person:franklin foer

  • The Urgent Quest for Slower, Better News | The New Yorker
    https://www.newyorker.com/culture/annals-of-inquiry/the-urgent-quest-for-slower-better-news

    In 2008, the Columbia Journalism Review published an article with the headline “Overload!,” which examined news fatigue in “an age of too much information.” When “Overload!” was published, Blackberrys still dominated the smartphone market, push notifications hadn’t yet to come to the iPhone, retweets weren’t built into Twitter, and BuzzFeed News did not exist. Looking back, the idea of suffering from information overload in 2008 seems almost quaint. Now, more than a decade later, a fresh reckoning seems to be upon us. Last year, Tim Cook, the chief executive officer of Apple, unveiled a new iPhone feature, Screen Time, which allows users to track their phone activity. During an interview at a Fortune conference, Cook said that he was monitoring his own usage and had “slashed” the number of notifications he receives. “I think it has become clear to all of us that some of us are spending too much time on our devices,” Cook said.

    It is worth considering how news organizations have contributed to the problems Newport and Cook describe. Media outlets have been reduced to fighting over a shrinking share of our attention online; as Facebook, Google, and other tech platforms have come to monopolize our digital lives, news organizations have had to assume a subsidiary role, relying on those sites for traffic. That dependence exerts a powerful influence on which stories that are pursued, how they’re presented, and the speed and volume at which they’re turned out. In “World Without Mind: the Existential Threat of Big Tech,” published in 2017, Franklin Foer, the former editor-in-chief of The New Republic, writes about “a mad, shameless chase to gain clicks through Facebook” and “a relentless effort to game Google’s algorithms.” Newspapers and magazines have long sought to command large readerships, but these efforts used to be primarily the province of circulation departments; newsrooms were insulated from these pressures, with little sense of what readers actually read. Nowadays, at both legacy news organizations and those that were born online, audience metrics are everywhere. At the Times, everyone in the newsroom has access to an internal, custom-built analytics tool that shows how many people are reading each story, where those people are coming from, what devices they are using, how the stories are being promoted, and so on. Additional, commercially built audience tools, such as Chartbeat and Google Analytics, are also widely available. As the editor of newyorker.com, I keep a browser tab open to Parse.ly, an application that shows me, in real time, various readership numbers for the stories on our Web site.

    Even at news organizations committed to insuring that editorial values—and not commercial interests—determine coverage, it can be difficult for editors to decide how much attention should be paid to these metrics. In “Breaking News: the Remaking of Journalism and Why It Matters,” Alan Rusbridger, the former editor-in-chief of the Guardian, recounts the gradual introduction of metrics into his newspaper’s decision-making processes. The goal, he writes, is to have “a data-informed newsroom, not a data-led one.” But it’s hard to know when the former crosses over into being the latter.

    For digital-media organizations sustained by advertising, the temptations are almost irresistible. Each time a reader comes to a news site from a social-media or search platform, the visit, no matter how brief, brings in some amount of revenue. Foer calls this phenomenon “drive-by traffic.” As Facebook and Google have grown, they have pushed down advertising prices, and revenue-per-click from drive-by traffic has shrunk; even so, it continues to provide an incentive for any number of depressing modern media trends, including clickbait headlines, the proliferation of hastily written “hot takes,” and increasingly homogeneous coverage as everyone chases the same trending news stories, so as not to miss out on the traffic they will bring. Any content that is cheap to produce and has the potential to generate clicks on Facebook or Google is now a revenue-generating “audience opportunity.”

    Among Boczkowski’s areas of research is how young people interact with the news today. Most do not go online seeking the news; instead, they encounter it incidentally, on social media. They might get on their phones or computers to check for updates or messages from their friends, and, along the way, encounter a post from a news site. Few people sit down in the morning to read the print newspaper or make a point of watching the T.V. news in the evening. Instead, they are constantly “being touched, rubbed by the news,” Bockzkowski said. “It’s part of the environment.”

    A central purpose of journalism is the creation of an informed citizenry. And yet––especially in an environment of free-floating, ambient news––it’s not entirely clear what it means to be informed. In his book “The Good Citizen,” from 1998, Michael Schudson, a sociologist who now teaches at Columbia’s journalism school, argues that the ideal of the “informed citizen”––a person with the time, discipline, and expertise needed to steep him- or herself in politics and become fully engaged in our civic life––has always been an unrealistic one. The founders, he writes, expected citizens to possess relatively little political knowledge; the ideal of the informed citizen didn’t take hold until more than a century later, when Progressive-era reformers sought to rein in the party machines and empower individual voters to make thoughtful decisions. (It was also during this period that the independent press began to emerge as a commercial phenomenon, and the press corps became increasingly professionalized.)

