What is one consequence of bias in computing?

Bias in computing refers to systematic favoritism or prejudice that can creep into algorithms, data sets, or applications, leading to outcomes that are not equitable. When bias exists, it can skew the results produced by algorithms, particularly in areas such as machine learning, natural language processing, and facial recognition. Consequently, this bias can manifest in unfair treatment of certain demographics, resulting in discrimination based on race, gender, socioeconomic status, or other characteristics.

Analyzing the context of other options highlights why they do not represent the correct understanding of bias in computing. Increased efficiency in software development and ensuring reliability or trustworthiness imply a positive enhancement of outcomes, which bias contradicts. A more inclusive user experience would ideally stem from efforts to eliminate bias rather than perpetuate it. Thus, the consequence of bias leading to unfair outcomes and discrimination is a significant concern in the field of computing, affecting the integrity and social responsibility of technological solutions.