Ethics in AI

This data was originally featured in the May 14th, 2025 newsletter found here: INBOX INSIGHTS, May 14, 2025: Strengthening Your Foundation, Ethics in AI

In this week’s Data Diaries, let’s talk about AI ethics. I was teaching at Harvard Business School last week, and one of the students in my guest lecture asked what I thought about the ethics of AI models.

To start, we have to define what ethics even means, generally, then applied to AI. Broadly speaking, there are three branches of ethics, VASTLY oversimplified.

• Deontology: the rules make something good or bad. If you don’t follow the rules, it’s bad. Your intentions don’t matter.
• Virtue: the character of the person doing the thing makes something good or bad. Good things come from good people. Your intentions matter.
• Consequentialism: the ends justify the means. A good outcome is good, even if you broke the rules to do it. Your intentions don’t matter.

The huge challenge with ethics is that ethics is about right and wrong, and right and wrong are mostly moral judgements, which in turn means they are determined by the culture you live in.

These differing philosophical leanings show up in how cultures approach complex ethical brambles like AI. A culture prioritizing consequentialism might find it ethical or at least defensible for an AI company to use vast amounts of data without permission if the societal benefit is large, even if individual rules about consent (a deontological concern) are bypassed.

Conversely, a culture strong on individual rights might lean on deontological principles to restrict such data use, irrespective of potential collective gains.

Let’s take two AI companies as examples of this challenge, DeepSeek and OpenAI. OpenAI is a Western company based in San Francisco, founded on mostly Western values, such as the individual being more important than the collective.

Hangzhou DeepSeek is a Chinese company based in Hangzhou, founded on Chinese and East Asian values, such as the collective being more important than the individual.

If we examine the ethical question of whether an AI company has the right to infringe on individuals’ content to create a model that could cause potential economic harm to those individuals, in Western cultures, this would largely be seen as unethical. Collective harm is frequently subordinated to the rights of the individual, especially in countries like the USA.

In Eastern cultures, the opposite is often true. The expectation is often that the individual subordinates their rights for the good of society, of the collective, especially in countries like Japan, Korea, and China. An AI company taking individual works to produce a product that benefits the society as a whole would be ethical in this situation.

Where this comes to a head is in AI model performance. The best models are trained on the best data (garbage in, garbage out). For AI model makers, whoever has access to the best, highest quality data will win the AI race, all other factors being equal.

Which means that the ethics about how AI models are made (from one perspective, infringing on individual rights and from another perspective, individual rights being less important than the collective) will be driven in part by the company and the culture that company is embedded in – and a determinant in the capability of those models.

So what? What does this mean for you? It means that practically speaking, until legislation exists in Western nations that prohibits the use of intellectual property for AI training without licensing or consent, there are strong incentives for all AI companies to infringe on IP rights.

It also means that in economies and cultures where such legislation exists, they will eventually be at a technological disadvantage; for example, the EU has access to fewer AI tools because of the EU AI Act. This places EU-based companies at a disadvantage compared to their peers in other markets.

Is there an ethical path forward? Again, the answer depends on your culture.

From a collectivist perspective, there are fewer ethical issues with AI models using your data without your express consent because in those cultures, individuals are expected to contribute to the collective good, sometimes at their own expense.

From an individualistic perspective, the ethical approach would be for AI companies (particularly those in Western cultures) to license and compensate intellectual property owners for use of their data in some fashion.

How this all plays out is less clear, and again is based firmly in our respective countries and cultures. However, one thing is clear: the best models will come from the best data, which in turn means that cultures which favor collective benefit over individual rights might have a greater advantage in the AI race – and that could very well determine, down the road, who the big winners in AI are and whose models you use to get your work done.

Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.