    Schudson proposes a model for citizenship that he believes to be more true to life: the “monitorial citizen”—a person who is watchful of what’s going on in politics but isn’t always fully engaged. “The monitorial citizen engages in environmental surveillance more than information-gathering,” he writes. “Picture parents watching small children at the community pool. They are not gathering information; they are keeping an eye on the scene. They look inactive, but they are poised for action if action is required.” Schudson contends that monitorial citizens might even be “better informed than citizens of the past in that, somewhere in their heads, they have more bits of information.” When the time is right, they will deploy this information––to vote a corrupt lawmaker out of office, say, or to approve an important ballot measure.

    #Journalisme #Médias #Economie_attention

  • The Biggest Misconceptions about Artificial Intelligence
    http://knowledge.wharton.upenn.edu/article/whats-behind-the-hype-about-artificial-intelligence-separat

    Knowledge@Wharton: Interest in artificial intelligence has picked up dramatically in recent times. What is driving this hype? What are some of the biggest prevailing misconceptions about AI and how would you separate the hype from reality?

    Apoorv Saxena: There are multiple factors driving strong interest in AI recently. First is significant gains in dealing with long-standing problems in AI. These are mostly problems of image and speech understanding. For example, now computers are able to transcribe human speech better than humans. Understanding speech has been worked on for almost 20 to 30 years, and only recently have we seen significant gains in that area. The same thing is true of image understanding, and also of specific parts of human language understanding such as translation.

    Such progress has been made possible by applying an old technique called deep learning and running it on highly distributed and scalable computing infrastructure. This combined with availability of large amounts of data to train these algorithms and easy-to-use tools to build AI models, are the major factors driving interest in AI.

    It is natural for people to project the recent successes in specific domains into the future. Some are even projecting the present into domains where deep learning has not been very effective, and that creates a lot of misconception and also hype. AI is still pretty bad in how it learns new concepts and extending that learning to new contexts.

    For example, AI systems still require a tremendous amount of data to train. Humans do not need to look at 40,000 images of cats to identify a cat. A human child can look at two cats and figure out what a cat and a dog is — and to distinguish between them. So today’s AI systems are nowhere close to replicating how the human mind learns. That will be a challenge for the foreseeable future.

    Alors que tout est clean, la dernière phrase est impressionnante : « That will be a challenge for the foreseeable future ». Il ne s’agit pas de renoncer à la compréhension/création de concepts par les ordinateurs, mais de se donner le temps de le faire demain. Dans World without mind , Franklin Foer parle longuement de cette volonté des dirigeants de Google de construire un ordinateur qui serait un cerveau humain amélioré. Mais quid des émotions, des sentiments, de la relation physique au monde ?

    As I mentioned in narrow domains such as speech recognition AI is now more sophisticated than the best humans while in more general domains that require reasoning, context understanding and goal seeking, AI can’t even compete with a five-year old child. I think AI systems have still not figured out to do unsupervised learning well, or learned how to train on a very limited amount of data, or train without a lot of human intervention. That is going to be the main thing that continues to remain difficult . None of the recent research have shown a lot of progress here.

    Knowledge@Wharton: In addition to machine learning, you also referred a couple of times to deep learning. For many of our readers who are not experts in AI, could you explain how deep learning differs from machine learning? What are some of the biggest breakthroughs in deep learning?

    Saxena: Machine learning is much broader than deep learning. Machine learning is essentially a computer learning patterns from data and using the learned patterns to make predictions on new data. Deep learning is a specific machine learning technique.

    Deep learning is modeled on how human brains supposedly learn and use neural networks — a layered network of neurons to learn patterns from data and make predictions. So just as humans use different levels of conceptualization to understand a complex problem, each layer of neurons abstracts out a specific feature or concept in an hierarchical way to understand complex patterns. And the beauty of deep learning is that unlike other machine learning techniques whose prediction performance plateaus when you feed in more training data, deep learning performance continues to improve with more data. Also deep learning has been applied to solve very different sets of problems and shown good performance, which is typically not possible with other techniques. All these makes deep learning special, especially for problems where you could throw in more data and computing power easily.

