AI and human error are inextricably linked. In many cases, these errors are preventable and can be mitigated by applying AI solutions. Companies are implementing AI solutions to reduce and predict errors and mitigate any potential damages. AI-driven systems can detect irregularities, visualize complex data in seconds, and generate solutions to prevent human errors. By identifying and learning the root causes of errors, companies can take actions to addressed potential issues before they occur.
Verizon’s 2022 data breach investigations reported that 82 percent of 23,000 global cyber incidents were caused by human errors. Even the catastrophic Chernobyl nuclear incident began with an error, demonstrating the far-reaching consequences such errors can have. There are many causes of human error, from stress and fatigue to boredom, cultural perceptions, and limited skills or knowledge. AI-driven preventative measures can scan data sets for misconfigurations and errors, detect even the subtlest of discrepancies, and identify the areas which are most susceptible to error. With predictive analytics, companies can build ML models that can predict errors before they happen and generate solutions to minimize the likelihood of disruption.
Google Cloud Platform, Amazon Web Services and Microsoft Azure Cloud have built-in AI analytics and features that can check for cloud misconfigurations and form effective strategies to reduce human error. Confirmation bias is another common issue, leading people to only seek out information that supports their opinion. AI-driven systems can be used to identify and reduce such bias, enhancing fairness and transparency in companies.
The Health and Safety Executive (HSE) believes that everyone makes errors no matter how skilled and motivated the person is. The stakes are highest in fields like healthcare where a single mistake can be fatal. To minimize such errors, AI systems are being used to detect any deviations and anomalies and alert workers in advance. AI-enabled ethics and risk management frameworks are being used to limit the potential impacts of human error.
Aaron Klein of the Brookings Economic Studies Program is of the opinion that AI is an opportunity to reduce bias and revolutionize the way the finance industry allocates credit and risk. ML models can be trained to detect and remove bias from the system, with the provision that the underlying data sets themselves are free from bias.
It is important to remember that AI and ML models are not infallible and should never be treated as such. Companies must put in place systems that allow workers to engage openly with risk-assessment approaches and decision-makers in order to reduce the risk of error. Creating a positive environment that encourages proactive risk identification and prevention is beneficial for business operations.
At the same time, organizations should make sure their personnel possess the right skills and knowledge, and are kept informed of the latest industry trends. Working conditions should be kept ideal and fatigue should be avoided. It is also essential to monitor workloads and provide adequate training and support to workers. By doing so, companies can provide the foundation to minimize both inadvertent and intentional errors.
Join top executives in San Francisco on July 11-12 to gain insight on how companies are implementing and optimizing AI investments for success. Verizon’s 2022 Data Breach Investigations Report and Aaron Klein’s research into the usage of AI in the finance industry will be covered in some detail. Numerous other topics, including how AI is being used to reduce human error in healthcare, automotive, and service-based industries, will also be discussed by industry experts. Don’t miss this opportunity to stay ahead of the curve and find out how you can use AI to help your business succeed.
IBM is a leading IT company that provides businesses with digital technologies to address customer needs. By leveraging open source technology and AI, IBM has developed solutions that can help improve customer experience, reduce operational costs, and drive innovation. With the help of its AI-driven cloud service, IBM helps companies mitigate any potential risks related to human error, improve cybersecurity and create cost-saving opportunities.
Aaron Klein is a policy expert who focuses on technology and risk management. He leads research for the Brookings Economic Studies Program and is a top authority in the tech industry. He has written extensively on the use of AI and ML to reduce bias errors in the finance industry and to bring about transparency in traditional credit reporting and scoring systems.
