Today, online social systems have become integral to our daily lives. Yet, these systems and the algorithms driving them surface problematic content, whether they be harmful misinformation or damaging conspiracy theories. Left unchecked, these problems can negatively impact our democracy. How do we systematically investigate algorithmic misinformation? How do we govern algorithmic systems to safeguard against problematic content? In this talk, I will present results of algorithmic audits for misinformation conducted on the search and recommendation algorithms driving two platforms: 1) YouTube, the most popular video search platform and 2) Amazon, world's leading e-commerce platform. I will end with ideas for how we can develop effective long-term algorithmic governance, the challenges in doing so and the new governance challenges and opportunities that are emerging with the recent advances in the field of large language models.