As corporations increasingly employ artificial intelligence (AI) and machine learning tools to automate labor-intensive tasks such as screening CVs and interviews, they face a compelling need to ensure that these technologies do not engage in what has been termed as “algorithm drift”, leading to improper bias. Legal liabilities or even a tarnished brand reputation could threaten companies that fail to navigate this complexity properly. This information comes from David Walton, chair of Fisher Phillips’ artificial intelligence team. He suggests that employers bear the burden of ensuring the authentication of AI tools to avoid biases within the technological framework.
Reacting to this emerging landscape, Walton particularly underlines the risk of management overlooking the capacity of AI systems to independently “learn” prejudices and diversify bias patterns that could potentially infringe on professional standards and regulations. This “algorithm drift” as he calls it, could engage a company in unwanted legal battles and critically damage its market standing.
Without diligent safeguards in place, AI tools that should be streamlining procedures could inadvertently lead to poor hiring practices and consequent reduction in company reputation. The inherent complexities in AI systems demand businesses to take preventative measures and prove high standards of technological competency to avoid inadvertently fueling bias and prejudice. Find here more about his insights into such potential ramifications of unchecked AI adoption.