YouTube video by Vishen

[Surfing AI Shock] [Human Written*] Recent radio clip of me talking about the real issue behind AI companies scanning and destroying books. The image of this is a great metaphor for how AI companies are strip-mining our collective intellectual property and then selling it back to us. If it were minerals, we would expect them to pay royalties. From the AI Dividend Chapter of my Surfing AI Book: 'Another related way of looking at the process of training chatbots, image and video generators, and similar AI on collectively owned intellectual property is to see it as similar to the process of mineral mining. Chatbots and related types of AI can be seen as mining a natural resource, human language, creative images, videos, music, or other human-produced products. In the case of mineral extraction, many governments demand royalty payments to recognize that minerals can be viewed as the collective property of the citizens of the country where the minerals are located. Therefore, it is not a great leap to contemplate the idea of royalty payments being sought from corporations involved in developing some forms of AI.' The chapter is here: https://lnkd.in/esyFpEDb [*This post was Human Written, see declaration at https://lnkd.in/euYQTNxX] #aiintellectualproperty #aidivident #prosocialai #surfingai

Sam Altman wants to give the U.S. government a 5% stake in OpenAI and share the returns with every American, but the numbers tell a sobering story. Each person's cut could amount to as little as $125, in a company that is spending twice what it earns. Before the dream of a national AI dividend takes hold, it helps to understand what it would actually take to make it real. https://qz.com/openai-5-percent-government-stake-mechanics-081226

Alex Bores, a former employee of Palantir and current Democratic candidate for the U.S. House of Representatives in New York, has introduced a policy proposal called the “AI dividend.” The plan is designed to address potential large-scale job displacement caused by advances in artificial intelligence and the concentration of wealth generated by these technologies. Under the proposal, Americans would receive direct financial payments if AI significantly increases productivity while reducing human employment opportunities. In addition to cash transfers, the program would fund workforce retraining, education initiatives, and strengthen government capacity to regulate AI systems and support independent oversight. Bores compares the idea to insurance, arguing that society should prepare for potential economic disruption even if the worst-case scenario does not occur. He notes that leading AI developers themselves have acknowledged their goal of automating much of human labor, which he says makes proactive policy intervention necessary. The proposal would be financed through several mechanisms, including a modest tax on AI usage, government equity stakes in advanced AI companies, and changes to tax incentives that currently encourage automation when it reduces employment. Bores also suggests that participation from AI companies in supporting such a plan would demonstrate sincerity about the societal impact of their technologies. The idea has emerged amid broader debates over universal basic income, technological unemployment, and the role of government in managing the economic effects of rapid AI development. Critics and supporters alike see it as part of a growing policy conversation about how to distribute the benefits and risks of artificial intelligence in the economy.