    Knowledge@Wharton: The other area of AI that gets a lot of attention is natural language processing, often involving intelligent assistants, like Siri from Apple, Alexa from Amazon, or Cortana from Microsoft. How are chatbots evolving, and what is the future of the chatbot?

    Saxena: This is a huge area of investment for all of the big players, as you mentioned. This is generating a lot of interest, for two reasons. It is the most natural way for people to interact with machines, by just talking to them and the machines understanding. This has led to a fundamental shift in how computers and humans interact. Almost everybody believes this will be the next big thing.

    Still, early versions of this technology have been very disappointing. The reason is that natural language understanding or processing is extremely tough. You can’t use just one technique or deep learning model, for example, as you can for image understanding or speech understanding and solve everything. Natural language understanding inherently is different. Understanding natural language or conversation requires huge amounts of human knowledge and background knowledge. Because there’s so much context associated with language, unless you teach your agent all of the human knowledge, it falls short in understanding even basic stuff.

    De la compétition à l’heure du vectorialisme :

    Knowledge@Wharton: That sounds incredible. Now, a number of big companies are active in AI — especially Google, Microsoft, Amazon, Apple in the U.S., or in China you have Baidu, Alibaba and Tencent. What opportunities exist in AI for startups and smaller companies? How can they add value? How do you see them fitting into the broader AI ecosystem?

    Saxena: I see value for both big and small companies. A lot of the investments by the big players in this space are in building platforms where others can build AI applications. Almost every player in the AI space, including Google, has created platforms on which others can build applications. This is similar to what they did for Android or mobile platforms. Once the platform is built, others can build applications. So clearly that is where the focus is. Clearly there is a big opportunity for startups to build applications using some of the open source tools created by these big players.

    The second area where startups will continue to play is with what we call vertical domains. So a big part of the advances in AI will come through a combination of good algorithms with proprietary data. Even though the Googles of the world and other big players have some of the best engineering talent and also the algorithms, they don’t have data. So for example, a company that has proprietary health care data can build a health care AI startup and compete with the big players. The same thing is true of industries such as finance or retail.

    #Intelligence_artificielle #vectorialisme #deep_learning #Google

  • Why it’s time to panic about the power of big technology.
    http://www.slate.com/articles/technology/interrogation/2017/10/why_it_s_time_to_panic_about_the_power_of_big_technology.html

    Isaac Chotiner: We tend to think of existential threats as being things like global warming or nuclear weapons. Why should we be thinking of technology in these dire terms?

    Franklin Foer: I’m not arguing that we should think about technology per se in these dire terms. I’m arguing that we need to think about our present course with technology in those terms, because our lives are increasingly dominated by a series of big companies that have achieved something close to the state of monopoly. They have a vision for humans, and they’re trying to lead us to that vision, which they’re able to do because of their enormous economic power. What concerns me about this trajectory is that we’re giving up a lot. We’re getting a lot. There’s no doubt that we’re getting a lot. The #iPhone is an incredible invention. #Google is arguably one of the greatest inventions. The search engine is one of the greatest inventions in human history. But we’re also sacrificing enormous things. The magical qualities of these pieces of technology are things that we enjoy, but they also tend to blind us, so we don’t apply all the skepticism to these companies and to these trends that we would apply to other significant institutions in our lives.

    #GAFA

  • Entre la Silicon Valley et les Américains, le climat a changé

    http://www.lemonde.fr/pixels/article/2017/09/18/haro-sur-la-silicon-valley_5186999_4408996.html

    La puissance des géants des technologies commence à inquiéter sérieusement l’opinion américaine et la classe politique. Les appels à la réglementation se multiplient.

    Le lancement en fanfare de l’iPhone X, le 12 septembre, n’a pas pu masquer l’évidence : les nuages s’accumulent sur la Silicon Valley. Même le dernier-né des smartphones d’Apple n’a pas été accueilli avec l’enthousiasme habituel, en dépit de son bestiaire de nouveaux emojis à tête de panda, de singe ou de robot. Le prix, déjà, est de plus en plus inabordable (1 159 euros pour la version de base). Surtout, la nouvelle fonction de reconnaissance faciale se révèle être un facteur anxiogène. Apple a beau l’appeler iPhone 10, la lettre X donne à son nouveau jouet une aura de mystère et, pour employer le mot à la mode, de dystopie. « Pour la première fois, une compagnie va disposer d’un outil de reconnaissance faciale avec des millions de portraits et l’équipement pour scanner et identifier les visages partout dans le monde », s’émeut le juriste Jake Laperruque, dans le magazine Wired.

