Can Ethical AI Be More Than a Talking Point?

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3 days ago

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Ethical AI is moving from talk to action as global laws, pledges, and accountability measures reshape how technology is built and deployed.
AI is everywhere in 2025. It writes, designs, predicts, diagnoses, recommends, and increasingly, governs. From smart cities to courtrooms, its decisions are shaping our lives.
But as AI grows more powerful, one question gets louder:
Are we building it responsibly?
Or are we just saying the right things?
This month, the European Union made headlines with the passage of the AI Act, the first major attempt to regulate AI at scale. This sweeping law bans certain uses of AI, such as real-time facial recognition in public spaces and social scoring systems. It also imposes strict rules on high-risk applications like biometric surveillance, recruitment tools, and credit scoring.
Why does this matter? Because it signals that AI governance is moving from voluntary ethics to enforceable law. The EU has set a precedent others may follow, much like it did with GDPR for data privacy.
But here's the catch: regulation is only as effective as its enforcement. Without clear oversight and penalties, even the best laws can fall short. Europe's AI Act is a strong start, but the world is watching how it will be applied.
Across the Atlantic, the United States is facing growing pressure to catch up. In May 2025, Congress held a new round of hearings with major AI players like OpenAI, Meta, Google DeepMind, and Anthropic. Lawmakers are calling for clear standards and transparency.
Several of these companies have signed voluntary AI safety pledges, promising to develop systems responsibly.
Meanwhile, South Korea is exploring a different path. Officials are developing an AI Ethics Certification, a system that would allow companies to prove that their models are fair, transparent, and safe.
This is a smart move. Turning ethics into something measurable and certifiable could help bridge the gap between values and verification. However, the success of this initiative depends on how independent, transparent, and rigorous the certification process is.
Principles Are Easy. Proof Is Hard.
It's worth noting that almost every major AI company today has published a set of ethical principles. Words like trust , safety , accountability , and fairness appear prominently in blog posts and mission statements.
But dig deeper and you'll find the real challenge: How are these principles enforced internally?
Are external audits allowed?
Are impact assessments made public?
Is there a clear process to test and mitigate bias?
When AI Ethics Fails
We've already seen what happens when AI is built without enough attention to fairness or inclusivity.
In 2023, a widely used hospital AI system in the U.S. was found to recommend fewer treatment options to Black patients. The cause? Biased training data that didn't account for structural inequalities in healthcare.
In 2024, generative AI tools sparked criticism for gender and racial bias. When users searched for terms like 'CEO' or 'doctor,' the images generated were overwhelmingly of white men, despite the global diversity of those professions.
These are not one-off glitches. They are symptoms of a deeper issue: AI systems trained on biased data will replicate, and even amplify, that bias at scale.
That's why ethics can't be a box to check after a product launches. It must be embedded from the start.
A New Ethical Frontier: The UAE Leads in the Middle East
Encouragingly, ethical AI leadership is emerging from regions not traditionally known for tech regulation.
The United Arab Emirates is one of them. The UAE's National AI Strategy 2031 places a strong emphasis on fairness, transparency, and inclusivity. This isn't just talk. Institutions like the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) are actively training a new generation of AI researchers with governance and ethics embedded in their education.
This is a critical development. It shows that countries outside the usual power centers, like the U.S. and EU, can shape global norms. The UAE isn't just importing AI innovation; it's helping design how AI should be governed.
Platforms for Global Dialogue
Major events like AI Everything and GITEX GLOBAL, hosted in Dubai, are also evolving. They're no longer just product showcases. They now bring together global experts, policymakers, and ethicists to discuss responsible AI practices, risks, and solutions.
These events are important, not only because they give emerging markets a voice in the AI ethics debate, but because they encourage cross-border collaboration. And that's exactly what AI governance needs.
Why? Because AI systems don't stop at national borders. Facial recognition, large language models, predictive analytics, they all operate across regions. If we don't align on ethics globally, we risk creating fragmented systems with uneven protections.
What Needs to Happen Now
It's clear that we're moving in the right direction, but not fast enough. What's missing is the bridge between principles and practice.
We need:
Not just values, but verification.
Not just pledges, but clear policies.
Not just intentions, but independent audits.
Ethics should be baked into the AI lifecycle, from design to deployment. That means testing for bias before the model goes live, ensuring transparency in how decisions are made, and creating clear channels for redress when systems fail.
AI governance shouldn't slow innovation. It should guide it.
The pace of AI innovation is staggering. Every week brings new tools, new capabilities, and new risks. But alongside that speed is an opportunity: to define the kind of AI future we want.
In 2025, ethical AI should not be a trending topic or a marketing slogan.
It must be the foundation, the baseline.
Because when technology makes decisions about people, those decisions must reflect human values, not just machine logic.
By Rabab Zehra, Executive Editor at TECHx.