How the composition of Tesla’s autopilot software gives clues to how we should invest, recognizing there are no perfect algorithms for driving or investing.
In this episode you’ll learn:
- Why Americans are afraid of self-driving cars.
- How autonomous automobile software works.
- Why people reject even the best possible algorithms.
- What are examples of safety features and rules of thumb we should build into our investing process.
- Why does everyone think a recession is coming soon even though there is little evidence currently.
Should you trust algorithmic decision making when you invest? Many people don’t trust artificial intelligence to make decisions for them, including trusting a self-driving vehicle to safely navigate traffic for them. In this episode of Money For the Rest of Us, David compares trusting algorithms in investing to driving a Tesla; letting go of control could be the safest and most accurate answer.
Fear of algorithms and the search for the perfect answers
According to the Brookings Institute, only 21% of adult internet users said that they would be inclined to trust a self-driving car. Why such a low percentage? 94% of accidents occur due to human error. Automated vehicles are simply the next logical step towards a safer transportation system, yet the majority of drivers say they would never try one. David explains that the fear of algorithms—of letting AI take control—is rooted in humans’ desire for the perfect answer. We somehow believe that we will have greater adaptability and skills to meet trouble or a problem than algorithms will. The statistics, however, demonstrate a different story. Many algorithms are more accurate than humans—including the algorithms used in automated vehicles such as Tesla. The reality is, we will never find the perfect answer or a perfect solution. Even so, people are scared of letting the best possible answer be the one they trust—algorithmic decision making.
Algorithmic decision making is more trustworthy than human decision making
In circumstances of irreducible uncertainty, we are more likely to choose the method that we believe has the greater capacity to be 100% correct vs. the method that is proven to be correct most of the time. We can’t hold algorithms to the standard of perfection. But we can’t hold ourselves to that standard either. We have to be willing to trust the solution that offers the best answer, the best guardrails, and the best safety mechanisms. Instead of asking whether or not algorithms are perfect, we should be asking if they are better than the status quo—human adaptability and decision making.
Testing has proven that algorithms are consistently more accurate and less biased than humans. They are being used heavily in the medical field, as well as in judiciary systems, recruiting, and mortgage applications. Where humans are often biased, the algorithms used are consistently less so. As long as algorithms provide us with the guardrails we need in driving and investing, they shouldn’t be something to fear or avoid. They should be utilized for the user’s best advantage.
Anxiety is the permeating characteristic of today’s market
Many fear that a recession is coming, but there is little evidence to suggest its looming arrival. David encourages listeners to consider the ways they can build guardrails for themselves to create strong portfolios that can stand the test of a possible recession. While algorithms can certainly help, even a Tesla isn’t completely driven by its own system. The driver has control over how much control the vehicle has. The same concept applies to investing.
Recently, the yield curve in the U.S. went negative. Many were frightened by the event, saying a recession is on its way. While storm clouds may be brewing, it doesn’t mean that a recession is inevitable. In fact, there is little to suggest it will materialize. There are still plenty of job opportunities, credit is easy, and oil remains cheap. We don’t need to be all-reliant upon human predictions. Yes, we need guardrails in our investing strategies, but humans cannot predict the future, and we shouldn’t place our trust in what we cannot accomplish.
Invest within the guardrails and diversify your return-drivers
While there is no perfect answer, there are safety features that we can take advantage of in our investing. Just as Tesla isn’t foolproof against disaster, no investment algorithm will be either. But both have safety mechanisms built in that allow for more accurate actions than the human equivalent.
What can you do as you continue to invest? David suggests understanding return drivers—what an investment’s cash flow is, how is the cash flow expected to grow over time, and what investors are paying for the cashflow. Another guardrail against anxious investing is to diversify your portfolio and cash flow streams. Some of your return drivers will disappoint, but others will do very well—allowing you peace of mind in a balanced portfolio. David explains that having multiple streams of income is similar to planting a garden. No one wants to plant an entire garden with one type of flower. Instead, a variety of flowers are usually planted, allowing for a greater opportunity of success. Be sure to listen to the entire episode for more insight into investing like a Tesla and letting go of anxiety in your investing.
- [0:17] The pervading fear of self-driving cars, despite their safety features.
- [3:33] Why do people fear algorithms and prefer human decision-making?
- [7:45] Algorithmic decision-making has proven to be most accurate.
- [10:10] Automating your investing is like choosing an automated vehicle.
- [12:06] Keeping within the guardrails of investing strategy.
- [15:44] How to diversify your portfolio as an additional guardrail.
- [17:31] Is a recession really looming on the horizon?
- [20:16] Don’t maximize for perfect answers.
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