“AI will likely render what I do and what you aspire to do as obsolete. Likewise to careers in marketing, accounting, engineering whether software, biological, mechanical data analysis, research management.
Season 3, Episode 5, Lioness
All of these careers will disappear in the next decade. You must alter the focus of your education to include machine learning, computer vision and management strategies, NLP engineering, computer vision engineering. And you must prepare yourselves for a world in which your endeavors are not compensated with money. Your compensation is in the collective betterment of our society, of our state.
What, no money, you say? Yep, that’s the future. Your efforts will be compensated through the services provided to you in return from the state housing, health care, food, clean transportation, entertainment.
And as you prepare yourselves for a career in the future, you must prepare yourselves also for a world that replaces the imperialist goals and economic meddling of a “free-market society” with a dedication to a state that in turn dedicates itself to an equitable life for all humankind.“
The submitted text (excerpt from Lioness, S03E05) articulates a radical thesis: algorithmic automation would render obsolete not only professions in analysis and research, but the very principle of wage-based remuneration, in favor of an allocation of services guaranteed by the state. Elon Musk’s statements on “Universal High Income” (UHI), a high universal income, not merely a subsistence income, fit into this vision, positing that technological deflation will make it possible to finance abundance without inflation.
Our analysis, conducted from the perspectives of quantitative finance, game theory, and monetary engineering, leads to the following conclusions:
The thesis that salaried employment is disappearing is partially supported by labor share data: The share of labor income in global GDP fell to \~53% in Q2 2026, its lowest level since 1947. Automation (AI, robotics) accounts for more than a quarter of this decline. This trend is structural, not cyclical.
The WEF projects a restructuring, not a net destruction of jobs: The Future of Jobs Report 2025 anticipates 92 million jobs lost and 170 million jobs created by 2030 (net: +78 million). However, the jobs created require radically different skills (AI, big data, fintech), widening the gap between those who control algorithmic capital and those who are excluded from it.
The future compensation mechanism will not be a “salary” but income derived from capital: The most robust proposals (academically and politically) are not the classic UBI, but Universal Basic Capital (UBC), the distribution of productive assets (shares, stakes in sovereign wealth funds, rights to AI revenues) or resource dividends (the Alaska Permanent Fund model, ~$1,000–1,500/year per resident). Anthropic has already taken this step in 2026 by injecting 5% of its equity into a public welfare fund, and Musk has proposed distributing SpaceX shares to every American child.
Tax feasibility is the sticking point: In January 2026, the OECD formalized a global minimum tax of 15% on multinational corporations, but US Big Tech companies are largely exempt through a “safe harbor” negotiated by Washington. Without global tax coordination, the concentration of algorithmic capital will make funding any universal transfer structurally unstable (risk of oligarchy, Krugman 2026).
Programmable money is the execution infrastructure: The BIS, through Project Agorá (eight central banks, more than 40 institutions), is developing a “unified ledger” enabling conditional programmable transfers (UBI, data dividends, subsidies) with full traceability. This architecture makes automated distribution technically possible, but raises risks of social control and monetary fragmentation.
Anticipate a transition in which labor compensation does not disappear but shifts toward a combination of (i) labor income from skills complementary to AI (supervision, creativity, ethics), (ii) ownership rights in algorithmic capital (UBC, sovereign wealth funds, equity-sharing), and (iii) programmable cash transfers funded by automation rents. “Scarce” assets (physical gold, Bitcoin) retain their role as a hedge against monetary and institutional uncertainty.
The economic model based on wages as the main source of aggregate demand is being challenged by the declining labor share, the decoupling of productivity from wages, and the substitution of capital for labor. In the United States, labor income’s share of GDP fell from ~65% after World War II to ~53% in Q2 2026, notably as a result of automation, while AI is accelerating the decline, according to Paul Krugman. The WEF has observed a growing gap between productivity and compensation since the 1970s, with the gains primarily benefiting capital owners. A study by MIT (January 2026) nevertheless specifies that investment and demand for skilled labor could support wages if institutions redistribute the gains. The WEF projects 92 million jobs displaced and 170 million jobs created by 2030, resulting in a net gain of +78 million jobs, with 22% turnover in the global workforce.
Formal modeling indicates that high substitutability between algorithmic capital and labor can reduce labor’s share even when total output increases. In April 2026, Elon Musk proposed a “Universal HIGH INCOME” (UHI), a high income funded by productivity gains from AI and robotics and made possible by technological deflation. This hypothesis remains uncertain because productivity gains do not automatically lower prices, and algorithmic oligopolies may maintain high prices in essential sectors.
Recent literature favors redistributing capital rents to sustainably reduce inequality, through a UBI funded by taxes on capital or a Universal Basic Capital (UBC) that directly distributes productive assets. A model covering 26 EU economies (June 2026) estimates that a UBC fund could reach ~€81,545 per citizen after 30 years, compared with ~€32,000 for a pure UBI, with its dividend exceeding that of the UBI from the 10th year onward. [33,34] Future remuneration could therefore combine wages linked to skills that complement AI, dividends from algorithmic capital, and targeted or universal cash transfers.
