Since I learned SEO in a web agency, I’ve always been sidelined between two common strategies. Either optimize my content for end-users through genuine and human-made content. Or optimize it for Google through technical shortcuts and generated content.
For Google, the debate has always been straightforward: human input is everything, so according to their guidelines you better create by yourself reliable, accurate and relevant content.
Yet, as machine learning technologies are growing, generated content might be proliferating on the Internet, without having a way to differentiate it from human content. …
“I certainly hope and believe that no great efforts will be put into making machines with […] the shape of the human body….their results would have something like the unpleasant quality of artificial flowers”
This is Alan Turing’s warning to all those who wish to make machines the alter-ego of man.
But why Turing’s high disregard for the robot’s look?
One way of putting it is that Turing considered this to be a “futile” and counterproductive effort. To him, designers should concentrate on more essential features like the calculation and thinking processes.
Yet, the question remains troubling and deserves to be asked : what are the emotional implications of building a humanoid robot? As designers are building increasingly human-like robots (like Samsung Neon strange display), these could fulfill the emotional needs of our relatives, friends, and customers, and even replace us for this task. In the last case, humans may be out of job, and robots question the future of human…
Since scientists discovered the predictive power of probability, economists have often been tempted to apply the probabilistic reasoning to our societies.
They have tried to explain the chances of success in an investment or market share, by comparing the expected values at stakes. Yet, unlike a simple roll of the dice, financial and human affairs can never be repeated under the same conditions. Each situation is unique, and human actors face problems of which they will never have the last word.
Nevertheless, for John Kay and Mervin King in Radical Uncertainty, it is easy to be fooled by numerical reasoning. …
As companies are using increasingly intelligent technologies, the question has emerged on how to keep them at the service of the user’s good, and not the designers’ ambitions.
Many AI founding theorists (Alan Turing, Norbert Wiener…) have predicted the rise of a “superintelligent AI”, which could exceed their designer’s understanding. According to Stuart Russell in Human Compatible, this potential threat is an opportunity to define technology goals that are truly for the benefit of people.
These Products that are designed from the outset for the specific benefit of the user,
Here’s how designers can built products that are unlikely to backfire, or respond to preferences that the user doesn’t have, and so restore the power of users. …
Since the digital era, some consumers have distinguished themselves by their distant relation with new technologies.
Refusing to take them as an irreducible sign of our time, they have closely considered the benefits and drawbacks of digital tools on them.
According to Cal Newport in Minimalism, these minimalists learned to actively choose the place and value of these products in their lives, rather than taken them as granted. They have learned to be pro-active in their purchase decisions.
This new generation of consumers is growing and will undoubtedly define the new consumer culture of the future. …
When Paul Ekman presented his theory of emotional facial recognition, he considered emotions as universally interpretable. And many companies like Affectiva have used this statement to create emotion reading technologies for marketing purposes.
By guessing people’s emotions based on facial patterns and similar body expressions, they claim to predict their specific feelings with more than 90% accuracy.
New research in the movement of a constructivist vision of emotions has put their results into perspective. …
We have all been tempted by the thousand ways to achieve success, grow, and boost our leadership. We have all believed in the results of adopting them.
Yet, even if these can help us on our path, they are no shortcut to permanent practice and experimentation.
According to David Epstein in Range, learning is a non-linear process. Successful learner have found improvement not by finding the easiest way, but through a struggling and never-ending path that make them face complex problems.
In this way, improvisation, critical thinking, and a wide range of cross-functional skills have become huge benefits for them. Whereas deep, focused expertise limited their abilities in one area, generalists skills have helped them gain superior flexibility in the face of adversity. …
Over the last ten years, open innovation has become a recurring issue in the management of large companies. More organizations have dreamed of extensive collaboration across their various departments and with external partners as their innovation ideal.
But fewer people ask about which type of employees can best contribute to these new types of organizations. According to David Epstein in Range, the number one value of these employees is the broad and varied range of their skills.
Creative collaborators are less and fewer lifetime specialists in one area of expertise, and more and more generalists who often change fields and can think about cross-cutting issues. …
Have you ever dreamed of working on a project vital to you but never had the time?
Now it’s time to get started, but not just in any way.
Your work habits are usually undermined by distractions and interruptions that prevent you from focusing deeply on an object. So to really get the most out of your skills.
According to Cal Newport in Deep Work, if you seek to create a differentiating skill, you need to boost your ability to get into intense concentration.
Unfortunately, the motivation to work intensely is limited and unnatural. …