##lfsson, d. li and l. r. raymond, “ generative ai at work. ” national bureau of economic research working paper no. 31161 ( april 2023 ). 4 s. peng, e. kalliamvakou, p. cihon and m. demirer, “ the impact of ai on developer productivity : evidence from github copilot, ” arxiv : 2302. 06590 ( february 2023 ). boost total factor productivity ( tfp ) by 9 % over the next decade. 5 a similar sustained improvement in tfp in canada would raise the average income per - person by roughly $ 4, 000 a year. this productivity boost is not just from automating tasks. as workers in lower productivity jobs are replaced by ai, they are freed up to fill other, more productive jobs in the economy. and new products and services emerge. these latter two effects provide most of the positive impact on productivity. 6 however, more pessimistic estimates suggest that ai might have only a modest impact on productivity. 7 these assessments take the view that fewer tasks can be effectively automated. ai could also create negative outcomes, such as amplifying internet addiction and enabling malicious actors. these adverse effects could substantially decrease the net positive impact of ai. as we look at the effects of ai on the broader economy, we also need to ask if this technology will be transformative enough to significantly boost productivity growth. or will ai simply be the latest innovation in a chain of innovations — like the invention of the sewing machine or the evolution of telecommunications — to keep productivity rising at its historical pace. this matters a lot because productivity growth plays a key role in determining how fast the economy can expand without sparking inflation. so what is actually happening? the infrastructure needed to make ai broadly available is being built quickly. ai platforms are sprouting up, and it is getting easier for businesses — large and small — to access the technology. but we are still looking for the new products and services — and the new business models — that will transform efficiency and productivity. prices and inflation ai adoption — and its full effect on productivity — will play out over many years. in the long run, we can expect ai to boost productivity. higher productivity allows for higher wages and more spending without pushing up inflation. but what about in the short run? already, strong investment in ai technologies is boosting demand in the economy. the run - up

navigating uncertainty we know that ai could have profound effects on the economy. but we also know that the timing, magnitude and even direction of these effects is uncertain. so how do monetary policy - makers manage this uncertainty? when you enter a dark room, you don ’ t go charging in. you cautiously feel your way around. and you try to find the light switch. that is what we are doing. what we central bankers need is more light. this means better information, along with research and analysis on how technology is diffused. its impact on businesses and on workers. and its effect on the overall economy and inflation. to this end, i encourage academics to work with businesses and policy - makers to better understand and predict the impacts of ai. and i applaud the national bureau of economic research and my former colleagues at the university of toronto for this conference series, which is putting a spotlight on the economics of ai. we can also use scenarios to better understand the potential effects of ai and manage risks so that we can get more of the good with less of the bad. for example, in a recent 8 y. gorodnichenko and o. talavera, “ price setting in online markets : basic facts, international comparisons, and cross - border integration, ” american economic review no. 107, issue 1 : 249 – 282 ( january 2017 ). 9 however, in an environment with greater competition, firms may adjust their prices by less because they don ’ t want their prices to differ too much from those of their competitors. this could make the phillips curve flatter. speech, gita gopinath, deputy managing director of the international monetary fund, explored how the adoption of ai could worsen the next recession for workers. 10 she noted that in previous downturns, most automation - related job losses happened in the first year of the recession and those jobs never came back. widespread adoption of ai could make this problem worse because more jobs could be ripe for automation. ai adoption could also lead to financial stability issues. banks and financial institutions are investing in ai to improve customer service, to enhance compliance and risk management, and to better assess credit and liquidity risk. in principle, these investments should improve efficiency and stability. but there are pitfalls. operational risks could become concentrated in a few third - party service providers and an event at one of them could quickly spread through the financial system. the predictive ability of ai can deteriorate unexpectedly, suffer