The GemLabs Podcast

In this episode, Gabor Farkas talks with Dan Davies about his book, 'The Unaccountability Machine,' which explores why big systems often make poor decisions and the implications of these failures. Dan, a former bank regulator and investment banker, discusses his career shift to investigating system breakdowns, complexity, and information theory. They delve into the history and principles of cybernetics, particularly Stafford Beer's viable system model, and how these can explain organizational failures and a lack of accountability. The conversation also touches on how modern economic theories and data biases impact decision-making processes and individual responsibilities in an increasingly complex world, including the role of AI and information technology. Dan underscores the need for more responsive and smaller-scaled decision-making units to mitigate the systemic issues of unaccountability.

In this episode of the GEMLabs podcast, we dive into AI governance with consultant Jörn Erbguth. The conversation spans the EU AI Act, highlighting its stages, potential errors, transparency, and intellectual property issues. Delving into ethical, cultural, and regulatory perspectives, the discussion examines the roles of corporations, governments, and the global impact of AI regulation. We also explore the risks and societal implications of AI, such as biometric categorization, facial recognition, and potential job displacement. Key themes include the balance between innovation and regulation, stakeholder responsibilities, and future challenges in AI development.

In this episode, Marianne Schoerling discusses the concept and importance of collective intelligence in addressing contemporary global challenges. Emphasizing the need for collaboration across diverse backgrounds, Marianne explores how collective intelligence acts as a catalyst for innovation and sustainable solutions. She delves into her experiences in innovation management, highlighting the significance of social systems and diversity in achieving meaningful outcomes. The conversation explores strategies for ensuring diverse participation in collective intelligence initiatives and the role of soft skills and inclusivity. Marianne also addresses the potential biases in data and emphasizes the importance of equitable access to collective intelligence platforms. Throughout, the dialogue provides insights into the role of leadership, diversity, and strategic planning in fostering sustainable innovation projects.

In this episode of the GEMLabs podcast, Gabor Farkas speaks with Ekkehard Ernst, the president and co-founder of GEMLabs (Geneva Macro Labs). They delve into the origins, growth, and future aspirations of GEMLabs, a think-and-do tank based in Geneva aimed at leveraging collective intelligence to advance the UN's Sustainable Development Goals. Ekkehard shares his motivations for starting the initiative, which began as a small lunch conversation and grew into a global network involved in various impactful projects. The discussion covers GEMLab's structure, challenges in securing funding, and the importance of community participation and younger generations' involvement. Ekkehard also highlights the need for sustainable funding sources and reflects on potential future directions, including focusing on projects related to natural capital and responsible consumption.

In this episode of the GemLabs podcast, host Gabor Farkas converses with Dr. Sandy Chong on the importance of AI inclusion and culturally diverse perspectives for creating a positive future. Dr. Chong, with her extensive background in Australian and Asian experiences, discusses her roles with the United Nations Association in Western Australia, ASEAN Business Alliance, and Australian Harvard Women. She underlines the importance of incorporating various cultural viewpoints and ethical frameworks, guided by the UN Sustainable Development Goals, into AI development. The discussion also highlights the necessity of trust, cultural diversity, and ethical innovation in AI. The conversation concludes with optimism about AI’s potential as a constructive tool for solving complex human problems and expresses hope for future dialogues on the evolution of AI.