Group items tagged

"Going from small data analytics to Big Data analytics or to predictive and prescriptive analytics is trickier. Expanding in both dimensions is human capital intensive, requiring talented data scientists. A McKinsey report (2011) estimates that by 2018, there will be a shortage of 140,000 to 190,000 workers with "deep analytical" experience and a further 1.5 million data-literate managers in the US. Technology giants such as Google, Facebook and Amazon, and large investment banks and top hedge funds can afford such employees, however even now the competition is fierce, as is evidenced by the ongoing talent war in Silicon Valley. The data scientist is indeed a sexy job in the 21st century."

"Unlike other companies, Zebra's algorithms provide an actual diagnosis, completely automatically using only imaging data. This is a very new field - older technology was always driven by the radiologist, and never automatic. The algorithms are part of the Zebra Analytics Platform - a cloud based analytics engine that receives medical imaging studies, analyzes them and returns results to participating hospitals and physicians."

"Can AI and analytics be used in a way that improves operational efficiency without jeopardizing our ethical principles? The answer is "yes" - if moral objectives and constraints, now often treated as an afterthought, are considered from the outset when designing models. We will discuss a recent attempt to combine ethics, analytics, and operational efficiency in the world of organ allocation and examine the lessons it holds for other areas of health care and beyond."

"The reason is that routine big-data analytical techniques can now effectively manufacture personal data that is not protected by any of the measures we've used up to now. A well-known illustration of this is the way Target, an American retail chain, creatively collated scattered pieces of data about individuals' changes in shopping habits to predict the delivery date of pregnant shoppers - so that they could then be targeted with relevant advertisements."

"The store will also utilise data and video analytics to analyse purchasing behaviour and customise its inventory. An auto-ordering system eliminates the need to manually track and order stocks."

"The app then measures 14 health parameters (Glucose, Protein, Urobilinogen, Calcium, Blood, Creatinine, pH, Ketone, Bilirubin, Specific Gravity, Nitrites, Leucocyte, Ascorbic Acid, Microalbumin) using routine urine analysis, provides day-to-day analytics, and, importantly, enables regular monitoring for early warning markers for more than 25 medical conditions, including complications of diabetes, pregnancy, kidney disease, and urinary tract infections. The whole idea is to spot risks early, and to address big problems before they become too big. This is important both for the home user, as well for the beneficiary of the low-cost clinic in the developing world. "

"Twitter claims a 90 percent accuracy rate for the clever techniques it uses to learn the gender of any given user. Glenn Fleishman reports on a the company's disconcerting new analytics tools, the research behind them, and how large a pinch of salt they come with."

"Selling data is as yet a small part of Twitter's overall income - $70m out of a total of $1.3bn last year, with the lion's share of cash coming from advertising, but the social network has big plans to increase that. Its acquisition of Chris Moody's analytics company Gnip for $130m last April is a sign of that intent. Google and Facebook have built their businesses around sharing data, but their control of our private and public information has become a source of huge controversy. "

"Amid mounting financial pressure, at least a dozen police forces are using or considering predictive analytics, despite warnings from campaigners that use of algorithms and "predictive policing" models risks locking discrimination into the criminal justice system."

"Scientists must embrace circumspection, transparency, and robust ways of working that safeguard against bias and analytical flexibility. Doing so will provide parents and policymakers with the reliable insights they need on a topic most often characterized by unfounded media hype."

"SINGAPORE - In the not too distant future, surveillance cameras sitting atop over 100,000 lampposts in Singapore could help authorities pick out and recognise faces in crowds across the island-state. The plan to install the cameras, which will be linked to facial recognition software, is raising privacy fears among security experts and rights groups. The government said the system would allow it to "perform crowd analytics" and support anti-terror operations."

""Employers are increasingly exploiting metadata logged by software and devices for performance analytics and algorithmic control," Christl added. "MS is providing the tools for it. Practices we know from software development (and factories and call centres) are expanded to all white-collar work.""

"POLICE IN CHINA'S Liaoning province were sitting on mounds of data collected through invasive means: financial records, travel information, vehicle registrations, social media, and surveillance camera footage. To make sense of it all, they needed sophisticated analytic software. Enter American business computing giant Oracle, whose products could find relevant data in the police department's disparate feeds and merge it with information from ongoing investigations."

"While it's still a popular choice to allege that technology is putting human beings out of work, a study by Deloitte based on 140 years of data seems to prove otherwise. Automation, robotics and the simple fact that IT is faster, better connected and capable of massive amounts of analytics and storage means technology has often been held responsible for replacing the roles of people, but census data stretching back to 1871 begs to differ."

"If you've been job hunting recently, chances are you've interacted with a resume robot, a nickname for an Applicant Tracking System, or ATS. In its most basic form, an ATS acts like an online assistant, helping hiring managers write job descriptions, scan resumes and schedule interviews. As artificial intelligence advances, employers are increasingly relying on a combination of predictive analytics, machine learning and complex algorithms to sort through candidates, evaluate their skills and estimate their performance. Today, it's not uncommon for applicants to be rejected by a robot before they're connected with an actual human in human resources. The job market is ripe for the explosion of AI recruitment tools. Hiring managers are coping with deflated HR budgets while confronting growing pools of applicants, a result of both the economic downturn and the post-pandemic expansion of remote work. As automated software makes pivotal decisions about our employment, usually without any oversight, it's posing fundamental questions about privacy, accountability and transparency."

" The machine's doing the prediction, making the distinct role of judgment in decision making clearer. So as the value of human prediction falls, the value of human judgment goes up because AI doesn't do judgment-it can only make predictions and then hand them off to a human to use his or her judgment to determine what to do with those predictions."

"My entry point into this story began, as so many things do, with a late-night Google. Last December, I took an unsettling tumble into a wormhole of Google autocomplete suggestions that ended with "did the holocaust happen". And an entire page of results that claimed it didn't."

"This tool predicts your psycho-demographic profile from digital footprints of your behaviour. It reveals how you might be perceived by others online and provides detailed insights on your personality, intelligence, life satisfaction and more." YIKES