Building data ethics programs in line with environmental, social, and governance values

AI/ML algorithms possess the ability to make and inform significant decisions that may impact individual lives, business, and societies at large. And the benefits of AI/ML come hand in hand with potential risks of a type not previously fully explored by business or society. The public and regulators alike have been quick to scrutinize the predictive processes of this innovative technology. Businesses and organizations who address and implement ethical considerations when developing and using AI systems will be best placed as the legal and regulatory landscape evolves.

To succeed, these governance programs need to create a strong foundation for future development. There needs to be a careful approach to enabling innovation and mitigating risks. Companies will likely need to take into account their environmental, social, and governance (ESG) initiatives when building out data ethics programs. Strong and ethical leadership from the top of a company will have a significant impact on the company’s culture when it comes to the use of AI/ML, and ethical future uptake. Clear lines of reporting, management structures, and ensuring that no aspect of the organization operates in a silo when it comes to the use of AI/ML is key, as are transparency and a critical evaluation of internal practices. As ever, companies will need to monitor developing legal requirements and codes of conduct and will – for some time – likely need to make determinations on AI/ML compliance structures even in circumstances where there are gaps in legislation and regulation.

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