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Even computer algorithms can be biased. Scientists have different ideas of how to prevent that

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Scientists say they've developed a framework to make computer algorithms "safer" to use without creating bias based on race, gender or other factors. The trick, they say, is to make it possible for users to tell the algorithm what kinds of pitfalls to avoid – without having to know a lot about statistics or artificial intelligence. With this safeguard in place, hospitals, companies and other potential users who may be wary of putting machine learning to use could find it a more palatable tool for helping them solve problems, according to a report in this week's edition of the journal Science. Computer algorithms are used to make decisions in a range of settings, from courtrooms to schools to online shopping sites. The programs sort through huge amounts of data in search of useful patterns that can be applied to future decisions.


It's not just factories. A.I is coming for white-collar jobs too, new study says.

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When you think about automation, there's a good chance you think about robots in a factory or a warehouse. That's partially because a lot of automation that is starting to be utilized more and more has to do with robotics. However, as a new report from the Brookings Institute explains, it's not just blue collar jobs associated with physical labor that are under threat. Developments in robotics will contribute to the loss of largely blue-collar jobs, but will also AI threaten the high-paying jobs many of us are striving to one day obtain, according to the report. Robert Maxim, a research associate in the Metropolitan Policy Program at Brookings, tells Inverse automation is going to impact pretty much every kind of job.


Better-educated, higher-paid workers will be 'most affected' by AI, per new study

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That is, the jobs that are in the greatest danger of being disrupted, if not altogether displaced, by machines are occupied by blue-collar and front-line service workers--those in "lower- wage, lower-education roles" who perform rote tasks, as a report from the Brookings Institution framed it earlier this year. But a new study from Brookings, being released today, challenges this assumption, at least as it pertains to artificial intelligence. "White-collar, well-paid America--radiologists, legal professionals, optometrists, and many more--will likely get no free pass," it asserts. In fact, Brookings says, "better-educated, better-paid workers will be the most affected" by AI. This modified view is based on a novel research technique developed by a Stanford PhD student in economics named Michael Webb, who built his own algorithm to compare language from 16,400 AI patents with the specific words used to describe 769 different jobs in the government's official occupational database, known as O*NET.


Beyond The 'Smart' City: Get Ready For The 'Hyperconnected' City

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Whatever happened to the "smart city?" It's alive and well but morphing into the "hyperconnected city," powered by data analytics, artificial intelligence, Internet of Things (IoT), and other advanced technologies. Among the goals: Create new business opportunities, increase the efficiency of government processes, and improve public safety and health, according to a new study by research firm ESI ThoughtLab and sponsored by Oracle. Those benefits will come with a discernible return on investment that increases as connectivity expands, the report maintains. One surprising finding is the extent to which hyperconnected cities--even some with huge technology investments--admit to being largely unprepared for cyberattacks.


New Study: 64% of People Trust a Robot More Than Their Manager

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People have more trust in robots than their managers, according to the second annual AI at Work study conducted by Oracle and Future Workplace, a research firm preparing leaders for disruptions in recruiting, development and employee engagement. The study of 8,370 employees, managers and HR leaders across 10 countries, found that AI has changed the relationship between people and technology at work and is reshaping the role HR teams and managers need to play in attracting, retaining and developing talent. Contrary to common fears around how AI will impact jobs, employees, managers and HR leaders across the globe are reporting increased adoption of AI at work and many are welcoming AI with love and optimism. The increasing adoption of AI at work is having a significant impact on the way employees interact with their managers. As a result, the traditional role of HR teams and the manager is shifting.


Where Should AI Ethics Come From? Not Medicine, New Study Says - Web AI

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As fears about AI's disruptive potential have grown, AI ethics has come to the fore in recent years. Concerns around privacy, transparency and the ability of algorithms to warp social and political discourse in unexpected ways have resulted in a flurry of pronouncements from companies, governments, and even supranational organizations on how to conduct ethical AI development. The majority have focused on outlining high-level principles that should guide those building these systems. Whether by chance or by design, the principles they have coalesced around closely resemble those at the heart of medical ethics. But writing in Nature Machine Intelligence, Brent Mittelstadt from the University of Oxford points out that AI development is a very different beast to medicine, and a simple copy and paste won't work.


AI Develop Number Sense Taking Machines Closer to General Intelligence

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Numbers figure pretty high up on the list of what a computer can do well. While humans often struggle to split a restaurant bill, a modern computer can make millions of calculations in a mere second. Humans, however, have an innate and intuitive number sense that helped us, among other things, to build computers in the first place. Unlike a computer, a human knows when looking at four cats, four apples and the symbol 4 that they all have one thing in common – the abstract concept of "four" – without even having to count them. This illustrates the difference between the human mind and the machine, and helps explain why we are not even close to developing AIs with the broad intelligence that humans possess.


Do we trust artificial intelligence agents to mediate conflict? Not entirely: New study says we'll listen to virtual agents except when goings get tough

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Researchers from USC and the University of Denver created a simulation in which a three-person team was supported by a virtual agent avatar on screen in a mission that was designed to ensure failure and elicit conflict. The study was designed to look at virtual agents as potential mediators to improve team collaboration during conflict mediation. But in the heat of the moment, will we listen to virtual agents? While some of researchers (Gale Lucas and Jonathan Gratch of the USC Viterbi School Engineering and the USC Institute for Creative Technologies who contributed to this study), had previously found that one-on-one human interactions with a virtual agent therapist yielded more confessions, in this study "Conflict Mediation in Human-Machine Teaming: Using a Virtual Agent to Support Mission Planning and Debriefing," team members were less likely to engage with a male virtual agent named "Chris" when conflict arose. Participating members of the team did not physically accost the device (as we have seen humans attack robots in viral social media posts), but rather were less engaged and less likely to listen to the virtual agent's input once failure ensued and conflict arose among team members.


AI develops human-like number sense – taking us a step closer to building machines with general intelligence

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Numbers figure pretty high up on the list of what a computer can do well. While humans often struggle to split a restaurant bill, a modern computer can make millions of calculations in a mere second. Humans, however, have an innate and intuitive number sense that helped us, among other things, to build computers in the first place. Unlike a computer, a human knows when looking at four cats, four apples and the symbol 4 that they all have one thing in common – the abstract concept of "four" – without even having to count them. This illustrates the difference between the human mind and the machine, and helps explain why we are not even close to developing AIs with the broad intelligence that humans possess.


How an AI trained to read scientific papers could predict future discoveries

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"Can machines think?", asked the famous mathematician, code breaker and computer scientist Alan Turing almost 70 years ago. Today, some experts have no doubt that Artificial Intelligence (AI) will soon be able to develop the kind of general intelligence that humans have. But others argue that machines will never measure up. Although AI can already outperform humans on certain tasks – just like calculators – they can't be taught human creativity. After all, our ingenuity, which is sometimes driven by passion and intuition rather than logic and evidence, has enabled us to make spectacular discoveries – ranging from vaccines to fundamental particles.