Preventing Harmful AI Bias With Fairness Through Awareness
Artificial intelligence (AI) holds great potential to revolutionize business operations. In fact, according to a study commissioned by my company, 67% of organizations expect their AI and machine learning (ML) use cases to increase over the next year. These technologies offer advantages to increase business efficiencies, generate insights, boost competitive market capabilities and deliver personalized customer experiences.
However, enterprises within highly regulated industries face particular challenges related to AI explainability. Industries such as financial services, insurance and healthcare must use transparent, auditable decision platforms to adhere to strict regulations and compliance standards. Today, there are many AI solutions to automate business processes and decisions, but few provide meaningful explainability. While rife with potential, organizations must never lose sight of the “why” behind automated decisions and predictions.
Today, there are many calls from political organizations and society for greater transparency around AI. In addition, governments and consumers seek greater visibility into the algorithms behind their credit and loan approvals, marketing offers and smart home technologies. Proposed legislation in the United States (the Algorithmic Accountability Act) and globally (the EU's Artificial Intelligence Act) seeks to establish standards for safe, ethical and transparent AI outcomes. However, governments have just begun to find ways to implement regulations on AI since use cases are still evolving and emerging.
