We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. As AI adoption continues to ramp up exponentially, so is the discussion around -- and concern for -- accountable AI. While tech leaders and field researchers understand the importance of developing AI that is ethical, safe and inclusive, they still grapple with issues around regulatory frameworks and concepts of "ethics washing" or "ethics shirking" that diminish accountability. Perhaps most importantly, the concept is not yet clearly defined. While many sets of suggested guidelines and tools exist -- from the U.S. National Institute of Standards and Technology's Artificial Intelligence Risk Management Framework to the European Commission's Expert Group on AI, for example -- they are not cohesive and are very often vague and overly complex.

Datasets are critical to AI and machine learning, and they are becoming a key driver of the economy. Collection of sensitive data is increasing rapidly, covering almost every aspect of people's lives. In its current form, this data collection puts both individuals and businesses at risk. I hope that 2020 will be the year when we build the foundation for a responsible data economy. Today, users have almost no control over how data they generate are used.