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"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...

page 15 "[...], we are also seeing personal assistants, like Alexa and Siri, seeking to pick up on the emotional undertones of human speech, with companies even going so far as to patent methods of marketing based on detecting emotions, as well as mental and physical health. The AI-enabled emotion measurement company Affectiva now promises it can promote safer driving by monitoring "driver and occupant emotions, cognitive states, and reactions to the driving experience...from face and voice." Yet there is little evidence that any of these systems actually work across different individuals, contexts, and cultures, or have any safeguards put in place to mitigate concerns about privacy, bias, or discrimination in their operation. Furthermore, as we have seen in the large literature on bias and fairness, classifications of this nature not only have direct impacts on human lives, but also serve as data to train and influence other AI systems. This raises the stakes for any use of affect recognition, further emphasizing why it should be critically examined and its use severely restricted."

Les propositions de Laurence Devillers : 11 commandements à appliquer à la conception des assistants intelligents, sociaux, de compagnie... "Les systèmes actuels sont [...] encore très loin de savoir converser et de pouvoir détecter les émotions complexes de la vie de tous les jours. Ils possèdent des facultés de compréhension très pauvres et n'ont aucun sens commun. Malgré cela, l'humain projette sur ces objets des capacités humaines et les anthropomorphise. [...] Engager l'utilisateur dans une interaction avec un robot doté de capacités affectives, faire qu'il prenne du plaisir à interagir avec lui, faire qu'il ait confiance en lui, sont des buts de la robotique de compagnie. Mais si les systèmes singent les comportements des humains, encore faut-il prendre en compte les risques de confusion pour une grande partie du public." 1 - Donnés privées : « Tu ne divulgueras pas mes données à n'importe qui. » 2 - Droit à l'oubli : « Tu oublieras tout ce que je te demande d'oublier. » 3 - Sécurité : « Tu pourras te déconnecter d'Internet si je te le demande. » 4 - Contrôle : « Tu seras régulièrement contrôlé pour évaluer ce que tu as appris. » 5 - Explicabilité et traçabilité : « Tu pourras m'expliquer tes comportements si je te le demande. » 6 - Loyauté : « Tu seras loyal. » 7- Consentement : « Tu seras empathique et simulera des émotions, seulement si je le sais ! » 8 - Risque de dépendance : « Tu stimuleras ma mémoire et veilleras à ce que je ne devienne pas trop dépendant de toi ! » 9 - Risque de confusion : « Tu feras attention à ce que je ne te confonde pas avec un être humain ! » 10 - Adaptation aux règles sociales « Tu apprendras à vivre avec des humains et tu t'adapteras aux règles sociales. » 11 - Utilité et bienveillance : « Tu seras bienveillant et utile. Et pourquoi pas, doué d'un peu d'humour ! »

The Amazon Echo as an anatomical map of human labor, data and planetary resources - By Kate Crawford and Vladan Joler (2018) [...] "At this moment in the 21st century, we see a new form of extractivism that is well underway: one that reaches into the furthest corners of the biosphere and the deepest layers of human cognitive and affective being. Many of the assumptions about human life made by machine learning systems are narrow, normative and laden with error. Yet they are inscribing and building those assumptions into a new world, and will increasingly play a role in how opportunities, wealth, and knowledge are distributed. The stack that is required to interact with an Amazon Echo goes well beyond the multi-layered 'technical stack' of data modeling, hardware, servers and networks. The full stack reaches much further into capital, labor and nature, and demands an enormous amount of each. The true costs of these systems - social, environmental, economic, and political - remain hidden and may stay that way for some time. We offer up this map and essay as a way to begin seeing across a wider range of system extractions. The scale required to build artificial intelligence systems is too complex, too obscured by intellectual property law, and too mired in logistical complexity to fully comprehend in the moment. Yet you draw on it every time you issue a simple voice command to a small cylinder in your living room: 'Alexa, what time is it?" And so the cycle continues."

Personnaliser les services, et le bot en fonction de l'humeur et la personnalité de la personne. L'affective computing ou social computing continue d'intéresser les industriels. Orange s'y intéresse et s'interroge aussi sur le degré d'acceptabilité des usagers. Jusqu'où aller dans la personnalisation de services et d'interaction avec les machines?

inventaire des capacités émotionnelles de l'IA