gender


Is AI capable of tackling biased opinion? – Revain – Medium

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Along with recent notorious data security breaches AI today is probably the most controversial, yet most cherished subject in tech: it is looked upon as either blessing by the likes of Mark Zuckerberg, or being cursed and questioned by Elon Musk and Steven Hawking. Interestingly, those who are raising those concerns, are not really feared about robots taking over and massacring the humanity in'Terminator 2: Judgement Day' best tradition. What the AI-opponents are really worried about lies a bit deeper down: raising awareness of responsible deployment of AI in the era of machine learning algorithms and software becoming mass available. Securing unbiased AI that is not affected by human prejudice about race or gender has long been discussed by researchers. But is there any solid grounding for this fuss in the first place?


Is AI capable of tackling biased opinion? – Revain – Medium

#artificialintelligence

Along with recent notorious data security breaches AI today is probably the most controversial, yet most cherished subject in tech: it is looked upon as either blessing by the likes of Mark Zuckerberg, or being cursed and questioned by Elon Musk and Steven Hawking. Interestingly, those who are raising those concerns, are not really feared about robots taking over and massacring the humanity in'Terminator 2: Judgement Day' best tradition. What the AI-opponents are really worried about lies a bit deeper down: raising awareness of responsible deployment of AI in the era of machine learning algorithms and software becoming mass available. Securing unbiased AI that is not affected by human prejudice about race or gender has long been discussed by researchers. But is there any solid grounding for this fuss in the first place?


How more women in AI could change the world

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Have you ever wondered why so many companies program robots, virtual assistants, and AI with feminine traits? Have you ever pondered, if there were more women behind the algorithms, how AI would be different -- not just vocally and aesthetically, but functionally? With Alexa, Cortana, Siri, Google Home, and most GPS systems defaulting to female, there has been plenty of speculation over the ubiquity of demure, ladylike tones emitted from the speakers of modern machines. Research has demonstrated a greater affinity for female voices on the part of men and women alike, prompting big tech companies like Amazon to opt for "Alexa" over "Alexander." Still, it's impossible to ignore the gendered implications at play, even if consumer demand drives such decisions.


Discriminating algorithms: 5 times AI showed prejudice

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Modern life runs on intelligent algorithms. The data-devouring, self-improving computer programmes that underlie the artificial intelligence revolution already determine Google search results, Facebook news feeds and online shopping recommendations. Increasingly, they also decide how easily we get a mortgage or a job interview, the chances we will get stopped and searched by the police on our way home, and what penalties we face if we commit a crime, too. So they must be unimpeachable in their decision-making, right? Skewed input data, false logic or just the prejudices of their programmers mean AIs all too easily reproduce and even amplify human biases – as the following five examples show.


Five reasons why AI in Canada needs more women

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Over the course of the last few years, artificial intelligence (AI) has become recognized as one of the keys to solving some of the world's most complex issues, unlocking a level of growth and innovation that has never been seen before. Governments across the globe are now shifting gear, actively designing investment approaches, incentives and discussing regulatory frameworks to help their nations maintain a top spot in this emerging industry. And much like global counterparts, Canadian policy makers and industries are grappling with the challenge of regulating without stifling innovation. AI was a central focus at the 2017 annual business of AI conference hosted by Rotman's Creative Destruction Lab (CDL), a Canadian accelerator that builds AI-powered startups. At the conference, Canada's Prime Minister Justin Trudeau said the following about AI: "Let's be part of it and help shape it, and let's make sure we're benefiting from the innovations – in both the designing of them and the applications and the jobs."


How machine-learning code turns a mirror on its sexist, racist masters

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Be careful which words you feed into that machine-learning software you're building, and how. A study of news articles and books written during the 20th and 21st century has shown that not only are gender and ethnic stereotypes woven into our language, but that algorithms commonly used to train code can end up unexpectedly baking these biases into AI models. Basically, no one wants to see tomorrow's software picking up yesterday's racism and sexism. A paper published in the Proceedings of the US National Academy of Sciences on Tuesday describes how word embeddings, a common set of techniques used by machine-leaning applications to develop associations between words, can pick up social attitudes towards men and women, and people of different ethnicities, from old articles and novels. In word-embedding models, an algorithm converts each word into a mathematical vector and maps it to a latent space.


Why Artificial Intelligence needs women

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Artificial Intelligence seems to be reinforcing gender stereotypes. In 2016, a university professor from Virginia noticed that the image recognition system he was working on often associated picture of kitchens with women. Intrigued, he and his colleagues tested large collections of photos used to train this kind of software. What they discovered was shocking. The software's depiction of common activities showed a definite gender bias.


AI can now tell if you're a man or a woman, just by your smile

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Men and women have different patterns of smiling, new research reports -- and this, the authors add, can allow AI to easily distinguish between the genders. Image credits Benjamin D. Glass / U.S. Navy. Many a man has been enraptured by the right smile, and many more will probably follow -- although the opposite doesn't seem to hold true. Regardless, while romance unfolds across the world, one team of researchers from the University of Bradford is working to bring this subtle yet powerful gesture to bear in our interactions with artificial intelligence (AI). According to them, computers can learn to differentiate between men or women simply by observing a smile.


AI assistants are sexist and understand men better

Daily Mail

Digital personal assistants, such as Amazon's Alexa and Apple's Siri, are sexist, according to one expert. They struggle to understand quiet and'breathy' voices of women compared with the deeper voices of men. The software is often developed with the help of male voice examples and so lacks a deeper understanding of female commands. The comment was made by Delip Rao, the CEO and co-founder of R7 Speech Sciences, a company that uses artificial intelligence to understand speech. Voice recognition software is built-in to most modern devices and has been around for years.


Psst .. 5 Things Your Boss Desperately Needs Reverse Mentoring In

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Here's something you can bet on: Your youngest employees are already way smarter than you in lots of areas. As a leader, are you taking the time to learn from them? For bosses and senior leaders, staying relevant and effective means finding a way to keep up to date on what's just coming on the radar--and that's where reverse mentoring comes in. Reverse mentoring--in essence, learning from younger employees--isn't a new approach. But, in my experience, it's sadly underutilized.