Gender Bias, Artificial Intelligence and Healthcare Books

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Sex and Gender Differences in Pharmacology


Sex and Gender Differences in Pharmacology
  • Author : Vera Regitz-Zagrosek
  • Publisher : Springer Science & Business Media
  • Release : 2012-10-02
  • ISBN : 9783642307263
  • Language : En, Es, Fr & De
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This is the very first book to deal with sex and gender differences in drug therapy - an increasingly recognized medical need. It starts with an overview on S/G in clinical syndromes and a documentation of the medical and socioeconomic damage caused by gender specific adverse drug effects. Part I covers S/G differences in pharmacokinetics. Researchers will be satisfied by the detailed discussion of the mechanisms of S/G differences in drug effects that represents cutting edge science and includes interaction of drugs with sex hormones, genomic and epigenetic mechanisms. It also covers S/G in drug development, in animal models and clinical development and S/G in drug prescriptions. Part II targets S/G differences in drug effects in cardiovascular, pulmonary, CNS, neuromuscular, neuropsychiatric and metabolic diseases, in cancer, inflammation, and rheumatic diseases, in bacterial and retroviral infections, thrombosis, embolism. New drugs will be discussed.

The Oxford Handbook of Ethics of AI


The Oxford Handbook of Ethics of AI
  • Author : Markus D. Dubber
  • Publisher : Oxford University Press
  • Release : 2020-06-30
  • ISBN : 9780190067410
  • Language : En, Es, Fr & De
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This volume tackles a quickly-evolving field of inquiry, mapping the existing discourse as part of a general attempt to place current developments in historical context; at the same time, breaking new ground in taking on novel subjects and pursuing fresh approaches. The term "A.I." is used to refer to a broad range of phenomena, from machine learning and data mining to artificial general intelligence. The recent advent of more sophisticated AI systems, which function with partial or full autonomy and are capable of tasks which require learning and 'intelligence', presents difficult ethical questions, and has drawn concerns from many quarters about individual and societal welfare, democratic decision-making, moral agency, and the prevention of harm. This work ranges from explorations of normative constraints on specific applications of machine learning algorithms today-in everyday medical practice, for instance-to reflections on the (potential) status of AI as a form of consciousness with attendant rights and duties and, more generally still, on the conceptual terms and frameworks necessarily to understand tasks requiring intelligence, whether "human" or "A.I."

Deep Medicine


Deep Medicine
  • Author : Eric Topol
  • Publisher : Basic Books
  • Release : 2019-03-12
  • ISBN : 9781541644649
  • Language : En, Es, Fr & De
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One of America's top doctors reveals how AI will empower physicians and revolutionize patient care Medicine has become inhuman, to disastrous effect. The doctor-patient relationship--the heart of medicine--is broken: doctors are too distracted and overwhelmed to truly connect with their patients, and medical errors and misdiagnoses abound. In Deep Medicine, leading physician Eric Topol reveals how artificial intelligence can help. AI has the potential to transform everything doctors do, from notetaking and medical scans to diagnosis and treatment, greatly cutting down the cost of medicine and reducing human mortality. By freeing physicians from the tasks that interfere with human connection, AI will create space for the real healing that takes place between a doctor who can listen and a patient who needs to be heard. Innovative, provocative, and hopeful, Deep Medicine shows us how the awesome power of AI can make medicine better, for all the humans involved.

Data Feminism


Data Feminism
  • Author : Catherine D'Ignazio
  • Publisher : MIT Press
  • Release : 2020-03-31
  • ISBN : 9780262358538
  • Language : En, Es, Fr & De
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A new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism. Today, data science is a form of power. It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought. Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever “speak for themselves.” Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed.

The Ethical Algorithm


The Ethical Algorithm
  • Author : Michael Kearns
  • Publisher : Oxford University Press
  • Release : 2019-10-04
  • ISBN : 9780190948221
  • Language : En, Es, Fr & De
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Over the course of a generation, algorithms have gone from mathematical abstractions to powerful mediators of daily life. Algorithms have made our lives more efficient, more entertaining, and, sometimes, better informed. At the same time, complex algorithms are increasingly violating the basic rights of individual citizens. Allegedly anonymized datasets routinely leak our most sensitive personal information; statistical models for everything from mortgages to college admissions reflect racial and gender bias. Meanwhile, users manipulate algorithms to "game" search engines, spam filters, online reviewing services, and navigation apps. Understanding and improving the science behind the algorithms that run our lives is rapidly becoming one of the most pressing issues of this century. Traditional fixes, such as laws, regulations and watchdog groups, have proven woefully inadequate. Reporting from the cutting edge of scientific research, The Ethical Algorithm offers a new approach: a set of principled solutions based on the emerging and exciting science of socially aware algorithm design. Michael Kearns and Aaron Roth explain how we can better embed human principles into machine code - without halting the advance of data-driven scientific exploration. Weaving together innovative research with stories of citizens, scientists, and activists on the front lines, The Ethical Algorithm offers a compelling vision for a future, one in which we can better protect humans from the unintended impacts of algorithms while continuing to inspire wondrous advances in technology.