Earlier this year, the EU Commission tabled a Proposal of the European Parliament and Council on the Artificial Intelligence Act ("Proposal" or the "Act") a brief summary of which can be accessed through our website. The Proposal was recently scrutinised by the European Data Protection Board ("EDPB") and the European Data Protection Supervisor ("EDPS") in a joint opinion issued on the 18th of June 2021 ("Joint Opinion"). In this Joint Opinion the EDPB and EDPS, whilst acknowledging the Commission's initiative to extend the use of Artificial Intelligence Systems ("AI Systems") throughout the Member States, rejected a few of the tabled proposals. Of particular interest, in the Joint Opinion the EDPB and EDPS delves into the interaction between the EU Data Protection Law and the provisions of the Proposal. The EDPB and EDPS highlight the importance that the two frameworks to be complementary to each other and advised that any inconsistency or conflict should be eradicated as the lack of harmonisation could lead to directly or indirectly put the fundamental right to the protection of personal data at risk.

For some time, there has been an acute need for a legal framework to govern artificial intelligence (AI). This is largely due to the number of longstanding regulatory and ethical concerns surrounding the technology since its inception. I am a firm believer that we need to properly govern AI to prevent issues such as unethical biases, the undermining of legal and regulatory norms, and the blurred lines of organizational accountability from happening. These problems can seriously overwhelm users, business and citizens, and yet would be so avoidable if proper governance for AI was in place. So, earlier this year, when the EU Commission put forward the idea of a world-first legal framework for AI, great progress was made.

Between Microsoft's Tay debacle, the controversies surrounding Northpointe's Compas sentencing software, and Facebook's own algorithms helping spread online hate, AI's more egregious public failings over the past few years have shown off the technology's skeevy underbelly -- and just how much work we have to do before they can reliably and equitably interact with humanity. Of course such incidents have done little to tamp down the hype around and interest in artificial intelligences and machine learning systems, and they certainly haven't slowed the technology's march towards ubiquity. Turns out, one of the primary roadblocks to emerge against AI's continued adoption have been the users themselves. We're no longer the same dial-up rubes we were in the baud rate era. An entire generation has already grown to adulthood without ever knowing the horror of an offline world.

Certain machine behaviors never cease to amaze me. I'm astounded by their ability to learn from their accomplishments and from their interactions with we humans. Unfortunately, many business managers still think of artificial intelligence (AI) and machine learning algorithms as something that will be impossible for them to understand. But I believe that knowing the fundamental principles that underlie the new technologies behind autonomous vehicles, shopping recommendation engines, Alexa and the rest can boost managers' confidence in them and help them make their companies more innovative. The two key drivers of major smart technologies today are machine learning and deep learning.

Artificial Intelligence (AI) is becoming increasingly important. Thus, sound knowledge about the principles of AI will be a crucial factor for future careers of young people as well as for the development of novel, innovative products. Addressing this challenge, we present an ambitious 3-year project focusing on developing and implementing a professional, internationally accepted, standardized training and certification system for AI which will also be recognized by the industry and educational institutions. The approach is based on already implemented and evaluated pilot projects in the area of AI education. The project’s main goal is to train and certify teachers and mentors as well as students and young people in basic and advanced AI topics, fostering AI literacy among this target audience.