. for algorithmic traders, even nanoseconds can represent a long time. the media or political cycle operates over a matter of hours. and, as we saw yesterday, acting to sustain orderly markets may also require action at short order. but monetary policy needs to be framed on a more considered or lower frequency basis, reflecting both the famously ‘ long and variable lags ’ in the transmission of monetary policy to price developments, as well as the need to distinguish signal from noise in the flow of incoming data and analysis. so the following question arises : if we need to wait for november for our comprehensive assessment, what happens in the meantime? during the intervening period, we need to rely on our communication about the economic and policy outlook through remarks like these, and its transmission to market developments, the real economy and wage and price setting behaviour, via market participants ’ expectations. that process, in turn, relies on the underlying macro and market institutional framework. essential to maintaining a credible and stable institutional framework within which the bank ’ s monetary policy can operate effectively are : clearly defined responsibilities ; clearly identified objectives ; and respect for institutional independence. in that context, the treasury ’ s announcement of a clear timetable for the clarification of its new fiscal rules, as well as its preparedness to submit its policy plans to the independent, external scrutiny of the office for budget responsibility is to be welcomed. these considerations also point to the importance of distinguishing between the bank ’ s financial stability operation implemented yesterday, and the bank ’ s conduct of monetary policy by the mpc. i sought to emphasise that distinction earlier. so to conclude, let me sum up by describing where we stand. i speak here as an individual. i do not represent the views of the mpc as a whole. and, of course, my assessment this evening is conditional on the situation as it stands today. we live in rapidly moving times. as events unfold, assessments need to be updated. but, at present, on the basis of the fiscal easing announced last week, the macroeconomic policy environment looks set to rebalance. taken in conjunction with the macroeconomic impact of ensuing market developments, it is hard to avoid the conclusion that the fiscal easing announced last week will prompt a significant and necessary monetary policy response in november. the views expressed in this speech are not necessarily those of the bank of england or the monetary policy committee. i would particularly like to thank saba alam, bob hills and jack meaning for their help in

managing machines : the governance of artificial intelligence speech given by james proudman, executive director of uk deposit takers supervision fca conference on governance in banking 4 june 2019 i am very grateful to philip sellar for preparing these remarks, and to sadia arif, jamie barber, jas ellis, magnus falk, orlando fernandez ruiz, anna jernova, carsten jung, tom mutton, lyndon nelson, jennifer nemeth and oliver thew for very helpful advice and comments. all speeches are available online at www. bankofengland. co. uk / publications / pages / speeches / default. aspx introduction consider the well - known story of one big tech company ’ s attempt to use artificial intelligence to improve the efficiency of its staff recruitment. the machine learning system reviewed job applicants ’ cvs with the aim of automating the search for top talent. the company ’ s experimental hiring tool used artificial intelligence to give job candidates scores ranging from one to five stars. within a year, the company realised its new system was not rating candidates for software developer jobs and other technical posts in a gender - neutral way. that is because the computer models were trained to vet applicants by observing patterns in cvs submitted to the company over a 10 - year period. most came from men, a reflection of male dominance across the technology industry. in effect, the company ’ s system taught itself that male candidates were preferable. it penalised cvs that included the word “ women ’ s ” as in “ women ’ s chess club captain ”. and it downgraded graduates of two all - women ’ s colleges. the story is a clear example of how artificial intelligence can produce bad outcomes for all concerned. it also offers a case study for exploring the root causes that lead to bad outcomes - and so in turn offers insights for boards on how to govern the introduction of artificial intelligence. the art of managing technology is an increasingly important strategic issue facing boards, financial services companies included. and since it is a mantra amongst banking regulators that governance failings are the root cause of almost all prudential failures, this is also a topic of increased concern to prudential regulators. in my comments, i will provide a quick overview of the scale of introduction of artificial intelligence in uk financial services ; then make three observations about it, and suggest three principles for governance derived from them. artificial intelligence technological innovation is inevitable and welcome. as the governor noted during this year ’ s uk fin