Learn how NXP responsibly supports edge AI, focusing on ethical considerations, privacy, security, and fairness in embedded machine learning applications.
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While some people first consider how to make AI work, NXP goes beyond expectations and asks a question: How can we make AI work in a safe, reliable, and responsible manner? This is where responsible AI takes center stage, collaborating with technology, government, and business leaders to make it a reality.Imagine driving to meet a friend, excited to enjoy your favorite dinner. It has been a while since you last saw them, so you want to look your best, but as you drive, the alarm keeps going off, and you don’t understand why. The alerts you receive come from your vehicle’s Driver Monitoring System (DMS), informing you that even though you are driving well, you are not paying enough attention.What you don’t know is that the reason these scenarios occur is due to the training data used by the AI model that supports the computer vision in the vehicle. For some reason, due to biases in the training data, the AI model misinterprets its real-time inputs, indicating that female drivers are more often classified as ‘distracted due to personal enticement,’ a result of subtle false representations made during training.
Risks of Responsible Edge AI Developmentare not just examples of the risks of using AI to analyze data and make predictions; they are also issues of fairness and robustness in AI/ML systems and how they affect modern life. Just as individuals may be denied financial services due to erroneous biases in training data, edge AI can also lead to discrimination if appropriate measures and risk assessments are not taken. Smart edge plays a crucial role in connecting the physical and digital worlds. Physical AI is a cross-cutting theme of generative AI and robotics that can only be created through edge devices, not just the cloud. Therefore, additional scrutiny of the risks associated with edge AI misalignment is necessary to prevent personal harm and discrimination.When it comes to AI in everyday life, the world is at a critical juncture. In January 2025, a survey by the Boston Consulting Group found that 75% of C-suite executives listed AI as one of their three strategic priorities for 2025. Meanwhile, less than one-third of companies have improved the AI skills of less than a quarter of their employees, highlighting an urgent need for education and awareness.
Edge AI, the Responsible WayWhile many companies are considering how to make AI work in the first place, at NXP, we are going beyond ourselves and asking: How can we make AI work in a safe, reliable, and responsible manner? This is where responsible AI takes center stage, collaborating with technology, government, and business leaders to make it a reality.Responsible AI is not a unique technology or a collection of strategies and best practices. Responsible AI permeates all aspects of technology and non-technology, whether it is machine learning, generative AI and language models, time series data, computer vision, and speech recognition; all types of intelligent software, sensors, and hardware. The risks of AI impact both businesses and individuals – responsible AI must equally represent both sides.
Therefore, a coordinated and comprehensive effort is needed to put responsible AI into practice. At NXP, we have explored this topic through the lens of edge AI support. As a leader in the smart edge space, we have written a white paper on responsible AI support.The goal of this white paper is to make the latest legislation, such as the EU AI Act, more accessible and interpretable, discuss and address the risks of edge AI, highlight the role and responsibilities of SoC suppliers, and outline how NXP contributes to responsible AI through software and tools. For example, in the previously mentioned DMS example, NXP is developing Explainable AI (XAI) software as part of oureIQ Toolkit® that helps detect biases after model training and before deployment. This will help prevent discrimination, ensure robustness, and enable developers to identify risks early and obtain explanations.Edge AI can benefit humanity in many ways; enhancing automation and productivity, safer and more sustainable transportation, and more resource-efficient computing. Responsible support plays a crucial role in ensuring that the advantages of edge AI are maximized while minimizing any potential harm.