Artwork

Contenido proporcionado por Sean MacNutt. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Sean MacNutt o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.
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The Ethics of Training Data

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Manage episode 397639997 series 3518095
Contenido proporcionado por Sean MacNutt. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Sean MacNutt o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.

(00:04) Ethical Implications of AI Training Data

This chapter, I discuss the intricacies of training data in AI technology, starting with its technical foundation and moving into the ethical implications, particularly concerning the sourcing of creative works. I highlight how AI models learn from vast datasets, which often include artists' works without their consent, raising questions about intellectual property rights and fair compensation. We explore the importance of transparency in data sourcing and the potential for establishing policies that protect creators' rights, recognizing the value of their contributions to AI development. Through this conversation, I aim to shed light on the need for equitable practices in the AI industry, ensuring that as technology advances, it does so with respect for the individuals whose work informs it.

(09:04) Ethics in AI Training for Artists' Work

This chapter tackles the ethical concerns surrounding the use of artists' work in the development of AI systems. We examine the notion that artistic creation is genuine labor, deserving of recognition and fair compensation, especially when it contributes to technological advancements. Acknowledging the investment, skill, and unique styles that artists pour into their work, the conversation underscores the disquiet among creators when their output is utilized without payment or proper credit. The chapter highlights the call for transparency in how these artistic contributions are handled and the need for a system that respects the value of creative endeavors within the burgeoning AI industry.

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37 episodios

Artwork
iconCompartir
 
Manage episode 397639997 series 3518095
Contenido proporcionado por Sean MacNutt. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Sean MacNutt o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.

(00:04) Ethical Implications of AI Training Data

This chapter, I discuss the intricacies of training data in AI technology, starting with its technical foundation and moving into the ethical implications, particularly concerning the sourcing of creative works. I highlight how AI models learn from vast datasets, which often include artists' works without their consent, raising questions about intellectual property rights and fair compensation. We explore the importance of transparency in data sourcing and the potential for establishing policies that protect creators' rights, recognizing the value of their contributions to AI development. Through this conversation, I aim to shed light on the need for equitable practices in the AI industry, ensuring that as technology advances, it does so with respect for the individuals whose work informs it.

(09:04) Ethics in AI Training for Artists' Work

This chapter tackles the ethical concerns surrounding the use of artists' work in the development of AI systems. We examine the notion that artistic creation is genuine labor, deserving of recognition and fair compensation, especially when it contributes to technological advancements. Acknowledging the investment, skill, and unique styles that artists pour into their work, the conversation underscores the disquiet among creators when their output is utilized without payment or proper credit. The chapter highlights the call for transparency in how these artistic contributions are handled and the need for a system that respects the value of creative endeavors within the burgeoning AI industry.

Facebook Page

YouTube Channel

Instagram

PayPal

  continue reading

37 episodios

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