Stop Hiding Behind Your Algorithm

As our lives move further into the digital age, more and more of our interactions are taking place online. Consciously or unconsciously, we are trusting algorithms to handle these interactions.

Algorithms are taking over making decisions previously made by humans – everything from what news we see, to job listings we see, to our eligibility for loans. But who is responsible when the algorithm makes a mistake? The programmer who wrote the code? The company that uses the algorithm? The leaders who rely on the algorithm’s decisions?

The pace of change has resulted in some unanswered questions, such as the ethics and responsibility for the decisions made by algorithms.

Hiding in Plain Sight

We’ve already seen some who have attempted to hide behind the algorithms, using them as a shield against public scrutiny. By using algorithms instead of people to automate the decision-making, these organizations believe they can avoid responsibility for any negative outcomes. If (when) something goes wrong, they can simply say that the algorithm made the wrong decision, not them.

For example, when Lufthansa’s competitor, Air Berlin, went out of business, fares shot up 30%. They attempted to pass off the issue by denying it changed its pricing methods. Lufthansa argued that its fully automated booking system was simply responding to a spike in demand following the Air Berlin collapse and displaying higher average prices as a result. They attempted to hide behind the algorithm.

Germany’s Federal Cartel Office (FCO), the country’s competitive watchdog, isn’t buying the excuse and has an investigation underway.

This is the start of a troubling trend and one that we need to be aware of as we move further into the digital age.

What is an Algorithm?

An algorithm is a set of unambiguous instructions for solving a problem or accomplishing a task. They are not random or arbitrary; they must be logical and have a specific purpose.

While we may think of algorithms as related to computers, the steps in any set of instructions is an algorithm. For example, the instructions for an Ikea bookcase are an algorithm.

When it’s related to computers, algorithms can solve mathematical problems, process data, or automate processes and activities.

However, algorithms are not perfect. They can produce incorrect results, especially if the data they are working with is inaccurate or incomplete. Additionally, algorithms can be extremely complex, making them difficult to understand.

History of Algorithm Use by Organizations

The organizational use of algorithms has changed dramatically over time. In the early days of computing, we used algorithms primarily for mathematical or scientific purposes. However, in recent years, algorithms have become an important tool for organizations in a variety of industries.

Algorithms now make decisions about everything from product placement to customer service. Including being used to create personalized experiences for customers such as Amazon’s product recommendations based on past purchase history.

Some are now using algorithms to make decisions about pricing, staffing, and even product development. They are even being used to predicting outcomes. For example, Google has for years been using algorithms to predict the spread of flu outbreaks based on search terms used.

The use of algorithms has revolutionized the way organizations operate. They allow organizations to process large amounts of data quickly and efficiently. They also allow organizations to make better decisions based on data-driven insights. As algorithms continue to evolve, they will become an even more important tool for organizations around the world.

What Could Go Wrong?

As we continue to develop new and more complex algorithms, it becomes increasingly important that we have a clear understanding of what these algorithms are doing. However, this is not always evident. In many cases, we do not fully understand the workings of these new algorithms, and as a result, we don’t understand their implications. This lack of understanding can lead to some dangerous consequences.

One concern is that the algorithms may not consider all the relevant factors, leading to an unethical decision. Another worry is the algorithm may be biased in some way, resulting in an unfair outcome. It is important that we find ways to prevent this from happening and make sure all people are treated equally under the law.

Is It Too Late To Fix?

To enjoy the benefits of future innovations such as the algorithms that enable AI, there is a need to address the issues and challenges of using algorithms in decision-making. They already play a critical role in our lives, but their impact on society is often not transparent. 

How they make decisions is often obscure, and they have the potential for significant unintended consequences. We need to develop a framework for understanding and regulating the use of algorithms. This framework should include principles for transparency, and accountability, as well as mechanisms for oversight and public engagement.

Transparency

There are a few key principles for the transparency of algorithms. First, individuals should be able to understand how it works and what factors it takes into account. Second, the algorithm should be transparently auditable, meaning that it can be checked for accuracy and fairness. Finally, the algorithm should be explicable, meaning that individuals should be able to understand the rationale behind the decisions it makes.

Accountability

Accountability ensures that those responsible for the decisions made by algorithms are held accountable. This helps to ensure that algorithms are used fairly and effectively and that any negative consequences of their use are minimized. Accountability also helps to ensure that users of algorithms can trust the results and that any algorithm-based decisions are fair and unbiased.

Mechanism of Oversight

Mechanisms for oversight include public consultation, disclosure requirements, and independent review bodies. By ensuring that algorithms are transparent and accountable to the public, these mechanisms help to build trust in their use.

Public Engagement

Public engagement ensures that all voices are heard and that everyone has an opportunity to participate in the decision-making process. This principle is especially important when algorithms are used to make decisions that have a significant impact on people’s lives. 

By engaging the public, we can ensure that the algorithm reflects the values and concerns of the community. We can also identify potential problems and find solutions before they become an issue. Public engagement also helps to build trust in algorithms, which can be beneficial for both individuals and organizations.

Conclusion

The pervasiveness of algorithms has led to a number of organizations hiding behind the decisions made by their creations. By doing so, they are attempting to avoid responsibility for the consequences. This is problematic for a number of reasons.

First, it undermines democracy by removing important decisions from public scrutiny. Second, it leads to poorer decision-making as the algorithms are not subject to the same level of scrutiny as human decision-makers. Finally, it allows these organizations to evade accountability for their algorithms’ actions.

Organizations that rely on automated decision-making must be careful not to allow those algorithms to become a crutch. If an organization’s algorithms make bad decisions, it should not be allowed to hide behind the algorithm, but should instead take responsibility.

Despite the risks, the future of business is algorithm-driven. So it’s time to cowboy up and take responsibility for the decisions made by our algorithms.