Navin Bishnoi, AVP Data Center Engineering and India Country Manager, Marvell
Navin Bishnoi serves as the AVP, Data Center Engineering and India Country Manager at Marvell Technology. With extensive experience in advanced semiconductor engineering and leadership across global teams, he brings deep expertise in data centers, AI infrastructure, and the future of semiconductor innovation in India and worldwide.
As semiconductor devices grow more intelligent and interconnected in commensurate with the new demands of AI technology, the expectations placed on the hardware have also transformed to include trust and ethics in chip design.
Semiconductors are the foundational technology of modern life. They are embedded in virtually everything we interact with today—from smart phones and appliances in our homes to outdoor digital signage and more. Semiconductors are also used to move, store, process and secure the world’s data, powering the infrastructure of massive computing systems running within hyperscaler, cloud and enterprise data centres. These advanced systems utilize high-performance semiconductors across all elements of the architecture—for compute, connectivity, switching, data security, data storage and more—and are the driving force of innovation in the artificial intelligence (AI) field.
As semiconductor devices grow more intelligent and interconnected, and as the new demands of AI technology require a continual evolution of more powerful and efficient silicon solutions, the expectations placed on the hardware have also transformed to include trust and ethics in chip design. This is emerging as the next frontier in responsible innovation, alongside stronger cybersecurity practices, where the choices made by engineers at the silicon level will determine the reliability and integrity of the digital ecosystems of tomorrow.
Integrating zero-trust at the silicon layer
The need for security at the hardware layer is essential if one wants to design and implement a trustable, ethical framework at the chip level, as hardware-focused security attacks continue to increase and are getting more sophisticated. A recent CISO study reported an 88% increase in hardware security vulnerabilities, largely due to the increase in IoT devices and the release of new enterprise hardware. This makes it imperative for data security to start at the very beginning of the semiconductor design process.
Embedding protection at the hardware level—with techniques like secure boot, hardware-backed encryption and robust isolation—creates a resilient foundation before any software is loaded. Integrating zero-trust principles at the silicon layer can further strengthen this approach by reducing the points of vulnerability. It assumes that no component, user or workload is inherently trustworthy, ensuring semiconductors enforce continuous verification across AI, IoT and cloud deployments. These mechanisms ensure that systems cannot be tampered with and that sensitive data remains protected at all times.
Engineering ethics into the chip
Ethics is often discussed in the context of algorithms or policies; however, it must begin much earlier—within the hardware that powers all AI workloads. Semiconductor engineers should embed capabilities that support traceability, fairness and accountability to ensure that AI systems behave responsibly.
For example, semiconductors can be designed to provide audit trails, enabling stakeholders to investigate and verify how models were trained, what data was used and how outputs were generated. For this, engineers also need to collaborate with other stakeholders like ethicists and policymakers. Rigorous design reviews will help identify risks such as potential bias, misuse scenarios or unintentional opacity. Ensuring transparency at the hardware level will provide the ‘explainability’ that critical sectors like healthcare, finance and public services urgently require. Addressing these concerns early will ensure that modern systems do not cause harm as they scale.
Designing efficiency with a focus on sustainability
AI brings with it significant energy and thermal challenges. Training and deploying advanced AI models not only demands substantially more computational power than traditional data centre systems, but also more advanced connectivity and storage solutions, leading to significant energy and thermal challenges. As a result, maximizing power efficiency becomes both an environmental and economic responsibility.
The semiconductor industry can play a major role in global sustainability efforts by prioritizing power-efficient architectures at the design stage. Advances in chip packaging, thermal management and power regulation can also significantly lower energy requirements and improve operational efficiency. Better thermal design extends hardware life, reduces cooling costs and lowers the total cost of ownership for hyperscalers, cloud service providers, enterprises and research institutions.
Combine engineering design with governance
Technical safeguards need to be supported by strong governance frameworks that emphasize privacy, accountability and transparency. As technologies evolve, the semiconductor ecosystem—semiconductor designers, policymakers, independent industry bodies and academia—must collaborate to address emerging threats, policies, potential biases and ethical issues so that they can be addressed within the product lifecycle. This will ensure that responsible practices are embedded at every stage, starting at architecture design through deployment.
Opening up access to advanced semiconductor technologies will also allow a more diverse set of innovators to participate in building secure and ethical solutions. Open hardware platforms, modular design tools and shared research resources can level the playing field for startups, academic institutions and public-sector innovators. When more voices contribute to shaping technology, the outcomes become more inclusive and context-aware.
Semiconductors power systems that connect all of us and help us make critical decisions in our daily and professional lives. They are also fundamental technologies driving new waves of innovation in AI, cloud and enterprise computing, scientific research and myriad other fields. The future of ‘responsible technology’ will be shaped by what we choose to build into our silicon today—namely, ethics, security and sustainability. And when ‘integrity’ is part of a chip’s core architecture, every layer built upon it becomes more resilient, transparent and trustworthy.