    Entre les Américains et la Silicon Valley, le climat a changé. Chaque jour apporte un cortège d’informations embarrassantes pour la « Tech ». Facebook va d’aveux en promesses de corriger les erreurs. Devant la commission d’enquête parlementaire sur les ingérences russes dans l’élection présidentielle de 2016, le réseau social a dû exposer les failles de son modèle de vente de publicités personnalisées. En pleine campagne électorale, plus de quatre cents faux comptes liés à la Russie ont pu acheter pour 100 000 dollars (83 581 euros) de publicités et diffuser quelque trois mille messages sur des sujets aussi polémiques que l’immigration, les droits des homosexuels, le racisme, le contrôle des armes à feu, influençant potentiellement le scrutin.

    La firme de Mark Zuckerberg est maintenant visée par un mandat de perquisition du procureur spécial Robert Mueller. Si l’on en croit le professeur Benjamin Edelman, d’Harvard, cité par le New York Times, ses ingénieurs s’y perdent eux-mêmes dans la complexité de leur système de collecte de publicités, à la fois automatisé et manuel. Et « la machine a son propre cerveau », ajoute-t-il.

    « Le pouvoir de Google »

    Google fait l’objet d’une nouvelle plainte pour sexisme, cette fois en nom collectif, déposée le 14 septembre par trois anciennes ingénieures s’estimant sous-payées et surtout sous-promues. Le moteur de recherche continue aussi d’être sous le feu des accusations d’avoir évincé du think tank New America, qu’il finance, un chercheur qui s’était félicité de l’amende qui lui a été imposée en juin par la Commission européenne pour abus de position dominante. « Le pouvoir de Google sur le marché est aujourd’hui l’un des défis les plus importants pour les responsables des politiques de concurrence dans le monde », écrivait le chercheur Barry Lynn, parti créer une structure indépendante avec son équipe.

    Il y a longtemps que des insiders, comme Jaron Lanier, de Microsoft Research, ont montré que les géants de la Vallée, en s’appropriant gratuitement les données des utilisateurs, contribuaient à l’appauvrissement des classes moyennes. Des années, aussi, que la Commission européenne tente d’imposer des limites à l’hégémonie des GAFA (Google, Apple, Facebook, Amazon). Mais les critiques restaient largement confidentielles. L’Europe était jugée incorrigiblement étatique, réticente aux innovations. Les sceptiques étaient relégués au rang de passéistes, d’Amish du numérique, ou mépris suprême, de luddites hostiles au progrès.

    La critique est tendance

    Aujourd’hui, les Cassandre ont pignon sur rue dans les médias. Les tribunes se succèdent sur le thème : l’âge d’or est fini pour la Silicon Valley. La Tech est rebaptisée « Big Tech », comme on disait hier « Big Oil », pour la tentaculaire industrie pétrolière. « Faut-il casser Google » ? Le moteur de recherche n’est-il pas « trop puissant ? », s’interroge Fox News, qui le soupçonne, il est vrai, de sympathies démocrates. Selon Politico, Margrethe Vestager, la commissaire européenne à la concurrence, qui arrive lundi 18 septembre à Washington, va trouver une atmosphère nettement plus accueillante. Le « fan-club » américain de cette dernière est en « pleine expansion », constate le magazine. « L’Antitrust est de retour », exulte Luther Lowe, l’un des responsables de Yelp, la plate-forme de recommandations qui croise le fer depuis des années avec Google, accusé d’abus de position dominante.

    Longtemps, les jeunes innovateurs ont été accueillis avec bienveillance dans la capitale fédérale. Avec Barack Obama, c’était fusionnel. Quelque 250 cadres sont passés de Google à la Maison Blanche, et inversement. En fin de mandat, le président démocrate a alerté ses compatriotes sur les « méfaits » qui risquaient d’accompagner les « bienfaits » apportés par les technologies. Mais le débat a été escamoté pendant la campagne électorale. Aujourd’hui il revient comme un boomerang. De l’engorgement des villes par les chauffeurs Uber aux « fake news » et à l’agressivité grandissante de la société, la Silicon Valley – « le sombre centre d’un pouvoir sans contrôle », selon l’expression de Ben Smith, le rédacteur en chef de Buzzfeed – est rendue responsable de tous les maux de l’époque.

