Building Trustworthy and Explainable AI: Insights from Intel's Ria Cheruvu

Table of Contents

• Introduction
• Ria Cheruvu: An AI Architect at Intel
• The Role of an AI Lead Architect
• The Three Categories of Responsible Abilities
  • Regular Software Development and Team Management
  • Compliance: Critical for Ethical AI
  • Engaging with the Regulatory Landscape
• Explaining Explainable AI
  • Understanding AI Systems
  • Transparency vs. Explainability
  • Interpretability: Going Deeper
• The Importance of Ethical AI
  • Ethical AI as a Social and Technical Development
  • Human-Centered AI: Designing for Users
  • The Value Proposition of Ethical AI
• The Evolving Role of Government in AI
• Creating a Robust Ecosystem for Ethical AI
  • Collaboration Across Stakeholders
  • The Contributions of Academia, Industry, and Non-Profits
• Exciting Aspects of Artificial Intelligence
  • The Fascinating Possibilities of Cognitive Computing
  • Reinforcement Learning and Intuitive Physics
• Ria Cheruvu's Journey in Technology and Writing
  • Influences from Parents, Mentors, and Community
  • A Passion for Writing and Poetry
• Conclusion

Ria Cheruvu: Building Trustworthy AI Solutions for Intel

Ria Cheruvu is an AI lead architect at Intel, where she focuses on developing trustworthy AI solutions for Intel's Internet of Things Engineering Group. With her expertise in security, privacy, machine learning fairness, and responsible AI systems, Ria plays a crucial role in ensuring that AI models are explainable and ethical. In addition to her technical work, Ria is also a published poet and children's book author. Her diverse background and passion for neuroscience contribute to her holistic approach in the AI field.

As an AI lead architect, Ria's purview involves three main categories: regular software development, compliance for ethical AI, and engaging with the regulatory landscape. In terms of software development, Ria oversees a team and manages various products that Align with Intel's vision for AI. She strives to develop technologies that enhance AI models' explainability and meet the needs of developers.

Compliance is another critical aspect of Ria's role. She emphasizes the importance of ensuring ethical AI throughout the entire AI lifecycle. By understanding different segments and potential risks, Ria and her team work towards identifying and implementing ethical practices that align with Intel's values and streamline processes.

Furthermore, Ria actively engages with regulatory bodies and standards organizations, advocating for national and international outlooks on AI ethics. She recognizes the importance of considering the impacts and potential harms of AI systems to mitigate unforeseen consequences. By collaborating with various stakeholders, Ria aims to Shape the regulatory landscape in a way that encourages responsible AI development and usage.

Understanding the concept of explainable AI is key to Ria's work. Explainable AI focuses on comprehending the processes, control mechanisms, and decision-making of AI systems. Ria acknowledges that this is an evolving field, with different terms such as transparency and interpretability often used interchangeably. While transparency highlights understanding the AI system's position and influence, interpretability delves deeper into the model's internal workings. Ria emphasizes the significance of demystifying AI systems, encouraging responsible data science, and promoting best practices from the ground up.

Ethical AI is a central part of Ria's work. She believes that ethical AI encompasses the social and technical development of AI systems. It involves understanding the societal impact, addressing concerns about job displacement, and considering the manipulative power dynamics AI can Create. Ria's focus on human-centered AI aligns with the goal of making AI systems user-friendly, accessible, and aligned with societal values. By capturing user experience, psychology, and various stakeholders' perspectives, Ria strives to ensure AI systems benefit society while addressing concerns.

Ria recognizes the evolving role of the government in driving ethical AI practices. Regulatory bodies provide guidelines and standards that shape the development and deployment of AI technologies. Ria believes that collaboration between government organizations, non-profits, and industry players will lead to formalized guardrails for AI systems in the future. This collaborative ecosystem ensures the development of AI technologies that align with ethical principles and mitigate potential harms.

In building a robust ecosystem for ethical AI, Ria emphasizes the importance of collaboration across academia, industry, and non-profit organizations. Each stakeholder brings valuable insights and perspectives to the table. Academia contributes with critical analysis and pushing the state of the art. Industry helps implement AI technologies and provides real-world applications. Non-profits and consortiums advocate for ethical guidelines, ensuring AI technologies align with societal expectations. Collaboration and knowledge-sharing among these stakeholders foster innovation and responsible AI practices.

Looking ahead, Ria is excited about cognitive computing, graph neural networks, and physics-Based modeling. Cognitive computing aims to provide AI models with access to databases of scenarios and knowledge, enabling more Context-aware decision-making. Graph neural networks offer greater control and explainability in AI models, potentially reducing reliance on black-box approaches. Physics-based modeling aims to imbue AI systems with intuitive physics reasoning, enabling them to understand complex physical interactions. Ria believes these advancements have the potential to revolutionize AI and make it more interpretable, reliable, and aligned with human understanding.

Despite her dedicated focus on AI, Ria expresses her passion for writing and poetry. Inspired by her parents and mentors, Ria has honed her skills as a Writer alongside her technical expertise. She believes that poetry offers a beautiful medium to express emotions and appreciate life's beauty. Writing allows her to balance the challenges of working in ethical AI and explore deeper philosophical questions surrounding human-AI distinctions and the future of technology.

In conclusion, Ria Cheruvu's journey in technology, passion for ethical AI, and writing skills make her a remarkable AI lead architect at Intel. Her relentless pursuit of trustworthy AI solutions and collaboration with diverse stakeholders contribute to the development of responsible and explainable AI systems. Ria's multidimensional approach to AI, combining technical expertise with philosophical insights, ensures she remains at the forefront of the AI industry.