Over the past year and a half, our lives have become more digital than ever before. A huge number of people have been working from home, attending online classes and looking at countless photos and videos on social media. Passwords are essential for all those platforms and channels, and that has caused a new phenomenon: password anxiety. Fortunately, it is something that is easily remedied.
Sharing vehicles with your neighbors or colleagues is no longer a pipe dream. Enter BattMobility: a platform and an app that makes sharing electric vehicles easy. As a partner of BattMobility, Sofico took on the task of developing the platform and was able to rely on AE’s expertise for this.
The past year has been a tough learning curve. We have learned that we are all in the same COVID storm together, but not everyone is in the same boat. The adaptability of organizations and the great efforts of employees soon resulted in new working methods that saw working from home as the mandatory norm. However, no one-size-fits all approach was available to make this actually work. Even now that the curve is going up again and restrictions are tightening once more, we are already thinking together about how we are going to shape better times ahead. The two principles of psychological freedom and inclusion will definitely get us off to a good start. And yes, some generous doses of creativity and technology can also give us an extra boost.
In a previous blog post we talked about the importance of accessibility in your application. In this post we will zoom in on screen readers. A screen reader is a program that helps people with a visual impairment to interact with your website or application by reading aloud what is displayed on the screen. To enable this, the front-end code must provide structure and recognizable elements. Actually, the web is accessible by default and screen readers can manage perfectly, it is just our job to not screw it up. So here are some tips and tricks to make sure you don’t.
Artificial Intelligence (AI) and Machine Learning (ML) used in the right way offer companies new and unprecedented opportunities to tap into. For the man and woman in the street it brings many new and exciting advances in their everyday lives. However, they also have a dark side. When we design algorithms and train models based on data of a privileged minority group, ML model outcomes (like predictions, recommendations, classifications,...) have the ability to discriminate and exclude large parts of the population in a way that is not acceptable. Fact is that we don’t always realize this, and thus need to be very careful and build in checks to avoid these circumstances.