    Ses géants se présentent comme les champions de l’individualité et de la diversité, « alors que leurs algorithmes nous poussent à la conformité et écornent notre vie privée », tempête le journaliste de The Atlantic, Franklin Foer, dans un livre (World Without Mind, The Existential Threat of Big Tech, Penguin Press) publié le 12 septembre et déjà dans les meilleures ventes aux Etats-Unis.

    Menace pour la démocratie ?

    Washington ne peut plus rester inactif. Quarante-cinq pour cent des Américains reçoivent leurs informations par l’intermédiaire de Facebook. Si on inclut Instagram, WhatsApp et Messenger, la plate-forme de Mark Zuckerberg contrôle 80 % du trafic des réseaux sociaux sur mobile. La part de marché de Google dans les recherches en ligne dépasse 85 % aux Etats-Unis. Amazon assure 43 % des ventes en ligne… Et depuis l’élection, surtout, la menace sur la démocratie est prise au sérieux. « Sans Facebook, Trump serait-il président aujourd’hui ?, s’est interrogée Margaret Sullivan dans le Washington Post. Il y a de plus en plus de raisons de penser que la réponse est non. »

    Analyse similaire pour Evan Williams, l’un des fondateurs de Twitter, la plate-forme dont le président fait un usage immodéré. Donald Trump n’est que le « symptôme » d’un problème plus large, a-t-il déclaré à la BBC, celui de la dictature de la publicité ciblée instantanée, un système qui « abêtit le monde entier ».

    A peine le show Apple terminé, à Cupertino, le sénateur démocrate Al Franken a publié une lettre au PDG Tim Cook réclamant des éclaircissements sur la manière dont la firme entend gérer les questions d’atteinte potentielle à la vie privée. Que fera Apple si le gouvernement, comme l’a fait la NSA pour les communications électroniques, réclame les clés de son système de reconnaissance Face ID ? Quelles sont les mesures de protection de l’utilisateur si la police parvient à débloquer son smartphone en le brandissant devant son visage ? D’autres parlementaires réfléchissent à la manière de soumettre Facebook et Google, qui assurent 80 % des publicités en ligne, aux mêmes règles que les médias traditionnels sur les messages politiques.

    Pour une fois, conservateurs et progressistes font cause commune. L’ancien conseiller de M. Trump, Steve Bannon, l’a répété le 12 septembre à Hongkong : c’est lui qui avait « pris la tête », à la Maison Blanche, du camp qui voulait imposer aux entreprises technologiques les mêmes réglementations que les compagnies de téléphone ou d’électricité ; un scénario de cauchemar pour Google et Facebook, qui résistent depuis des années à l’idée d’être considérés comme autre chose que des plates-formes.

    A gauche, Bernie Sanders a fait la même proposition. Réglementation, scission, réforme de la loi antitrust ? Washington soupèse les formules. Quel que soit le résultat, le « backlash » (contrecoup) est réel. Comme Wall Street après des années de « greed » (cupidité), les titans de la Tech sont rattrapés par leurs excès.

  • Amazon doit être stoppé - New Republic
    http://alireailleurs.tumblr.com/post/100568367963

    « Amazon s’est enraciné dans la vie américaine moderne (…) tant et si bien qu’il a atteint un niveau de domination qui porte une étiquette ancienne : le #monopole », explique Franklin Foer (@franklinfoer), éditeur de The New Republic, le magazine de centre gauche américain. Il est le symbole du nouvel âge d’or du monopole incarné par les grandes entreprises de la Silicon Valley, celui des prix bas pour tout. Tant et si bien que nous n’aurions plus rien à craindre de ces nouveaux monopoles, qui, comme l’affirme l’investisseur Peter Thiel dans son dernier livre, Zero to One, ne sont que le synonymes d’entreprises qui réussissent. Pourtant, estime Foer, la guerre des prix que livrent ces géants industriels à notre profit, ne doit pas faire oublier les dépouilles qu’ils laissent sur leur passage. Après être (...)

    #concurrence #économie #GAFA