Published Oct 1, 2024

Ethically Sourced Creativity: Shutterstock's Alessandra Sala

Senior director of data science and AI at Shutterstock, Alessandra Sala, shares insights on the company's evolution as a leader in AI model training, exploring the transformative potential of generative AI in redefining creativity while underscoring Shutterstock's ethical practices and the importance of governance for responsible innovation.
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  • Ethical Frameworks

    Alessandra Sala, senior director of data science and AI at Shutterstock, emphasizes the company's commitment to ethical AI practices. She highlights the development of a trust framework with five pillars, focusing on ethically sourced training data and royalty compensation for contributors. This approach not only aligns with ethical standards but also provides a strategic advantage, as Sala notes, "We have been the first in our space to launch ethically sourced data in our trust frameworks that underpins an ethically safe product." 1 2 The framework has set a precedent for other companies in the industry, showcasing the importance of integrating ethical considerations into AI development.

       

    Compensation Models

    Shutterstock's compensation model for contributors is both innovative and complex. Sala explains that the company shares revenue with contributors whose assets are used to train AI models, ensuring fair compensation based on the volume and uniqueness of their contributions. She acknowledges the challenges in attribution, stating, "Attribution is very hard. And at the beginning we didn't even know." 3 4 This model not only supports contributors financially but also enhances the quality and diversity of Shutterstock's creative library, which is crucial for training robust AI models.

       

    AI Standards

    In the realm of AI industry standards, Sala discusses Shutterstock's role in promoting safe and ethical AI practices. The company has amassed a vast collection of creative assets, all reviewed for quality and compliance, setting a benchmark for ethical data sourcing. Sala argues against models based solely on popularity, emphasizing the value of diverse and high-quality content: "We should be able to distribute wealth to everyone, to those that gives us content of quality." 5 6 This commitment to quality and diversity not only strengthens Shutterstock's position in the market but also contributes to the development of more reliable AI models.

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