Whose Ethics Matter Most and Why
Ethics is a declaration of whose voices, opinions, and values matter
By Dr. Tommy Cooke
Sept 19, 2024
Key Points:
Engage with voices and ideas outside your organization as a litmus test for your ethical priorities
Treat AI ethics frameworks as living documents that are organic and change over time
Strive to think globally - not locally
When we talk about ethics in AI, it’s easy to overlook their underlying complexity. Many organizations treat ethics as a straightforward process: identify some standards, create some policies, and follow compliance. But this approach overlooks a key reality.
This reality is that ethics are subjective. Ethics reflect values, and values differ in context, culture, and stakeholder expectations. This subjectivity can be particularly challenging for organizations operating in diverse industries and global markets.
In AI development and AI use, writing ethics is a declaration. It’s a statement of your organization's beliefs about right and wrong, good and bad. But it’s also a reflection of the values you’re embedding into your AI systems, and the choices you make along the way are critical.
To make things a bit more complicated, one key question often goes unanswered: Whose ethics are we prioritizing? In an increasingly interconnected world, it’s vital to consider whose perspectives are included - and whose might be missed.
Ethics is a Living Framework
At its core, ethics are codified morals. They are an attempt to translate abstract ideas and values into solid standards for behaviour. However, in AI, where the implications of decisions are far-reaching, the ethics landscape is complex and shifting. For example, in Europe, the General Data Protection Regulation (GDPR) provides a comprehensive ethical framework for data use. It is largely individual-centric, focused on protecting the privacy and rights of individuals, requiring transparency and consent for how data is collected and used.
In contrast, the U.S. takes a more business-centric approach to AI ethics. There is less comprehensive regulation, and ethical standards tend to focus on enabling innovation while mitigating harm through self-regulation and sector-specific guidelines. For companies operating in both the US and the EU, this difference creates a challenge: ethical beliefs around privacy, autonomy, and transparency can be misaligned depending on where you are, resulting in inconsistencies in AI governance.
The Subjectivity of Ethics
The subjective nature of ethics means that what is considered ethical in one context might not be viewed the same way elsewhere. For instance, the concept of fairness is interpreted differently across cultural boundaries. In Western countries, fairness in AI often focuses on preventing discrimination based on race, gender, or disability. In contrast, in China or other parts of East Asia, fairness might emphasize collective welfare and societal harmony, even if it means sacrificing some degree of individual privacy.
This raises critical questions for organizations: when you create an ethical framework, whose values are you representing? Which ones do you prioritize, and why? And, just as importantly, whose values are being left out?
As businesses develop AI systems that impact people across borders, the need for a more inclusive and adaptable ethical framework becomes apparent. Without it, companies risk ethical blind spots that can lead to reputational damage, loss of trust, and, in extreme cases, legal action.
Questions for Organizations
So, how can organizations navigate this complex ethical landscape? Here are three essential questions to ask:
Whose voices are included in your ethics frameworks? Consider the diversity of stakeholders impacted by your AI systems, including employees, customers, communities, and global regulators. Do your ethical standards reflect this diversity, or are they shaped by the dominant voices within your organization? It is becoming increasingly clear around the globe that inclusive frameworks tend to be more robust and resilient because they account for a wider range of perspectives.
How often do you revisit your ethical guidelines? Ethics cannot be static. As technology evolves and societal expectations shift, so too must your ethical frameworks. For example, the rise of generative AI and large language models has created new ethical dilemmas around intellectual property, misinformation, and AI autonomy. Organizations should regularly assess whether their ethical guidelines remain relevant and effective.
Are you balancing internal and external values? Often, companies prioritize their internal values—whether it’s innovation, efficiency, or profitability—over external stakeholder concerns. But ethics are about building trust, and to do so, organizations need to align their values with those of the communities they serve.
Practical Advice for Ethical AI Governance
Building an adaptable, inclusive ethical framework doesn’t have to be overwhelming. Here are three practical tips for organizations looking to strengthen their AI ethics:
Engage with external voices. Ethics should be informed by a diversity of perspectives, both internal and external. Regularly engage with stakeholders—including regulators, customers, and community leaders—to ensure that your ethical frameworks are inclusive and reflective of broader societal values.
Make ethics a living document. Ethical standards should be dynamic, not static. Establish a regular process for reviewing and updating your ethics policies to reflect the latest technological developments, regulatory changes, and societal shifts.
Think globally, act locally. Your ethics should be adaptable to different cultural and legal contexts. Strive for a balance between global standards and local values to ensure your AI systems are both responsible and contextually appropriate.
Ethics as a Strategy
In the end, ethics in AI is not just about doing what’s right. It’s about being strategic. In a world where AI systems can influence lives across continents, ethical governance is about building trust, ensuring accountability, and safeguarding the future of your organization. By asking the right questions and adopting a flexible, evolving approach, companies can develop ethical frameworks that are not only reflective of their values but adaptable to a rapidly changing world.