Diagnostic Robotics Responds to NTIA Request for Comments on AI Accountability Policy

Diagnostic Robotics, a leading provider of artificial intelligence and care management solutions for health plans and providers, announced that it has filed a public comment in response to the US Department of Commerce’s National Telecommunications and Information Administration‘s (NTIA) request for expert feedback on how to develop a productive AI accountability ecosystem.

In its comment, Diagnostic Robotics highlights two critical concerns: bias in AI systems and the identification of fake versus real data. The company calls out that while AI holds immense promise in revolutionizing healthcare, algorithms built on biased data risk perpetuating existing disparities in care. Moreover, accurately discerning fake data from real data is crucial in critical domains such as cybersecurity, finance, and healthcare.

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The company also recommends the adoption of ethics guidelines for trustworthy AI, emphasizing transparency, accountability, fairness, privacy and data protection, human oversight and control, and continuous monitoring and improvement.

Diagnostic Robotics has submitted this comment to contribute its expertise and insights in the field of AI-based healthcare solutions. As a company deeply committed to the responsible development and deployment of AI technologies, Diagnostic Robotics aims to ensure that AI systems benefit the entire healthcare industry. By addressing bias and identifying fake versus real data, the company strives to establish robust accountability measures and policies that enhance the reliability and trustworthiness of machine learning systems.

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“We firmly believe that addressing bias and ensuring the authenticity of data are fundamental steps in promoting the accountability of AI systems,” said Dr. Kira Radinsky, CEO of Diagnostic Robotics. “Our comment emphasizes the importance of proactive measures and ethics guidelines for trustworthy AI to ensure effective and equitable outcomes.”

Diagnostic Robotics looks forward to engaging in further discussions and collaborating with relevant stakeholders to drive the development of accountability measures and policies for AI systems.

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