3 Ways Companies Can Ethically and Efficiently Develop Generative AI Models

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President Biden meets with AI experts to examine the dangers of AI. Sam Altman and Elon Musk publicly express their concerns. Consulting giant Accenture has become the latest to bet on AI, announcing plans to invest $3 billion in technology and double its dedicated AI staff to 80,000. other consulting companies, Microsoft, Alphabet and Nvidia joining the fray.

Big companies aren't waiting for the bias problem to go away before adopting AI, making it even more urgent to solve one of the biggest challenges facing all major AI models generative. But regulating AI will take time.

Because every AI model is built by humans and trained on human-collected data, it is impossible to fully eliminate bias. Developers should, however, strive to minimize the amount of "real" bias they reproduce in their models.

To understand real-world biases, imagine an AI model trained to determine who is eligible to receive a mortgage. The formation of this model based on the decisions of individual human loan officers - some of whom might implicitly and irrationally avoid granting loans to people of certain races, religions or genders - poses a huge risk of reproducing their actual biases in the result. Event

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The same goes for models intended to mimic the thought processes of doctors, lawyers, human resource managers, and countless other professionals.

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