The EU Commission recently proposed a new set of stringent rules to regulate AI, citing an urgent need. With the global race to regulate AI officially on, the EU published a detailed proposal on how AI should be regulated, explicitly banning some uses and defining those it considers "high-risk," planning to ban the use of AI that threatens people's rights and safety. We can all agree with the sentiment of Margrethe Vestager, the European Commission executive vice president, when she said that when it comes to "artificial intelligence, trust is a must, not a nice to have," but is regulation the most effective and efficient way to secure this reality? The takeaways from the commission are incredibly in-depth, but the ones that make the most sense to me are those that stress regulated AI should aim to increase human well-being. However, regulation should not overly constrain experimentation and development of AI systems.

When it comes to new technologies like Artificial Intelligence, the pure technology is only a small aspect required to putting it to use. Still, given the hype that exists currently, one can easily loose sight of the big picture as announcements of new algorithms, toolboxes, or cloud services fight for grabbing our attention as the next game changer. The field itself can also feel quite overwhelming at times, as it is always expanding and keeping track of all the developments seems impossible for one individual to do. There was a time when a single individual could cover all the bits and pieces, but given the explosive expansion that this field has been going through these past years, I think it is becoming more and more challenging. So this is my attempt to draw a bigger picture of how different roles and levels fit together to "do AI" in an enterprise setting.