This is an excerpt from the Forbes Article by Kevin Westcott.
Read the full article here.
Organizations have a myriad of opportunities to create a competitive advantage by using AI. They can use AI to automate engagement and communication with customers to predict customer behaviors. They can develop highly personalized products and services by using advanced analytics and leveraging data from a variety of sources. They can use AI to extract and monetize insights from the vast amounts of customer data generated by digital systems.
But just as companies use AI to create value, they also need to lead the way in implementing the safeguards and checks to ensure AI is used in the most trustworthy and ethical manner. To that end, TMT organizations should take the time to carefully consider the ethical application of AI within their own organizations. According to Deloitte’s Trustworthy AI framework, they can look to the following principles to help mitigate the common risks and challenges related to AI ethics and governance:
Fair and impartial use checks: actively identify biases within their algorithms and data and implement controls to avoid unexpected outcomes
Implementing transparency and explainable AI: be prepared to build algorithms, attributes, and correlations open to inspection
Responsibility and accountability: clearly establish who is responsible and accountable for AI’s output, which can range from the developer and tester to the CIO and CEO
Putting proper security in place: thoroughly consider and address all kinds of risks and then communicate those risks to users
Monitoring for reliability: assess AI algorithms to see if they are producing expected results for each new data set and establish how to handle inconsistencies.
Safeguarding privacy: respect consumer privacy by ensuring data is not leveraged beyond its stated use and allowing customers to opt-in or out of sharing data.
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