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The New York Times -“This village in West Sumatra, a lush province of volcanoes and hilly rain forests, had a problem with illegal loggers. They were stealing valuable hardwood with impunity. At first, a group of local people put a fence across the main road leading into the forest, but it was flimsy and proved …
Berkman Kein Center – “Government institutions around the globe are beginning to explore decision automation in a variety of contexts, from determining eligibility for services; to evaluating where to deploy health inspectors and law enforcement personnel; to defining boundaries around voting districts. Use cases for technologies that incorporate AI or machine learning will expand as …
Legal Executive Institute – “…What makes the Dark Web “dark,” are not the nefarious things that sometimes occur there; rather, it is the anonymity it offers. Most search engines keep a very close eye on who you are and what you are searching for. Plenty of ad trackers also want to eavesdrop on your Web …
The New York Times Opinion: “Algorithms make many important decisions for us, like our creditworthiness, best romantic prospects and whether we are qualified for a job. Employers are increasingly using them during the hiring process out of the belief they’re both more convenient and less biased than humans. However, as I describe in a new …
The New Yorker – [“At the end of every section in this article, you can read the text that an artificial intelligence predicted would come next.”] “…But Smart Compose goes well beyond spell-checking. It isn’t correcting words I’ve already formed in my head; it’s coming up with them for me, by harnessing the predictive power …
Smithsonian.com – A machine learning algorithm helped decode the squeaks Egyptian fruit bats make in their roost, revealing that they “speak” to one another as individuals: “Plenty of animals communicate with one another, at least in a general way—wolves howl to each other, birds sing and dance to attract mates and big cats mark their …
López de Prado, Marcos, Ten Applications of Financial Machine Learning (September 22, 2019). Available at SSRN: https://ssrn.com/abstract=3365271 or http://dx.doi.org/10.2139/ssrn.3365271 “This article reviews ten notable financial applications where ML has moved beyond hype and proven its usefulness. This success does not mean that the use of ML in finance does not face important challenges. The main …
Oseid, Julie A. and Vorenberg, Amy and Koenig, Melissa Love, Ok, Google, Will Artificial Intelligence Replace Human Lawyering? (2019). 102 Marquette Law Review 1269 (2019); U of St. Thomas (Minnesota) Legal Studies Research Paper No. 19-13; Marquette Law School Legal Studies Paper No. 19-13. Available at SSRN: https://ssrn.com/abstract=3449500 – “Will Artificial Intelligence (AI) replace human lawyering? …
Quartz – “Some corporations have always cared how their employees feel—if only because happier workers are more productive than those who are miserable. Others have only recently begun to wake up to the fact that they need to address wellbeing in meaningful ways. This focus raises a question: How can a company tell whether the …
Google Blog: “…So-called “deepfakes“—produced by deep generative models that can manipulate video and audio clips—are one of these. Since their first appearance in late 2017, many open-source deepfake generation methods have emerged, leading to a growing number of synthesized media clips. While many are likely intended to be humorous, others could be harmful to individuals …
thenextweb: “Don’t you absolutely hate how dense and confusing privacy policies are? Considering they’re full of gotchas and intentionally obscure legalese, it’s no surprise that hardly anyone bothers to even read them — we’ve simply accepted we’re giving up our data, and with it, our sense of privacy. But thanks to this new policy-reading AI, things …
“Machine vision tools like facial recognition are increasingly being used for law enforcement, advertising, and other purposes. Pew Research Center itself recently used a machine vision system to measure the prevalence of men and women in online image search results. This kind of system develops its own rules for identifying men and women after seeing …
