In the world of modern devices built to make our lives easier, it occasionally gives me pause when I think of how my smartphone knew I would be on the 7:55 flight this morning and subsequently, show me the weather conditions for Quebec City where I would soon be landing. How did it also know to send me a push notification of the best route to take home last night after work just as I was about to leave? The reason is that companies like Apple and Google, along with other platform developers, have added programs known as “bots” into their software. Bots are software programs that are built to perform tasks, which are typically highly repetitive, at a much higher rate than would be possible for a human.1 Contrary to some conspiracy theorists, they are not put onto your phone to spy on you even though sometimes it feels like they might be. Instead they are programmed to observe the patterns of your life and then to offer you help which you may find useful.2
Bots are growing in their uses and applications within our daily lives. They are finding their way into a great many aspects of our interactions and they are becoming more and more intelligent as we gain experience with them. Recently some car dealerships in the U.S. starting using intelligent bots to perform tasks such as answering customer questions that come in over interactive chats on the dealership’s website. Engaging in routine interactions such as booking a customer in for a service appointment is a task that is entirely in the sphere of what a bot can do today. In fact, many customers had no idea at all that they were talking to a program. Advances in natural language processing and buzzword terms like "machine learning" allow increasingly sophisticated communication between humans using artificial intelligence programs. Some exchanges even lead to a few customers to attempt to ask the Bot, named Holly, out on a date during their conversation and to even come into the dealership to meet “Holly”. This of course had to be handled with some tact by Holly’s supervisor.3
Bots are also finding their way into financial services and wealth management. Robo-advisory has been on the rise in the last couple of years. Although still a small segment of the industry, the growth has been nothing short of remarkable. In fact, Business Insider Intelligence reports that robo-advisors will manage around $1 trillion by 2020.4 Robo-advisors are presently able to handle rebalancing of portfolios within programmed parameters. They can also make tactical shifts to take advantage of perceived market advantages. This aspect is however still highly dependent of the input of the programmers and their own ideology on markets given that they provide the parameters under which the robo-advisor platform will be governed. We call this a hybrid human-robo platform.5
The clear advantages in the growth and usage of bots are the cost savings and increased efficiencies for companies that invest in them. Then, use bots strategically to automate low value tasks to create capacity for their employees to focus on more profitable tasks. For instance, imagine a portfolio manager (PM) whose job it was to rebalance the portfolio under her charge daily while also analyzing markets to forecast tactical shifts that offer strategic advantage. She could cede these tasks to a robo-advisor. Comparable to the economic theory of comparative advantage, this can create capacity for the PM to spend more time analyzing the output of trades in the present model based on the parameters that are coded into robo-advisory platform and determine the strengths and weaknesses of those outputs. The partnership between the human PM and the bot could allow for better decisions with future trades. Furthermore, the human PM offers a check and balance over the software. This partnership could then lead to stronger parameters for the program and better results for clients in the future.
The growth and potential applications for bots seems almost limitless at this stage. As exciting as this is, some have theorized on the impact and potential for employment degradation that may occur as more and more jobs get automated. In our next session, we will explore the effects of artificial intelligence on the labor market and the economics of AI in general.
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