Big data’s power is terrifying. That could be good news for democracy | George Monbiot Has a digital coup begun? Is big data being used, in the US and the UK, to create personalised political advertising, to bypass our rational minds and alter the way we vote? The short answer is probably not. A series of terrifying articles suggests that a company called Cambridge Analytica helped to swing both the US election and the EU referendum by mining data from Facebook and using it to predict people’s personalities, then tailoring advertising to their psychological profiles. None of this is to suggest we should not be vigilant. Our capacity to resist manipulation is limited. China shows how much worse this could become. That’s the bad news. A recent report by the innovation foundation Nesta argues that there are no quick or cheap digital fixes. Participation tends to be deep but narrow. Of course, there are hazards here. Either we own political technologies, or they will own us.
Tech Giants Grapple with the Ethical Concerns Raised by the AI Boom - MIT Technology Review This video isn't encoded for your device With great power comes great responsibility—and artificial-intelligence technology is getting much more powerful. Companies in the vanguard of developing and deploying machine learning and AI are now starting to talk openly about ethical challenges raised by their increasingly smart creations. “We’re here at an inflection point for AI,” said Eric Horvitz, managing director of Microsoft Research, at MIT Technology Review’s EmTech conference this week. “We have an ethical imperative to harness AI to protect and preserve over time.” Horvitz spoke alongside researchers from IBM and Google pondering similar issues. Francesca Rossi, a researcher at IBM, gave the example of a machine providing assistance or companionship to elderly people. Such robots may still be a ways off, but ethical challenges raised by AI are already here. Companies are also taking individual action to build safeguards around their technology.
Data Analyst, the most in-demand job of the coming years - Morning Future According to the forecasts of the World Economic Forum, by 2020 data analysts will be in high demand in companies around the world. The LinkedIn Workforce Report maintains that, in the USA, demand for these professional figures has grown sixfold compared to five years ago, and data analysts will continue to be the most sought after profiles over the next five years. This is further confirmed by IBM, which claims that the annual demand for data scientists, data developers and data engineers will lead to 700,000 new recruitments by 2020. According to an analysis conducted on a sample of 550 Italian small and medium-sized businesses by the Tag Innovation School (which has set up a Master in Business Data Analysis), 50% of SMEs state that they intend to hire a data analyst in the next three years. And the earnings are not to be sneezed at. The reason for all this is quite simple. But don’t think of it as the exclusive domain of IT giants or digital start-ups. But what do data analysts do?
Human Enhancement Human enhancement is at least as old as human civilization. People have been trying to enhance their physical and mental capabilities for thousands of years, sometimes successfully – and sometimes with inconclusive, comic and even tragic results. Up to this point in history, however, most biomedical interventions, whether successful or not, have attempted to restore something perceived to be deficient, such as vision, hearing or mobility. Even when these interventions have tried to improve on nature – say with anabolic steroids to stimulate muscle growth or drugs such as Ritalin to sharpen focus – the results have tended to be relatively modest and incremental. But thanks to recent scientific developments in areas such as biotechnology, information technology and nanotechnology, humanity may be on the cusp of an enhancement revolution. Both advocates for and opponents of human enhancement spin a number of possible scenarios. — Nicholas Agar, Victoria University Brugger of St.
15 Stunning Data Visualizations (And What You Can Learn From Them) | Visual Learning Center by Visme We’re literally drowning in data. Everyday, 2.5 quintillion bytes of data are created. This is the equivalent of 90% of the world’s information--created in the last two years alone. Now this is what we call “big data.” But where does it come from? Everywhere, from sensors and social media sites to digital images and videos. This is where data visualization comes into the picture. In the hopes of inspiring your own work, we’ve compiled 15 data visualizations that will not only blow your mind, they will also give you a clearer understanding of what makes a good visualization--and what makes a bad one. 1 It is interactive 2 It reveals trends The Year in News is a good example of how an expertly executed data visualization can reveal patterns and trends hiding beneath the surface of mountains of data. 3 It uses animation Ready? 4 It uses real images With so many data visualizations out there nowadays, it can be hard to find a unique angle that hasn’t been explored already. 5 It uses metaphors
How to bring better ethics to data science. iStock In the waning months of the Bloomberg administration, I worked for a time in a New York City Hall data group within the Health and Human Services division. One day, we were given a huge dataset on homeless families, which included various characteristics such as the number and age of children and parents, previous ZIP code, the number and lengths of previous stays in homeless services, and race. The data went back 30 years. The goal of the project was to pair homeless families with the most appropriate services, and the first step was to build an algorithm that would predict how long a family would stay in the system given the characteristics we knew when they entered. So one of the first questions we asked was, which characteristics should we use? Specifically, what about race? Most people building algorithms (except those in politics) stay away from race for similar reasons. A final obstacle to bringing up ethics in the context of data science is the training.
