A Principled Approach to Responsible AI

You can’t go anywhere these days without running into AI. Turn on the TV, there’s an ad about a new AI agent that will help you make dinner reservations at your favorite local restaurant. Open the news app on your phone, and there are countless articles about the latest and greatest advancements from companies looking to revolutionize and transform the future of AI. Even your dentist is using AI to confirm your next appointment. Some days, it feels downright overwhelming.  

Talent acquisition futurist Matt Alder referred to this as “the weekly AI panic,” smartly pointing out that “while the conversation swings between AI salvation and AI apocalypse, the opportunity gets ignored.” Which is why you have to wonder, what’s the strategy behind all this AI? Is it for the good of humanity, or is it AI for AI’s sake? While AI is advancing at a remarkable pace, for me, the real opportunity lies in building solutions that deliver meaningful value to the end user. But to achieve this, AI must be responsible, and to be responsible, AI needs to be principled, which means it should reflect the organization’s overall mission, values, and ethos.  

Deloitte’s 2025 Global Human Capital Trends Report suggests creating a “human value proposition” for AI, citing the need to reflect the increased collaboration between human and machine. However, that’s only part of the equation, and one that addresses AI after it has been implemented and adopted. We need to get ahead of these technologies so both our workforce and our customers have a clear understanding of who, what, when, where, why, and how.  

Think about it this way: what if AI came with a nutrition label? Something that explained to you what’s in the tool, how it was made, and whether it is good for you. Somewhere on that label, you would also see the information about the brand behind the AI, and that’s where the principles come into play. If you’ve ever had an energy bar, you know what I’m talking about. There are all those little details that explain what the brand stands for: only natural ingredients, Fair Trade Certified, Non-GMO, plant-based.  

Taking a similar approach, with more responsible AI being the goal, principles might include:  

• Human Oversight and Control – The United Kingdom has developed an Artificial Intelligence Playbook for its government, which actually outlines ten principles “to guide the safe, responsible and effective use of AI in government organizations.” The fourth principle is “You have meaningful human control at the right stage.” This principle ensures that humans can validate decisions, intervene if necessary, and maintain control over the models throughout development and deployment. From my perspective as a product leader, people-first is the foundational principle for all responsible AI.  

• Trust and Transparency – While many companies are advancing AI at this point, IBM has been at the forefront of this field for decades. IBM is also an organization with a clear set of AI principles, which include trust and transparency as the basis for its other AI ethics. Within trust and transparency, IBM accounts for explainability, fairness, robustness, transparency, and privacy, all aspects that reflect end-to-end AI governance. For AI to be sustainable, as these technologies advance, trust and transparency must be embedded at every step.  

• Fair and Inclusive – As AI evolves and its limitations become clearer, there is an increased need to reduce bias and promote fairness, aligning with research from Harvard University on ethical and rights-based approaches to AI principles. The authors identified six principles that fit this theme, all of which can be adopted by organizations today. The theme is also all-encompassing, signifying the need for the prevention of bias, representative and high-quality data, fairness, equality, inclusiveness in impact, and inclusiveness in design.  

• Practical and Flexible – Going back to the U.K.’s playbook, it is essential to remember that when it comes to AI, one size doesn’t fit all. This is why the sixth principle states, “You use the right tool for the job.” AWS echoes this sentiment, reminding us that the freedom to find the right model for a specific task needs to be ingrained in any AI strategy to ensure technology investments deliver the desired impact. Otherwise, we risk missing opportunities and underutilizing resources. We cannot jump at every bright, shiny object that hits the market.  

Ultimately, there are countless principles that can serve as the bedrock of a more thoughtful commitment to the use of AI. What matters here is that we take the time, now, to determine what is most important to our organization and put these principles into practice. Intentionality is the responsible way forward.