I Robot: U Tax? Considering the Tax Policy Implications of Automation
Notice bibliographique
Résumé
In a 2017 interview, Microsoft founder Bill Gates recommended taxing robots to slow the pace of automation. Funds raised could be used to retrain and financially support displaced workers. Up to 47 per cent of US jobs are at risk by advancements in artificial intelligence. Low-wage workers currently hold a majority of those at-risk jobs. Increased automation is likely to exacerbate income inequality. While employment changes due to automation are not new, advances in artificial intelligence threaten to eliminate many more jobs than were eliminated historically through automation. Accelerated automation presents two problems: a revenue problem and a human problem. The revenue problem exists because the tax system is designed to tax labour more heavily than capital, as labour is less likely to be able to avoid taxation. Capital investment, on the other hand, is taxed more lightly because capital is mobile and can escape taxation. When capital becomes labour, as in automation, the bottom falls out of the system. The human problem is first that most people need income from working to survive. Some scholars have advocated for a governmentally provided universal basic income (UBI). Taxing robots could in theory provide revenue for a UBI, although any source of revenue would work just as well. While a UBI would solve the survival problem, humans need more than basic survival. In his classic work, psychologist Abraham Maslow listed survival as the foundation of his hierarchy of needs. Work satisfies the higher order needs of social identity and self-esteem. The Tax Cuts and Jobs Act ( TCJA ), enacted in December 2017, significantly cut the US corporate tax rate, from 35 per cent to 21 per cent. In addition, TCJA increased tax benefits for purchasing equipment (which would include automation) by significantly enhancing bonus depreciation. The new tax legislation continued and deepened the existing tax bias towards automation. This article explores policy options for solving the revenue problem and the "jobs" problem, including a discussion and critique of UBI proposals and recommendations for other policy options, such as an enhanced earned income tax credit, incentives for employers, and reviving an idea from the Great Depression, the Civilian Conservation Corps.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».