Strategies For Avoiding Losses From AI Development

The term herd instinct refers to a phenomenon where people join groups and follow the actions of others under the assumption that other individuals have already done their research and know what they’re doing.

The herd instinct is especially prevalent in the financial sector, where investors follow what they perceive other investors are doing rather than relying on their own analysis. Option Alpha. “Herd Mentality”

The herd is always trying to sniff out the “next big thing.” Right now, one of those “next big things” is AI. Artificial intelligence (AI) is everywhere. From algorithms curating social media feeds to personal assistants on smartphones and home devices, AI has become part of everyday life for millions worldwide.

While companies and investors are geared to jump headfirst into this perceived next gold rush, many unknowns, and dangers make predicting the probability of success daunting. Many companies and investors may simply be unprepared for the potential risks – known and unknown – of AI itself and AI as an investment asset.

In terms of unpredictability, in 2017, Facebook raised alarms on social media when two of its AI chatbots, Bob and Alice, started conversing with each other in a language only known to the bots. What were these bots talking about? Nobody knew.

AI is an uncertain and risky frontier.

In a recent article, author Hafiz Sheikh Adnan Ahmed identified the principal business risks of AI:

  • Transparency and Accountability – Unlike humans, AI systems lack the ability to make judgments or understand the context of the environment in which they are deployed. Another important issue with AI systems is trust. As an emerging technology, the lack of adequate understanding of AI could potentially give rise to trust and accountability issues with AI systems.
  • Data Privacy – A major risk involved concerning data privacy invasion is the ability of attackers to infer the data set used to train the model, thereby compromising data privacy.
  • Data Quality and Availability – Poor and incomplete data could result in erroneous predictions or a failure to achieve the intended objectives.
  • Governance and Compliance – A major risk that AI systems face is a lack of governance, compliance, and regulatory requirements, which means AIs usage, monitoring, and potential applicability of AI will remain limited.
  • Unclear Legal Responsibility – Another potential risk of AI is the question of legal responsibility. If AI systems are designed with ambiguous algorithms, who is legally responsible for the system’s outcome – the organization, the programmer, or the system? This risk is not theoretical. In 2018, a self-driving car hit and killed a pedestrian. In that case, the car’s human backup driver was not paying attention and was held responsible when the AI system failed.

Ahmed, H. S. A. (2022, March 9). The Business Risk Posed by Artificial Intelligence.

The risks of AI development and implementation in business and personal use can be significant and overwhelming. Diving headfirst and ignoring the warnings of AI can be devastating financially for corporations and their investors.

​​Like Blockbuster, which ignored the warnings of the risks to its business by streaming, companies ignoring the warnings of AI could go the way of Blockbuster. In other words – extinction.

While the herd chases the next big thing like AI, seasoned and smart investors gravitate towards assets that are not only insulated from the herd but offer something AI cannot offer – predictability.

Herd investors may think they’re going against the grain by betting on something considered on the cutting edge, like AI, but they’re just doing what everyone else is doing. It’s not the herd investors but the seasoned and savvy investors who go against the grain and thrive from doing so.

Ultra-high-net-worth investors/individuals (UHNWIs) avoid the chaos and unpredictability of Wall Street in favor of alternative assets insulated from herd behavior with a track record of success and predictability. By investing in private alternative assets like commercial real estate (CRE) and investments in private companies (i.e., private equity), smart investors can mitigate risks by limiting unpredictability and chaos, as exhibited in an investment like AI and AI itself.

Private investments like CRE and investments in established companies are conducive to number crunching and analysis. This allows smart investors to focus on important factors such as analytics, math, supply, demand, income, and macroeconomic factors like employment instead of abstract elements such as buzz, hype, and the fear of missing out (FOMO) that plague the herd and cloud sound investment judgment.

Avoid investment losses by avoiding the AI herd. Stick to tried and true alternative assets insulated from broader market volatility, offering consistency, reliability, and predictability to create and grow wealth.