Exploring the impact of AI on jobs, including the uncertainties and potential risks. Discusses the role of AI in writing and creative industries. Examines income inequality and the need for wealth distribution. Explores retirement benefits and an AI chatbot handling telemarketers.
AI can be used as a creative assistant for screenwriters but poses a threat to average creative writers.
There is a need for wealth redistribution and ensuring AI's benefits reach the lower-income classes through taxes and other means.
Deep dives
The Impact of AI on Jobs
The podcast explores the impact of AI on jobs and begins by discussing the recent Hollywood writers strike and their agreements regarding artificial intelligence. The podcast emphasizes that AI cannot hold copyright and therefore cannot be considered a writer, which lessens the risk of AI taking over jobs from screenwriters in Hollywood. It is mentioned that AI can be used by screenwriters as assistants to generate ideas and storylines. The podcast also highlights the increasing capability of AI in creative writing, posing a threat to average creative writers. The host considers the paper by Fry and Osborne that claimed 47% of US employment is at high risk of automation but points out the controversial nature of the study. The podcast raises questions about the future of jobs, the feasibility of universal basic income, and the potential for increasing inequality due to AI.
The Need for Wealth Redistribution
The podcast explores the issue of wealth redistribution in the context of AI's impact on jobs. It argues that as AI generates more wealth, there is a necessity to ensure that the benefits are distributed beyond the wealthy few. The podcast questions how the money from AI's benefits will reach the lower-income classes, as current wealth distribution mainly favors the owners and executives of technology companies. The host emphasizes the importance of taxes as a means to redistribute wealth, citing the limitations of philanthropy. The podcast discusses the concept of universal basic income and its potential for addressing the threat of job displacement caused by AI. It also raises concerns about the psychological impact of unemployment and the need to consider individuals' well-being beyond financial aspects.
Challenges and Controversies in Job Transformation
The podcast addresses several challenges and controversies related to AI's impact on jobs. It questions the accuracy of predictions regarding which jobs are at the highest risk of automation, using the example of point-of-sale clerks whose tasks extend beyond repetitive work. The podcast highlights the potential automation of jobs in the C-suite and on boards of directors, discussing the benefits and disadvantages of AI in these positions. It also raises the issue of increasing income inequality, with CEOs' pay ratios compared to worker pay and the widening wealth gap highlighted. The podcast poses important questions about the creation of better jobs and the potential for fewer people to access them, as well as the psychological aspects of job satisfaction and individual experiences in a changing job market.
Global Framework and Ethical Considerations
The podcast discusses the need for a global framework for AI and the role of international collaboration in addressing its impact on jobs. It mentions European Commission President Ursula von de Leyen's proposal to create such a framework and emphasizes the importance of including partner countries, tech companies, and independent experts in its development. The podcast also explores the ethical considerations of AI's impact on jobs, such as the potential for capital to accumulate disproportionately and exacerbate inequity. It raises questions about the psychological and societal consequences of continued wealth accumulation and urges attention to the potential for future job dissatisfaction. The podcast concludes by highlighting the importance of human collaboration and solidarity in navigating the challenges of AI and job transformation.
What effect will #AI, especially large language models like #ChatGPT, have on jobs? The conversation is intense and fractious. I attempt to shed some light on those effects, and discuss some of the different predictions and proposals for distributing the dividend from reducing costs and increasing markets through deploying AI. How will that capital get to where it is needed?
All this plus our usual look at today's AI headlines.