000			01482nab a2200229 c 4500
999			_c150200 _d150200
003			ES-MaIEF
005			20250205093639.0
007			ta
008			250203t2024 xxu||||| |||| 00| 0 eng d
040			_aES-MaIEF _bspa _cES-MaIEF
100			_931970 _aAcemoglu, Daron
245	1	0	_aRegulating transformative technologies _c Daron Acemoglu and Todd Lensman
504			_aBibliografía.
520			_aTransformative technologies like generative AI promise to accelerate productivity growth across many sectors, but they also present new risks from potential misuse. We develop a multisector technology adoption model to study the optimal regulation of transformative technologies when society can learn about these risks over time. Socially optimal adoption is gradual and typically convex. If social damages are large and proportional to the new technology's productivity, a higher growth rate paradoxically leads to slower optimal adoption. Equilibrium adoption is inefficient when firms do not internalize all social damages, and sector-independent regulation is helpful but generally not sufficient to restore optimality.
650		4	_950141 _aIMPUESTO SOBRE EL VALOR AÑADIDO
650		4	_942572 _aDESARROLLO TECNOLOGICO
650		4	_947498 _aINTELIGENCIA ARTIFICIAL
650		4	_948148 _aPRODUCTIVIDAD
700	1		_972252 _aLensman, Todd
773	0		_9172578 _oOP 2145/2024/3 _tThe American Economic Review _x 2640-205X _g v. 6, n. 3, September 2024, p. 359-376.
942			_cART