Links for this week (weekly)

  • “Companies are not managing their employees’ long term careers any more. Workers must be their own HRD-professionals. With opportunity comes new responsibility. It is up to the worker to construct the narrative of work-life, to know what to contribute, when to change course and how to keep engaged – much longer than we have been used to. To do those things well you have to develop a new understanding of yourself and what you are actually up to.”

    tags: hr carreer patterns quantifiedself bigdata

    • The industrial era schools and workplaces were organized on the assumption that there is one right way to learn, or to do things, and it is the same for everybody.
    • This is where the biggest changes take place. Instead of the industrial era generalizations and abstractions of what is good for you, or what five steps everybody should take, it is now time to cultivate a deep understanding of the context, the unique, particular, situation you are in.
    • Most of the choices we make each day are believed to be the products of well-considered, rational decisions based on knowledge, but they are not. They are repeating patterns, habits. We are not conscious in the way we think we are; we do most of the things we do on autopilot.
    • I believe that the productivity suites of tomorrow are going to be a combination of sensors, big data and quantified-self technologies.
    • Managing yourself is first and foremost about pattern recognition. It is essential to remedy the things you repeatedly do, that don’t serve you and the life you want to create.
  • “Which might, in the modern, privacy-free world of sliced and diced web-browsing analysis, come as something of a surprise. Marketing departments gather terabytes of data on potential customers, spend fortunes on software to analyse their spending habits and painstakingly “segment” the data to calibrate their campaigns to appeal to specific groups. And still they get it almost completely wrong.”

    tags: marketing socialmedia demographics psychologicalprofiles profiling profile psychology humanresources

    • the problem is that firms are trying to understand their customers by studying their “demographics” (age, sex, marital status, dwelling place, income and so on) and their existing buying habits. That approach, he believes, is flawed. What they really need is a way to discover the “deep psychological profiles” of their customers, including their personalities, values and needs.
    • He and his team have developed software that takes streams of “tweets” from this social medium and searches them for words that indicate a tweeter’s personality, values and needs.
    • Dr Haber analysed three months’ worth of data from 90m users of Twitter. His software was able to parse someone’s presumptive personality reasonably well from just 50 tweets, and very well indeed from 200.
  • “Dans un monde de plus en plus axé sur les données, produites en surabondance, il nous faudra nous défaire d’un vieux réflexe qui a permis à l’être humain de survivre jusqu’à maintenant.

    Nous devons apprendre à restreindre notre propension à déduire des causes là où il n’y a que des corrélations fortuites.”

    tags: bigdata correlation causality

    • Le citoyen de demain doit maîtriser la différence entre causalité et corrélation.
    • Avec la montée des données volumineuses et de tous ces outils d’analyse en temps réel des foules, des mouvements, des transactions, notre monde est devenu plus complexe à interpréter.
    • l’analyse de données très volumineuses ne permet pas toujours de connaître la cause, mais simplement le lien, la corrélation entre deux choses, entre deux événements.
    • le big data permet de créer d’immenses quantités de données qui sont corrélées. Ça nous donne des statistiques sur la société, sur notre environnement, mais pas toujours les réponses à nos questions primaires de causalité.
    • Interpréter ce monde par les données demande d’acquérir de nouveaux réflexes, donc une éducation aux logiques statistiques et probabilistes, donc une pensée rationnelle, scientifique.

Posted from Diigo. The rest of my favorite links are here.

Head of Employee and Client Experience @Emakina / Former consulting director / Crossroads of people, business and technology / Speaker / Compulsive traveler
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