This analysis summarizes an article published by Aswath Damodaran, a professor at the New York University School of Business, on 30th August 2024, available here.
The author, internationally recognized for the data he periodically publishes on business valuations, faced a problem when a university colleague created a robot capable of emulating his work, taking into account all the books, teaching materials, and videos the author has published on the web.
With a robot on his heels, Damodaran points out that it will be a challenging period for him because, if the robot publishes company valuations that are:
– better than his students’, then there would be no point in him continuing to teach;
– worse than his students’, then it would mean that the he has published low quality research.
So, what can be done to defend against Artificial Intelligence (AI), to avoid losing our jobs?
Given that AI operates well in repetitive, rule-based contexts in a mechanical and predictable way, the author identifies four levers that humans can use to avoid being replaced by a machine.
1. Try to be a “generalist”: over the past few decades, in all disciplines, there has been a continuous and somewhat extreme increase in specialization (in finance, some professions are so esoteric that laypeople have no idea what they are about). There are fewer and fewer talents capable of working in multiple fields, to the point that humanity seems to have lost some of its value over time. For example, not everyone knows that the dome of the Cathedral of Santa Maria del Fiore in Florence was designed in the 1400s by Filippo Brunelleschi, an artist who worked in various disciplines over time, holding the following professions: architect; engineer; sculptor; mathematician; goldsmith. In a world where AI continues to develop, a return to the Renaissance and multi-disciplines would be desirable.
2. Practice bounded story telling: a model may work well in describing a phenomenon, but if it is based on incorrect assumptions, it will eventually fail. Numbers are useful and essential, but to increase their quality, one must go beyond, contextualizing them and trying to understand the reasons behind the results. In business valuations, the author advocates for a quantitative approach integrated with a qualitative one: the machine is fast and precise in extracting data from an Excel sheet but struggles to identify soft data (e.g., quality of management; barriers to entry), an area where humans can excel.
3. Exercise your reasoning muscle: over time, GPS is making us lose our familiarity with paper maps and our sense of direction. Similarly, in many fields, we let algorithms guide us because they are convenient, intuitive, and easy to use. A particularly insidious phenomenon comes from “Google search”, often used to find answers online instead of trying with our reasoning. Thinking about questions, even though it takes time and may sometimes lead us to the wrong answers, is an important training process for our minds, which we are gradually losing.
4. Let your mind wander: an “empty” mind is the birthplace for creativity and new ideas. It is wonderful how humans manage to come up with remarkable discoveries by connecting unrelated events and circumstances. This happens mostly during moments of reflection, detached from everyday work-life. The author found a way to explain the concept of value investing to his students while shoveling snow: he realized how a snowstorm (i.e., a turbulent market) could bring suffering to some people, forced to shovel snow, but joy to others, who enjoy throwing snowballs and building snowmen.
Taking the dog for a walk while leaving the phone at home, can add great value!
In light of the levers mentioned above, the author suggests three strategies that can be implemented, where possible, to outsmart one’s robot:
1. Be secretive about what you do: since the robot learns by using data (websites, YouTube, Facebook, etc.), by making the data unavailable, it is possible to keep the robot at bay. However, there are two caveats to keep in mind. First: if the competition publishes its data, the robot might still be able to imitate you. Second: the robot can perform reverse engineering: it is possible to trace the cause by looking at the effects. For example, a fund manager may not explicitly state her/his investment policy, but if one analyzes the stocks they buy and sell over time, it is possible to determine their investment strategy.
2. Get system protection: in some professions (e.g. notaries in Italy), even if a robot could economically replace a person, the system does not accept this type of action, always requiring the presence of a human being. Trying to channel one’s work into “protected” sectors could be useful to block the robot.
3. Build your moat: in more sophisticated companies, entry barriers are made up of a series of skills and investments that can provide a competitive advantage that is difficult to imitate. The same principle can be applied on a personal level.
In everyday life, think that somewhere there is a robot with your name, trying to imitate you. But think about what truly defines you and makes you unique as a human being: that is your best defense.
