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"Google a donc annoncé vendredi dernier BERT, une nouvelle avancée de son algorithme visant à mieux comprendre le langage naturel. Voici quelques informations complémentaires sur ce projet, afin d'éviter tout malentendu et mauvaise compréhension et interprétation du « phénomène »..."

un panorama sur le travail des invisibles, nouveau prolétariat des plateformes.Et en particulier le travail derrière l'IA. Faut il adapter le droit du travail à ces nouvelles pratiques, comme créer un nouveau statut pour ce type d'emploi et/ou introduire de la négociation collective, du dialogue social dans ces plateformes (Facebook Google Amazon)

"Some companies and scientists present Affective Computing, the algorithmic analysis of personality traits also known as "artificial emotional intelligence", as an important new development. But the methods that are used are often dubious and present serious risks for discrimination. It was announced with some fanfare that Alexa and others would soon demonstrate breakthroughs in the field of emotion analysis. Much is written about affective computing, but products are far from market ready. For example, Amazon's emotion assistant Dylan is said to be able to read human emotions just by listening to their voices. However, Dylan currently only exists in form of a patent. So far, Amazon, Google et al. have not launched such products. Identifying unique signals that indicate that someone is sad seems to be a bit more complicated than they initially thought. Maybe someone's voice sounds depressed because they are depressed, but maybe they are just tired or exhausted. However, these difficulties do not prevent other companies from launching products that claim to have solved these complex problems by using voice and speech for character and personality analysis." > One is the company Precire, based in Aachen, a city on border with Belgium. Their idea: you record a voice sample, and based on the person's choice of words, sentence structure and many other indicators, the software then produces an analysis of their character traits. The software can be used in staff recruitment or to identify candidates for promotion. > critique de la méthode : biais, discrimination...

"Julie est micro travailleuse et elle a entraîné Cortana, l'assistant vocal de Microsoft. Nassim lui, était livreur pour Deliveroo et son temps de travail était décidé par un algorithme. Deux histoires de micro travailleurs précaires qui posent d'importants problèmes éthiques."

"Unless there is a strong enough economic argument, don't expect big companies to rush into producing Welsh, Gaelic or Cornish speech systems. Even tech giant Samsung hasn't yet managed to produce a UK-English speaking version of their Bixby assistant (international English speakers need to speak to it in fake American accents to get it to work). " "Research on brain-like learning algorithms may just hold the key here. This is technology that can continually learn during use, just like humans learn to speak a new language. It is unlike most current AI systems that are trained in the lab, before being let loose in the wild - apart from a few exceptions some, like Microsoft's Tay, notable for their spectacular failures. Future systems will be able to gradually acquire skills in a second language just by having users gradually introduce more and more of that language in their daily interactions. Rather than funding research into Welsh speech AI, the Welsh government may well do better by backing research into this new kind of adaptive learning technology."

Every answer from a conversational agent is a sign that algorithms are becoming a tool of soft power, a method for inculcating particular cultural values. While conversational AI agents can reiterate stereotypes and clichés about how emotions should be treated, mood-management apps go a step further - making sure we internalise those clichés and steer ourselves upon them. The upbringing of conversational agents invariably turns into the upbringing of users. It's impossible to predict what AI might do to our feelings. Interacting with and via machines has already changed the way that humans relate to one another.

De quoi s'agit-il ? De constituer la plus riche base possible d'échantillons sonores qui seront mis à la disposition des développeurs sous une licence libre (licence CC0). Le projet global s'appelle Deep Speech et Mozilla fait travailler des ingénieurs à traiter les données collectées avec des algorithmes, et ainsi alimenter un dispositif d'apprentissage machine.

"We need some new breakthroughs that fundamentally change the rotten trade-off we now make between privacy and AI. The good news is that there's a growing research effort in what's called "privacy-preserving" machine learning. Academics are trying to develop algorithms that can operate on encrypted data, which means they wouldn't need to access anyone's data directly. Other researchers are figuring out ways to combine insights from different machine-­learning models without needing to merge all their underlying data. Companies like Apple, ­Google, and Microsoft already have teams working on such projects."

"[...] neuroscientists from Columbia University recently made a major advancement toward this futuristic goal, successfully translating brain waves into intelligible speech for the first time." "Rather than directly tracking thoughts to produce speech, the researchers recorded neurological patterns generated by test subjects listening to others speak. These brain waves were fed into a vocoder-an artificial intelligence algorithm that synthesizes speech-and then converted into comprehensible, albeit robotic-sounding, speech mirroring the phrases heard by participants." article scientifique : https://www.nature.com/articles/s41598-018-37359-z

"Demain, lorsque vous arriverez de bon matin dans la salle de bain, votre assistant vocal comprendra immédiatement que vous êtes particulièrement fatigué grâce à une caméra dissimulée dans le miroir et un algorithme qui analysera votre expression. Alors, il adoucira le ton de sa voix et ne vous proposera pas forcément de lancer la radio comme d'habitude. Ce type de scénario est actuellement testé par Orange à Rennes via une plate-forme de recherche baptisée Home'in."

Maud Funaro, Directrice de la Stratégie et de l'Innovation Groupe E. Leclerc : « Pour prendre un exemple dans l'alimentaire, si vous désirez commander un yaourt aux fraises à travers une interface visuelle, vous devez suivre les étapes 'rayons', puis 'frais', puis 'crèmerie', puis 'yaourt', et enfin 'fruits' ! Avec une interface vocale, il suffit de dire : 'Je veux un yaourt aux fraises'. » "La création de ce nouveau service vocal est guidée par trois principes : primo, s'appuyer sur l'historique d'achats du client s'il existe. « Si vous commandez toujours des yaourts à la fraise de Danone par quatre, l'IA ajoutera ceux-là. » Secundo, si le client n'a pas d'historique et qu'il faut chercher dans le catalogue de produits, « nous avons conçu un algorithme de modélisation des préférences pour parvenir à converger vers les bonnes références rapidement ». Tertio, si la liste finale est trop longue à prononcer, il est possible de finir le parcours sur une interface visuelle."

> https://erlendprendergast.com/CounterBug "Glasgow School of Art graduate Erlend Prendergast has designed a modular robotic device that talks back to Amazon's virtual assistant Alexa in order to protect users from digital surveillance." "Speaking to Dezeen at the Glasgow School of Art degree show, Prendergast described his proposal as "an alternative approach to digital self defence" that is intentionally "satirical and tongue-in-cheek". "There is an inherent irony at the core of the project," he added, "because really the only way to defend yourself against Alexa is to not buy an Alexa."" "Murmur attempts to confuse Amazon's algorithms for tailored advertising by whispering contradictory phrases when the user mentions something that could indicate a preference, taste or hobby."

"The Internet has overturned how people shop and reshaped the retail industry. Voice assistants are about to unleash another revolution. As people increasingly shop via the likes of Alexa and Siri, they will tend to demand generic products, starting with everyday items such as batteries and eventually including more complex purchases such as electronics. Digital assistants will use algorithms to compare product specifications, make suggestions, and do comparisons, so that customers can find "the longest-lasting battery pack" or "the cheapest bag of flour." If digital assistants with trustworthy recommendations become a significant source of sales - and we think they will - they could chip away at all but the strongest product brands. Competition will become even more brutal as consumers switch between only one or two verbally suggested options offered by digital assistants - one being their own private label or another low-cost product. Companies that have negotiated with retailers for shelf space up to now will have to find ways to convince the digital assistants to put their products at the top of verbal searches."