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Answering AI’s biggest questions requires an interdisciplinary approach | TechCrunch

Sep 15, 2023 - news.bensbites.co
The article discusses the importance of ethical considerations in the development and application of artificial intelligence (AI). It emphasizes the need for companies to staff their leadership teams with individuals who can understand and address the potential consequences of AI technology, beyond the scope of engineers and computer scientists. The author suggests that AI is a human challenge that requires a cross-disciplinary approach, including perspectives from philosophy, neuroscience, and ethics.

The author proposes the creation of three new roles within companies: a Chief AI and Data Ethicist, a Chief Philosopher Architect, and a Chief Neuroscientist. These roles would address short and long-term issues with AI, existential concerns, and questions of sentience and intelligence within AI models, respectively. The author argues that these roles are necessary to ensure that AI technology is developed and used responsibly, effectively, and ethically.

Key takeaways:

  • AI’s impact is existential and requires an authentic commitment from companies. This includes staffing leadership teams with stakeholders who can adequately navigate the consequences of the technology they’re building.
  • Addressing the challenges of AI requires a cross-disciplinary approach, combining insights from computer science, neuroscience, philosophy, and other fields. This is necessary to tackle the "alignment problem," where AI's unintended consequences can lead to societal issues.
  • The author proposes three new executive roles for companies dealing with AI: a Chief AI and data ethicist, a Chief philosopher architect, and a Chief neuroscientist. These roles would address ethical, existential, and cognitive aspects of AI respectively.
  • Companies need to build a more responsible future where they are trusted stewards of people’s data and where AI-driven innovation is synonymous with good. This involves bringing broad-minded, differing perspectives to the decision-making table to achieve ethical data and AI use.
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