Can big data save these children? Humming away in a brick building near the banks of Pittsburgh’s Monongahela River, two servers filled with personal data hold the potential to improve the lives of the state’s most vulnerable children. Harnessing what’s on these servers would represent an ambitious use of big data, one that could possibly safeguard thousands of kids from abuse and neglect and transform a foster care system in need of help. But tapping into that data could come at a cost. On March 9, 1994, police found a toddler in a hotel bed in suburban Pittsburgh. She had been dead for more than 24 hours. The 2-year-old, Shawntee Ford, had 52 injuries, including a bruise so deep and massive that a pathologist could only compare it to injuries suffered by fatal car crash victims. Her father, Maurice Booker Sr., had beaten his daughter to death because she cried, the Pittsburgh Post-Gazette later reported. The child’s death had cascading effects on Allegheny County’s child protective services department. Not a done deal
Fake News Is Unbelievably Cheap to Produce - MIT Technology Review Judging by the state of Facebook feeds everywhere, fake news is now a very real problem—and one that appears to have equally real consequences by shaping political and social situations. Now, a new report puts some numbers to the costs of running a fake-news campaign, revealing that a key part of the problem may be that doing so is incredibly affordable. There are some obvious steps required in launching a fake-news assault. First, you need some fake news—it needn’t be based on fact, but it better have a compelling headline or take the form of an easy-to-digest video, and it ought appeal to the existing biases and ideologies of potential viewers. Then, you need to push it out via social networks, using bots or real humans that you’ve coerced into doing your bidding. Finally, you’ll need likes and shares (again performed by either bots or real people) to ensure that the content saturates the feeds of your targets—and, with any luck, warps their perception of reality.
Data scientist jobs: Where does the big data talent gap lie? | IT PRO Data science is one area of the digital sector that is desperately short of talent. In fact, IBM thinks data science will account for 28% of all digital jobs by 2020, but worryingly, the same report revealed that on average, each of these places remains unfilled for up to 45 days due to a lack of talent equipped with the necessary skills. Advertisement - Article continues below "Machine learning, big data and data science skills are the most challenging to recruit for, and can potentially create the greatest disruption if not filled," according to IBM's The Quant Crunch report. The Royal Society found that demand for workers with specialist data skills in the UK has more than tripled over the last five years to 231%, comparable to a general increase of regular workers of 36%. And with the European Commission forecasting that 100,000 new data-related jobs will be created in the region by 2020, the fact there aren't enough people with the right skills to fill the role is certainly worrying.
Smartphones Are Weapons of Mass Manipulation, and This Guy Is Declaring War on Them If, like an ever-growing majority of people in the U.S., you own a smartphone, you might have the sense that apps in the age of the pocket-sized computer are designed to keep your attention as long as possible. You might not have the sense that they’re manipulating you one tap, swipe, or notification at a time. But Tristan Harris thinks that’s just what’s happening to the billions of us who use social networks like Facebook, Instagram, Snapchat, and Twitter, and he’s on a mission to steer us toward potential solutions—or at least to get us to acknowledge that this manipulation is, in fact, going on. Harris, formerly a product manager turned design ethicist at Google, runs a nonprofit called Time Well Spent, which focuses on the addictive nature of technology and how apps could be better designed; it pursues public advocacy and supports design standards that take into account what’s good for people’s lives, rather than just seeking to maximize screen time.
The Good, The Bad and The Robot: Experts Are Trying to Make Machines Be "Moral" | California Magazine Good vs. bad. Right vs. wrong. Human beings begin to learn the difference before we learn to speak—and thankfully so. We owe much of our success as a species to our capacity for moral reasoning. It’s the glue that holds human social groups together, the key to our fraught but effective ability to cooperate. We are (most believe) the lone moral agents on planet Earth—but this may not last. Robots are coming, that much is sure. “As machines get smarter and smarter, it becomes more important that their goals, what they are trying to achieve with their decisions, are closely aligned with human values,” says UC Berkeley computer science professor Stuart Russell, co-author of the standard textbook on artificial intelligence. But how, exactly, does one impart morals to a robot? He believes that the survival of our species may depend on instilling values in AI, but doing so could also ensure harmonious robo-relations in more prosaic settings. Stuart Russell sees another weakness.
The Future of Politics Is Bots Drowning Out Humans What is a robot, really? The question is more complicated than it seems. These efforts will only get more sophisticated. Chatbots have been skewing social-media discussions for years. Over the years, algorithmic bots have evolved to have personas. Combine these two trends and you have the recipe for nonhuman chatter to overwhelm actual political speech. Soon, AI-driven personas will be able to write personalized letters to newspapers and elected officials, submit individual comments to public rule-making processes, and intelligently debate political issues on social media. What is a robot, really? These efforts will only get more sophisticated. Chatbots have been skewing social-media discussions for years. Over the years, algorithmic bots have evolved to have personas. Combine these two trends and you have the recipe for nonhuman chatter to overwhelm actual political speech.
How Big Data Helps Avoid Cybersecurity Threats Cybercrime instances seem to be breeding like rabbits. According to security software maker Malwarebytes, its users reported 1 billion malware-based incidents from June to November 2016. That was two years ago. Just picture this figure in 2018. Big Data: a savior? Some say Big Data is a threat; others declare it a savior. The security-related information available from Big Data reduces the time required to detect and resolve an issue, allowing cyber analysts to predict and avoid the possibilities of intrusion and invasion. According to a CSO Online report, 84% of business use Big Data to help block these attacks. Insights from Big Data analytics tools can be used to detect cybersecurity threats, including malware/ransomware attacks, compromised and weak devices, and malicious insider programs. However, is it really possible to stay protected on an everyday basis? Intelligent risk management Threat visualization Predictive models Stay secure and ahead of hackers with penetration testing