arXiv subjects

Jakub Growiec

Publications and source records attributed to Jakub Growiec.

4 recordsLinked to original sources

arXiv2026

Redistributive Policies for the Times of Transformative AI

After the arrival of transformative artificial intelligence (TAI), broad-based automation is expected to decrease the labor share and increase income and wealth inequality. Although economic growth is likely to accelerate, most of its gains may accrue to a narrow group of individuals and firms. Hence, if unmitigated by redistributive policy, income and wealth inequality may rise to levels unseen in the industrial economy. Using a unifying theoretical framework, we survey the redistributive policies proposed for the era of TAI, such as universal basic income (UBI), universal basic capital (UBC), state-issued compute and robot permits, and taxes on capital, compute, robots, tokens, land, energy, consumption, and wealth. We argue that policies that are able to broadly distribute rents from capital including compute and robots - such as UBC or UBI financed through capital taxes - are most likely to achieve lasting reductions in inequality in a world with human-aligned transformative AI.

econ.GN↗

arXiv2026

The Economics of p(doom): Scenarios of Existential Risk and Economic Growth in the Age of Transformative AI

Recent advances in artificial intelligence (AI) have led to a wide range of predictions about its long-term impact on humanity. A central focus is the potential emergence of transformative AI (TAI), eventually capable of outperforming humans in all economically valuable tasks and fully automating labor. Discussed scenarios range from unprecedented economic growth and abundance ("post-scarcity" or "cornucopia") to human extinction after a misaligned TAI takes over ("AI doom"). However, the probabilities and implications of these scenarios remain highly uncertain. We contribute by organizing the various scenarios and evaluating their associated existential risks and economic outcomes in terms of aggregate welfare. Our results imply that even low-probability catastrophic outcomes justify substantial investments in AI safety and alignment research. This result highlights that current global efforts in AI safety and alignment research are insufficient relative to the scale and urgency of the risks posed by TAI.

econ.GN↗

arXiv2026

Workers' Incentives and the Optimal Taxation of AI

We characterize the optimal tax policy in an economy with human manual and cognitive labor, physical capital, and artificial intelligence (AI). Extending the dynamic taxation setup of Slavik and Yazici (2014), we find that it is optimal to start taxing AI when cognitive workers start to consider switching to manual jobs. This threshold may be crossed once AI becomes sufficiently capable in substituting humans across cognitive tasks.

econ.GN↗

arXiv2025

The Paradox of Doom: Acknowledging Extinction Risk Reduces the Incentive to Prevent It

We investigate the salience of extinction risk as a source of impatience. Our framework distinguishes between human extinction risk and individual mortality risk while allowing for various degrees of intergenerational altruism. Additionally, we consider the evolutionarily motivated "selfish gene" perspective. We find that the risk of human extinction is an indispensable component of the discount rate, whereas individual mortality risk can be hedged against - partially or fully, depending on the setup - through human reproduction. Overall, we show that in the face of extinction risk, people become more impatient rather than more farsighted. Thus, the greater the threat of extinction, the less incentive there is to invest in avoiding it. Our framework can help explain why humanity consistently underinvests in mitigation of catastrophic risks, ranging from climate change mitigation, via pandemic prevention, to addressing the emerging risks of transformative artificial intelligence.

econ.GN↗