Artificial Intelligence (AI), particularly Large Language Models (LLMs), has made significant strides in recent years, transforming the way we live and work. This talk delves into the wide-ranging implications of AI for modern leaders, organizations, societies, and individuals. By understanding the capabilities and limitations of these advanced models, leaders can harness their potential for decision-making, creativity, collaboration, and problem-solving. We will address critical questions surrounding the ethical, economic, and social aspects of LLMs and AI, exploring their impact on the workforce, privacy, accountability, and the future of human-AI interactions. Join us for an engaging and thought-provoking discussion on navigating the AI revolution and shaping a better future for all stakeholders.

Artificial intelligence (AI) is increasingly used to make decisions affecting individuals, societies, and organizations. Modern leaders need to understand the opportunities and challenges related to AI's growing importance. In this talk, we will discuss a number of important and timely questions pertaining to AI: How does it work? What is fueling its growing popularity? How is it transforming industries and business models? Can it be creative? Can it make fair decisions? Can AI decisions be interpreted? When is AI better than human decision makers? When will AI take over the world?

A growing proportion of human activities―such as social interactions, entertainment, shopping, and gathering information―are now mediated by digital devices and services. Such digitally mediated activities can be easily recorded, offering an unprecedented opportunity to study and assess psychological traits using actual (rather than self-reported) behavior. Our research shows that digital records of behavior―such as facial images, samples of text, Tweets, Facebook Likes, or web-browsing logs―can be used to accurately measure a wide range of psychological traits. Such predictions do not require participants' active involvement; can be easily and inexpensively applied to large populations; and are relatively immune to misrepresentation. Consequently, the predictability of psychological traits offers a promise to improve research and practice in fields ranging from psychology, sociology, and education to management and marketing. However, if applied unethically, the same models pose unprecedented risks to the privacy and well-being of entire societies.

With an increasing reliance on digital devices and platforms in healthcare, there is a vast amount of patient data available that can revolutionize medical practices. Our research demonstrates that digital traces, such as facial images, patient-written notes, health-related online interactions, and browsing habits, can be harnessed to assess various psychological and medical conditions more accurately than traditional self-reports. These findings open up possibilities for more personalized care and monitoring without a patient's active involvement. Furthermore, such predictions can be conducted inexpensively at a large scale and are less prone to misrepresentation. This potential holds immense promise for enhancing research and applications in the medical and psychological domains. However, the misuse of this data can pose significant threats to patient privacy and well-being, emphasizing the need for ethical considerations and robust data protection measures in the healthcare industry. Professor Kosinski's goal is to provide you with a deeper understanding of the double-edged sword that is digital data: its transformative potential for research and practical applications, as well as the pressing ethical considerations we must address to ensure that the end of privacy doesn't mean the end of individual autonomy and societal well-being. You will walk away better equipped to navigate our increasingly digital world, emphasizing responsible data use and safeguarding personal and collective privacy.