Miscommunication of algorithms refers to the incorrect or misleading communication of the design, function, or performance of algorithms. Algorithms are sets of rules or instructions that are used to solve problems or perform specific tasks, and are widely used in fields such as computer science, engineering, and finance.
The importance of accurate communication of algorithms lies in their widespread use and impact. Many algorithms are used to make important decisions or provide information, and if they are not communicated correctly, this can lead to incorrect or biased decisions or results. For example, if an algorithm is designed to identify and prioritize job candidates, but is not communicated accurately, it could result in unfair or biased hiring decisions.
However, there are also potential pitfalls associated with the miscommunication of algorithms. One of the main challenges is that algorithms can be complex and difficult to understand, even for experts in the field. This can make it difficult for non-experts to understand how an algorithm works, and can lead to misunderstandings or incorrect assumptions about its design or performance.
Another potential pitfall is the issue of bias and discrimination. Miscommunication of algorithms can lead to the inclusion of biases or prejudices in the design or function of the algorithm, which can result in unfair or discriminatory outcomes. For example, if an algorithm is used to determine loan approvals, and is not communicated accurately, it could result in discriminatory lending practices.
In summary, accurate communication of algorithms is important because it ensures that these complex systems are understood and used correctly. However, the complexity and potential for bias in algorithms can make accurate communication difficult, and can lead to misunderstandings or unfair outcomes.
Attention to potential threats posed by algorithms that fail to seamlessly work together was raised in 2018 when miscommunicating algorithms caused a fatal self-driving car accident. Such franken-algorithm mishaps continue to be a threat as evidenced by recent stock market glitches.
The ever-growing proliferation of algorithm-driven computing—Facebook alone has billions of algorithms working together—and A.I.-developed algorithms suggest that containing the franken-algorithm threat may prove a challenge.