PWL Capital July 7, 2016 Advanced Investing Market Research Trolleyology and the Future of Wealth Management A runaway trolley is headed for five workmen who will be killed if it proceeds on its current course. You are standing on a footbridge spanning the tracks, in between the oncoming trolley and the five people. Next to you is a railway workman wearing a large backpack. The only way to save the five people is to push this man off the footbridge and onto the tracks below. The man will die as a result, but his body and backpack will stop the trolley reaching the others. Is it morally acceptable to save the five people by pushing this stranger to his death?1 When posed with this dilemma, most people say that is wrong to kill one person to save five. This is one example of a series of thought experiments philosophers use to understand human morality. If the answer to this question seems obvious then consider this variant. In this version, the runaway trolley is heading down the tracks as before, but you can save the five by hitting a switch that will divert the trolley onto a sidetrack. Unfortunately, there is a single workman on the sidetrack who is oblivious to the danger and will be killed. Is it morally acceptable to hit the switch? In this example, most people are inclined to hit the switch. In the first case individual rights seem to take precedence (“Killing people is an infringement of their basic human rights”). In the second example the utilitarian perspective (“Five die or one dies? No contest.”) takes precedence. We are only beginning to learn how our very complex human moral machinery works, never mind encode that learning into software. Yet, trolleyology has pressing real world applications. As we rely more on artificial intelligence (AI) to help manage large amounts of data and make decisions, to what extent do we allow algorithms to make moral choices for us and whose morality do we use? It is, for example, a small step from trolleyology to self-driving cars2. Do we want our cars to have a utilitarian perspective (even if the one sacrificed for the many is the driver) or do we want it to protect the driver’s right to life, irrespective of the consequences? You can try out your own moral compass for self-driving cars here. Fortunately, investment advisors are more likely to make life and death decisions driving to work than at work. Yet, the investment industry is replete with moral dilemmas and conflicts of interest. Here are some examples with increasing moral complexity: An advisor can recommend two funds to a client, both of which are suitable based on the client’s situation but one fund pays a higher commission to the advisor than the other. An advisor is aware that a retired couple are spending at a rate that may be unsustainable. Does she discuss this with her clients, even if it risks losing their business? The son of an elderly client is in financial difficulties and he is encouraging his mother, who has early signs of Alzheimer’s disease, to help him even at the risk to her own financial security. Does the advisor intervene and on what basis? An advisor who puts their client’s interest first (i.e. adheres to a fiduciary standard) would not be troubled with the first two examples, but it is worth remembering that there is no fiduciary standard in Canada, only a much laxer suitability standard. Using current regulatory standards the advisor in the first example could decide to select the higher payout fund on the basis that both are suitable for the client. Regulatory standards in the investment industry are like the rules of the road for self–driving vehicles: necessary but not sufficient. Regulations cannot replace our moral machinery which, to be effective, requires an understanding of clients. The investment equivalent of self-driving cars are digital advice platforms (aka robo-advisors) that also incorporates artificial intelligence. The debate about whether these platforms can meet fiduciary standards has already started in the United States. Meanwhile in Canada, investment regulators are like an auto industry still debating the merits of seat belts. An optimistic view of the future is that the trajectory of regulation of the investment industry in Canada will follow the US regulators towards a fiduciary standard. Those advisors already adhering to a fiduciary standard, will be able to attend to more clients by using AI and digital tools to take on more mundane tasks such as portfolio rebalancing, performance reporting and cash flow management. Not only will these advisors be more productive and attend to more clients they can focus on using their social skills, empathy and moral judgement to offer a level of service unattainable by current or prospective AI technology. This might not only be good for clients but it might also be good for those advisors who have a long term interest in staying in the industry. This is a trend evident in other industries where, contrary to the popular idea that artificial intelligence leads to higher unemployment, AI is redefining jobs in ways that reduces costs and boosts demand. In the legal profession, for example, the ability of AI software to analyze text and plough through large volumes of legal documents has led to a steady increase in legal clerks as the cost of discovery has fallen and demand has risen. Similarly, in radiology practitioners have been empowered by technology and, in the developing world, increased capacity where skilled specialists are in short supply. But time and tide waits for no man. The investment industry needs to hurry up and reposition itself because it would be a shame if future advisors went to work in cars that had higher sense of moral purpose than themselves. 1 This and the subsequent example are excerpted from Moral tribes: emotion, reason, and the gap between us and them, Joshua D Greene (2013). 2 May 2016 saw the first fatality involving a Tesla while using the self-driving Autopilot feature. Share: Facebook Twitter LinkedIn Email
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