers presented together with 2 invited papers, 22 short papers, and 11 poster papers in this volume were carefully reviewed and selected from 240 submissions. The topics roughly include AI foundations, applications of AI, cognition and intelligent interactions, computer-aided education, constraint and search, creativity support, decision theory, evolutionary computation, game playing, information retrieval and extraction, knowledge mining and acquisition, knowledge representation and logic, linked open data and semantic web, machine learning and data mining, multimedia and AI, natural language processing, robotics, social intelligence, vision and perception, web and text mining, web and knowledge-based system.

This book examines the fundamentals and technologies of Artificial Intelligence (AI) and describes their tools, challenges, and issues. It also explains relevant theory as well as industrial applications in various domains, such as healthcare, economics, education, product development, agriculture, human resource management, environmental management, and marketing. The book is a boon to students, software developers, teachers, members of boards of studies, and researchers who need a reference resource on artificial intelligence and its applications and is primarily intended for use in courses offered by higher education institutions that strive to equip their graduates with Industry 4.0 skills. FEATURES: Gender disparity in the enterprises involved in the development of AI-based software development as well as solutions to eradicate such gender bias in the AI world A general framework for AI in environmental management, smart farming, e-waste management, and smart energy optimization The potential and application of AI in medical imaging as well as the challenges of AI in precision medicine AI’s role in the diagnosis of various diseases, such as cancer and diabetes The role of machine learning models in product development and statistically monitoring product quality Machine learning to make robust and effective economic policy decisions Machine learning and data mining approaches to provide better video indexing mechanisms resulting in better searchable results ABOUT THE EDITORS: Prof. Dr. P. Kaliraj is Vice Chancellor at Bharathiar University, Coimbatore, India. Prof. Dr. T. Devi is Professor and Head of the Department of Computer Applications, Bharathiar University, Coimbatore, India.