By: Alexandru Circiumaru (The Platform Law Blog)
The first thing to be mindful of when thinking about artificial intelligence (“AI”) is the need to see through the hype that surrounds it. In the past few weeks alone there have been claims that an AI system has become sentient (it hasn’t), while narratives of AI either saving or destroying humanity are commonplace.
The regulation of AI poses significant challenges, and requires the involvement of different disciplines (e.g., data science, computer engineering, philosophy). Different stakeholders around the world have already started engaging with those challenges. Most notably, the European Union has recently started to develop a comprehensive regulatory framework for AI, a worthy pursuit which will undoubtedly shape the digital age and emerging algorithmic societies.
The purpose of this piece is to outline five key issues which have emerged from the legislative process around the Artificial Intelligence Act (“AIA”) in the 14 months that have passed since the proposal was published by the European Commission (the “Commission”). These issues will remain relevant until the legislative process is completed and the way in which they will be addressed will likely determine the effectiveness of the AIA. Before discussing these issues, I briefly introduce AI and its importance for modern societies.
What is AI?
One of the many challenges the regulation of AI brings about consists in determining what the term “AI” encompasses. A good place to start is the 2018 Commission Communication on AI, which states that “AI refers to systems that display intelligent behaviour by analysing their environment and taking actions – with some degree of autonomy – to achieve specific goals.” The AI High Level Expert Group (‘AIHLEG’) built on this definition, explaining that, as a scientific discipline, AI includes several approaches and techniques, such as machine learning, machine reasoning, and robotics.
The term “machine learning” is also important when discussing AI and its regulation. That is because machine learning is one of the most common and effective applications of AI, playing a key role in image recognition, product recommendations and spam filters. Many of the recent breakthroughs that have been made using AI involve machine learning…
