The Rise of Financial Machines
The increase of machines in our lives impacts everything from how we buy groceries to have we meet people. So, it may seem only natural that machines also impact our finances. But finance is a unique industry. Finance has the power to affect the world economy, the distribution of power, employment, quality of life, etc. Increased reliance on machines in such a powerful and complex field has plenty of benefits, but it also comes with just as many potential concerns.
Machines in Finance
In the world of finance, even the slightest advantage can mean drastically higher returns. In such a competitive, high-stakes environment, machines provide a way to get or stay ahead. Therefore, it comes as no surprise that the financial industry has often been at the forefront of embacing new technology and is continuing to do so today. Most people are aware that machines have become responsible for things such as making trades or suggesting investments. Case in point, in the last decade, one of the biggest trends in finance has been the emergence of “robo-advisors”.
But machines aren’t only used for day-to-day tasks. Machines are now responsible for high-level responsibilities, such as monitoring the state of the economy. As the capabilities of technology continue to increase, especially in the area of artical intelligence (AI), financial machines require less and less human guidance. Less guidance opens up many possibilities, but it also means less oversight and higher stakes when machines make mistakes.
Benefits of Financial Machines
There is a simple reason why machines have such a strong presence in finance; embracing financial machines comes with a lot of benefits. These benefits have certainly helped major banks or elite investors, but financial machines have also given more people access to financial resources. In recent years, the cost of financial services has been driven down, and trading costs continue to drop, which has opened up investment opportunities to more people.
Machines also can go through more data in minutes that a human could get through in years. In an industry based on interpreting data, the fact that machines can go through so many impacts almost every area of finance, including the number of people that can receive personalized investment advice. Only wealthier individual used to have the luxury of highly personalized advice with complex financial modeling, but the rise of financial machines have made this information incredibly easy to access. As with almost any technology, though, there are plenty of benefits, but also plenty of concerns.
Concerns About Financial Machines
Ever since the tulip mania of the 1630s, humans have been causing bubbles and crashes. In theory, machines should be able to minimize this risk, as well as extreme volatility in general. But that’s not always the case. The way machines “think” is prone to creating crashes. Based on the algorithms machines use, machines may overvalue a commodity, and then, when the algorithm the machines use no longer sees as much value in the asset, suddenly create a massive sell-off.
Financial machine also raise the potential concern of conflicts of interest, specifically those that could lead to more concentrated wealth. Finally, there’s the issue of accountability. Plenty of powerful people get away with questionable decisions, but, at least in theory, they are held responsible by board members or shareholders. When emotionless machines are calling the shots, this poses many potential issues of where the responsibility lies.
Humans Make Machines
One of the most important things to keep in mind with any machine, even AI, is that it was ultimately created by a human. People create the algorithms financial machines use to make decisions and people make mistakes. A perfect example of this was the recent buzz elicited by the Apple credit card when issues of potential gender discrimination came up. Though it was highly unlikely that the discrimination was purposeful, it posed enough of a concern that the New York Department of Financial Services opened an investigation to ascertain whether or not any state laws were broken. The real concern is that the decisions made about credit cars are algorithms kept in a black box, which makes it incredibly difficult to figure out if and when discrimination is taking place. The algorithms upon which financial machines are based can streamline many processes and when used correctly can limit bias but it is important to remember that these algorithms are created by humans, and therefore are not foolproof.
Even though technology in finance poses special concerns, the ultimate takeaway is about the same as the rise of technology in any other industry, it is not innately good or bad. There are plenty of benefits, but there are also plenty of areas of concern that must be approached with caution.
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