The field of AI research is moving towards developing more robust and scalable oversight mechanisms to control future superintelligent systems. Researchers are exploring new frameworks and models to quantify the probability of successful oversight, taking into account the capabilities of the overseer and the system being overseen. Additionally, there is a growing focus on defending against intelligent attackers at large scales, with studies investigating the effect of scale on cybersecurity and proposing new defense strategies. Another area of interest is the development of more accurate strength estimation methods in games, which can improve human-AI interactions. Furthermore, researchers are working on discovering play styles and game behaviors in online gaming platforms, which can help create a psychological imprint of the user and propel deeper understanding towards players' experience and growth. Notable papers include: Policies of Multiple Skill Levels for Better Strength Estimation in Games, which improved the accuracy of strength estimation by taking into account human players' behavior tendency. CognitionNet: A Collaborative Neural Network for Play Style Discovery in Online Skill Gaming Platform, which proposed a two-stage deep neural network to discover play styles and game behaviors in online gaming platforms.