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The Urgent Need to Address Existing AI Risks

Artificial Intelligence (AI), while promising numerous advancements, also harbors substantial risks to individuals in our increasingly automated world. The rapid integration of AI systems into various aspects of daily life has introduced vulnerabilities that can have immediate, real-world consequences for people. From AI-based decisions affecting medical diagnoses and loan approvals to biased algorithmic hiring processes and even the potential denial of essential services, the reach of AI-induced harm extends broadly. These issues raise crucial concerns about the well-being and rights of individuals, especially those from marginalized communities, who may bear the brunt of these risks. Hence, this MIT Technology Review article highlights the importance of focusing on the AI risks that already exist.

The article begins by suggesting that while the concept of AI existential risk or “x-risk”, is often discussed and highly debated, the real and immediate harms caused by existing AI systems demand more attention. The article suggests that current AI applications, such as systems erroneously identifying individuals as criminals or malfunctioning self-driving cars, already pose lethal dangers to people. According to the article, the focus should shift from hypothetical existential threats to addressing tangible and demonstrated AI risks. The article suggests that instead of solely concentrating on preventing AI systems that could potentially end humanity, practical steps should be taken to protect individuals from the immediate risks of AI, especially the marginalized and vulnerable. Lastly, the article highlights that these concerns extend beyond academic and industry circles, emphasizing the need for broader public awareness and action in the pursuit of algorithmic justice.

Recognizing and addressing existing AI risks is paramount to ensuring a just and equitable future. The preceding text highlights the issue and elaborates on some steps that can be taken in this pursuit.

MIT PE Artificial Intelligence and Machine Learning

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