Adopting responsible AI practices can help businesses benefit from AI-driven lead generation while minimizing risks and keeping marketing efforts human-centric.
Data collection is at the heart of AI-driven lead generation, as AI algorithms rely on vast amounts of data to refine their predictions and improve their accuracy. However, the collection and use of this data can raise ethical concerns regarding customer privacy. As one way to address this, thewas developed through a consensus-building program to formulate ethical AI principles applicable to various fields, including digital marketing.
Addressing algorithmic biases can be achieved by utilizing datasets that accurately reflect the population, applying data augmentation and data balancing techniques and implementing algorithms that are designed to be equitable and transparent. Transparency measures, such as providing explanations for AI-generated decisions and using audit trails to track changes, can also serve as effective tools to detect and mitigate bias.
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