Supportsoft Glossary

AI Ethics and Responsible Artificial Intelligence Practices

AI ethics refers to the responsibility of developing and implementing AI systems in a responsible, transparent and fair manner. Due to the influence of increasing reliance on AI to inform business decisions, interact with customers and execute operational processes, ethical considerations for AI systems today are no longer optional; instead, they are necessary.

Responsible AI includes topics such as data privacy, bias, transparency, accountability and security. AI systems learn from historical data, which can include unintentional bias within the data set, and can perpetuate those biases if they do not have appropriate oversight. Therefore, having frameworks for ethical AI allows organisations to identify and monitor the potential risks associated with AI bias and mitigate their risk of occurring.

Data protection is a high priority for ethical AI due to the fact that many AI applications are designed to use sensitive information that belongs to customers and the business; ensuring the compliance of these applications with data privacy regulations is key for ethical AI.

Ethical AI in the business environment also includes maintaining human oversight of ethical decisions; therefore, organisations must not rely on automated decision-making systems to dictate significant business decisions (such as hiring or credit approval or customer profiling). A strategy of establishing governance and explainable models, as well as audit mechanisms, will foster trust in organisations with their stakeholders.

Adopting ethical AI practices protects the brand, decreases the risk of operational/business issues, and increases customer confidence.