What Ethical Considerations Arise When Compensating an AI Model More Than a Human Being?

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Designers working on Aitana's images at the agency. The Clueless Agency

In today’s rapidly evolving technological landscape, the integration of artificial intelligence (AI) into various industries has raised complex ethical considerations, particularly regarding compensation disparities between AI models and human workers. As AI technology continues to advance and play an increasingly prominent role in the workforce, it is essential to critically examine the ethical implications of compensating AI models more than human beings.

The facts

compensating an AI model more than a human being raises complex ethical dilemmas related to human dignity, fairness, employment impact, accountability, the value of human labour, and the ethical treatment of AI.

The unveiling of Aitana, Spain’s inaugural AI model, earning a monthly income of up to €10,000, is the latest issue of AI dominance and has sparked a profound debate regarding the transformative impact of artificial intelligence (AI) on various facets of society.

Rubén Cruz, the designer and founder of the agency The Clueless, revealed that he created Aitana during a challenging period when he faced a scarcity of clients.

“We started analysing how we were working and realised that many projects were being put on hold or cancelled due to problems beyond our control. Often it was the fault of the influencer or model and not due to design issues,” Cruz told Euronews.

Aitana’s emergence underscores the rapid advancements in AI technology and raises critical questions about its implications for the future of work and the ethical considerations surrounding AI development.

The arguments

Proponents argue that Aitana represents a groundbreaking achievement in AI innovation, showcasing its potential to revolutionise industries and generate substantial economic opportunities.

Her ability to earn a significant income highlights the potential for AI models to augment human capabilities and contribute to economic growth and prosperity.

They emphasise that AI models can often perform tasks faster and more accurately than human beings, leading to increased productivity and efficiency in various industries. This efficiency can result in cost savings for businesses and improved overall performance.

AI models can be also scaled up or down rapidly to meet fluctuating demand, providing flexibility and agility in operations. This scalability allows businesses to adapt to changing market conditions more effectively and efficiently.

AI models can consistently perform tasks without succumbing to fatigue, emotions, or human error. This reliability ensures a higher level of consistency in output, which can be crucial in industries requiring precision and reliability, such as manufacturing and data analysis.

However, opponents contend that Aitana’s ascent raises ethical concerns regarding the commodification of AI entities and the displacement of human workers. They argue that the proliferation of AI models in the workforce may exacerbate unemployment and income inequality, posing significant challenges to societal well-being and equity.

Furthermore, compensating AI models more than human workers raises ethical questions about the value and dignity of human labour. It may undermine the societal recognition of human contributions and diminish the sense of purpose and fulfilment derived from work.

Additionally, AI models lack the empathy, creativity, and intuition that human beings possess, making them less suitable for tasks requiring emotional intelligence or nuanced decision-making.

This loss of human touch can lead to a decline in customer satisfaction and quality of service in certain industries, such as healthcare and customer support.

Overreliance on AI models may hinder opportunities for skills development and human capital investment. Investing in human workers promotes economic growth and fosters innovation, creativity, and adaptability, which are essential for long-term sustainability and competitiveness.

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