Artificial intelligence (AI) and predictive analytics have changed the ways in which organizations create products and do business. In the tech industry, AI lets self-driving cars know how to stop at red lights, while in the medical field it is being used to detect and develop vaccines for COVID-19.
Big data is powerful and if you learn to leverage it correctly, it could help ethics and compliance practitioners develop complex risk management procedures and other tasks important to a high-performing ethics and compliance function.
As an ethics & compliance practitioner, AI is becoming more crucial to your daily work in ways you might not think. That hotline or case management platform you use every day is likely built on a foundation of algorithms and data sets that seek to make your job easier and more effective.
It is important that you future-proof your ethics and compliance program. By becoming an expert in the following key areas, you can be an even more effective ethics and compliance leader.
- Artificial Intelligence – Ensuring you know what it is, how it is used and how it is accelerating new technology.
- Leveraging Data – Knowing how and when to use data sets or create them for the first time.
- Practical Applications of AI – Now that you have the data, how can you use it in your E&C efforts?
- Ethical Implications – Knowing the risk areas of implementing AI and machine learning in organizations.
Practical Applications of Artificial Intelligence in Ethics and Compliance
One of the most recognizable uses of artificial intelligence that you may have seen on the web lately is the use of AI chat-bots - those automated pop-ups that are designed to look like a social media message from a friend that pop-up in the corner of your screen. Basic chat-bots are built using a pro-forma response and answer tree: “if user says A, chatbot says B”.
But increasingly, chat-bots are being designed to take all of the user inputs, grade the success of each “conversation” and optimize itself to create the best user experience. Such a chat-bot could be used as part of an organization’s employee portal, to help employees find important policy documents or solve problems without any human interaction.
Risks, Bias and Other Ethical Implications of AI in Ethics and Compliance
While artificial intelligence and machine learning on their surface may seem cold, calculating and without bias, the truth is that with any human designed mechanism, bias and other ethical implications can be just as much of a risk.
AI designed on a biased data set will sure enough produce results that suffer from similar bias. Therefore, it is important to design and build AI-based risk management protocols using the following five guiding principles.
Transparency – Mitigate skepticism of AI processes by maintaining transparency in how AI is used, how it works and providing oversight.
Business Strategy – There needs to be a solid strategy in place that is fully aligned to the organization’s business strategy. These solutions must be incorporated into the risk assessment and mitigation processes.
Trust – The public, as well as employees, must perceive that AI is being developed, used and protected in a way that is safe, secure and fair for all.
Privacy and Security – Organizations must maintain full awareness of the need to keep customer, employee and organizational data secure while deploying AI models.
Values and Social Impact – Are AI and machine learning systems being developed with a core set of values that aligns with corporate, personal and societal values?
Developing AI systems to optimize risk management can have exponentially positive effects if developed with a core set of guiding principles.
Download our latest report, Optimizing Risk Management Using Artificial Intelligence today. This 30-page report takes a deep dive into the practical steps for implementing an AI-based risk management strategy that can help you lead a successful, High-Quality Ethics & Compliance Program.
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