Group items tagged

Tenant-screening systems like SafeRent are often used in place of humans as a way to 'avoid engaging' directly with the applicants and pass the blame for a denial to a computer system, said Todd Kaplan, one of the attorneys representing Louis and the class of plaintiffs who sued the company. The property management company told Louis the software alone decided to reject her, but the SafeRent report indicated it was the management company that set the threshold for how high someone needed to score to have their application accepted. Louis and the other named plaintiff alleged SafeRent's algorithm disproportionately scored Black and Hispanic renters who use housing vouchers lower than white applicants. SafeRent has settled. In addition to making a $2.3m payment, the company has agreed to stop using a scoring system or make any kind of recommendation when it comes to prospective tenants who used housing vouchers for five years.

"The performance of LipNet compares incredibly favorably to human lipreading experts on GRID corpus, the largest publicly-available sentence-level lipreading dataset. In fact, where human experts got just 52 percent, LipNet scored 93 percent. Its sentence-based approach to lip-reading also smashed the best previous attempt by a machine, which managed 79.6 percent accuracy on the same dataset."

"Automated decision-making is appealing to businesses as it can save time and eliminate human emotional volatility. "People have a bad day and it then colors their perception of the world and they make different decisions. In a hedge fund that's a big deal," he added."

"A robot that can decide whether or not to inflict pain has been built by roboticist and artist Alexander Reben from the University of Berkeley, California. The basic machine is capable of pricking a finger but is programmed not to do so every time it can."

""AI can pick up missed cues and suggest nudges to bridge the gap in emotional intelligence and communication styles. It can identify optimal ways to discuss common problems and alleviate common misunderstandings based on these different priorities and ways of viewing the world. We could be looking at a different gender dynamics in a decade.""

"The system used historical data, including arrest records and electronic police reports, to forecast crime and help shape public safety strategies, according to company and city government materials. At no point did those materials suggest any effort to clean or amend the data to address the violations revealed by the DOJ. In all likelihood, the corrupted data was fed directly into the system, reinforcing the department's discriminatory practices."

"The report cited a recent academic analysis of studies on how people interpret moods from facial expressions. That paper found that the previous scholarship showed such perceptions are unreliable for multiple reasons."

"The tech giant is partnering with OpenAI to integrate its chatbot, ChatGPT, into the iPhone's operating system, Bloomberg reported. Apple is expected to announce the deal at its annual Worldwide Developers Conference which starts on June 10."

"Train the Deep Learning Ahem Detector with two sets of audio files, "a negative sample with clean voice/sound" (minimum 3 minutes) and "a positive one with 'ahem' sounds concatenated" (minimum 10s) and it will detect "ahems" in any voice sample thereafter."

"The school will teach cyber skills to some of the UK's most gifted 16- to 19-year-olds. It will select on talent alone, looking in particular for exceptional problem solvers and logic fiends, regardless of wealth or family background, according to Alastair MacWillson, a driving force behind the initiative. "The cyber threat is the real threat facing the UK, and the problem it's causing the UK government and companies is growing exponentially," said MacWillson, chair of Qufaro, a not-for-profit organisation created by a consortium of cybersecurity experts for the purposes of education."

"As the miles grow, the odds shrink. At some point, a car driving autonomously or semi-autonomously will cause a fatal accident. If their performance is remotely comparable to a human's, that moment could come within the next 18-24 months. If so, by the law of averages it will probably involve a Tesla Model 3. Self-driving cars may be about to have their Driscoll moment."

"It might not sound like much, but the success of the Minwa supercomputer, which can sort a million images into a thousand predefined categories with an error rate less than the typical human, makes it the latest secret weapon of the company known as "China's Google", Baidu."

"Hassabis was a child chess prodigy, who learned the game aged four and was able to beat his dad three weeks later - indeed, when he started playing competitively he was so small he had to bring a pillow with him to reach the board - and became a strong player. Yet in AlphaZero's case there was no human input, other than telling it the rules of each game. "In a matter of a few hours it was superhuman," Hassabis says proudly."

"Apart from biases in the training databases, it's hard to know how well face-recognition systems actually perform in the real world, in spite of recent gains. Anil Jain, a professor of computer science at Michigan State University who has worked on face recognition for more than thirty years, told me, "Most of the testing on the private venders' products is done in a laboratory environment under controlled settings. In real practice, you're walking around in the streets of New York. It's a cold winter day, you have a scarf around your face, a cap, maybe your coat is pulled up so your chin is partially hidden, the illumination may not be the most favorable, and the camera isn't capturing a frontal view.""

"Where the researchers struck gold was by realising that a large (but not overly large pair of glasses) could act to "change the pixels" even in a real photo. By picking a pair of "geek" frames, with relatively large rims, the researchers were able to obscure about 6.5% of the pixels in any given facial picture. Printing a pattern over those frames then had the effect of manipulating the image."

" "Why isn't my face being detected? We have to look at how we give machines sight," she said in a TED Talk late last year. "Computer vision uses machine-learning techniques to do facial recognition. You create a training set with examples of faces. However, if the training sets aren't really that diverse, any face that deviates too much from the established norm will be harder to detect.""

"The results may seem similar to what you'd get if you'd searched WebMD, Mayo Clinic, etc. The difference is that Dr. A.I. pulls in many more data points than those sites do, then combines artificial intelligence with a massive database to pinpoint the most likely results in your specific case. It doesn't just find all possible ailments and list them for you to explore further on your own."

"Game players-like drivers-often have to reach conclusions without full understanding of what the other players-or drivers-are doing. So more researchers are applying game theory to train self-driving cars how to act in uncertain situations."