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"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."

"The algorithmic manager seems to watch everything you do. Ride-hailing platforms track a variety of personalized statistics, including ride acceptance rates, cancellation rates, hours spent logged in to the app and trips completed. And they display selected statistics to individual drivers as motivating tools, like "You're in the top 10 percent of partners!" Uber uses the accelerometer in drivers' phones along with GPS and gyroscope to give them safe driving reports, tracking their performance in granular detail. One driver posted to a forum that a grade of 210 out of 247 "smooth accelerations" earned a "Great work!" from the boss."

""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.""

"Depending on how legal decisions shake out, AI systems could become a valuable tool to assist creativity, a nuisance ripping off hard-working human musicians, or both."

"self-awareness: Columbia engineers created a robot that could figure out what it looked like without any external input. In essence, it could imagine itself"

"The Wealth of Nations, by Adam Smith, should be a required reading for every head of state. What took 17 years to be written and transformed the whole world, takes only a few days to read it. Right in the first page Smith asserts that the wealth of "every nation… [is] regulated by two different circumstances; first by the skill, dexterity, and judgment with which its labour is generally applied; and, secondly, by the proportion between the number of those who are employed in useful labour,""

"Then came the algorithm, which used automatic speech recognition to detect specific features and patterns in each of the 48 recordings. It was clear from examining the waveforms of the cries that each category had a specific pattern."

"Scientists have taken a step forward in their ability to decode what a person is saying just by looking at their brainwaves when they speak."

"According to Folding@Home, the organisation that runs the distributed computing effort, the combined power of the network broke 1,000,000,000,000,000,000 operations per second - or one "exaflop" - on 25 March."

"When the field of AI believes it is neutral, it both fails to notice biased data and builds systems that sanctify the status quo and advance the interests of the powerful. What is needed is a field that exposes and critiques systems that concentrate power, while co-creating new systems with impacted communities: AI by and for the people."

"GPT-3 medical chatbot tells suicidal test patient to kill themselves"

"In 2015, a research group fed an AI system called Deep Patient health and medical data from some 700,000 people, and tested whether it could predict diseases. It could, but Deep Patient provides no explanation for the basis of a diagnosis, and the researchers have no idea how it comes to its conclusions. A doctor either can either trust or ignore the computer, but that trust will remain blind."

"Over the Bridge hopes the project emphasizes exactly how much work goes into creating AI music. "There's an inordinate amount of human hands at the beginning, middle and end to create something like this," explained Michael Scriven, a rep for Lemmon Entertainment whose CEO is on Over the Bridge's board of directors. Scriven added, "A lot of people may think [AI] is going to replace musicians at some point, but at this point, the number of humans that are required just to get to a point where a song is listenable is actually quite significant.""

"Researchers fed these algorithms (which function like autocomplete, but for images) pictures of a man cropped below his neck: 43% of the time the image was autocompleted with the man wearing a suit. When you fed the same algorithm a similarly cropped photo of a woman, it auto-completed her wearing a low-cut top or bikini a massive 53% of the time. For some reason, the researchers gave the algorithm a picture of the Democratic congresswoman Alexandria Ocasio-Cortez and found that it also automatically generated an image of her in a bikini. (After ethical concerns were raised on Twitter, the researchers had the computer-generated image of AOC in a swimsuit removed from the research paper.)"

"Assigning female genders to digital assistants such as Apple's Siri and Amazon's Alexa is helping entrench harmful gender biases, according to a UN agency."

"Microsoft's decision to replace human journalists with robots has backfired, after the tech company's artificial intelligence software illustrated a news story about racism with a photo of the wrong mixed-race member of the band Little Mix."

"The streaming video company's recommendation algorithm can sometimes send you on an hours-long video binge so captivating that you never notice the time passing. But according to a study from software nonprofit Mozilla Foundation, trusting the algorithm means you're actually more likely to see videos featuring sexualized content and false claims than personalized interests."

"No surprise, then, that Twitter is aglow with engineers and academics mocking Lemoine for falling into the seductive emptiness of his own creation. But while I agree that Lemoine has made a mistake, I don't think he deserves our scorn. His error is a good mistake, the kind of mistake we should want AI scientists to make."

"That is why we must demand transparency here, especially in the case of technology that uses human-like interfaces such as language. For any automated system, we need to know what it was trained to do, what training data was used, who chose that data and for what purpose. In the words of AI researchers Timnit Gebru and Margaret Mitchell, mimicking human behaviour is a "bright line" - a clear boundary not to be crossed - in computer software development. We treat interactions with things we perceive as human or human-like differently. With systems such as LaMDA we see their potential perils and the urgent need to design systems in ways that don't abuse our empathy or trust."