The Sanskrit slogan Satyameva Jayate, which means “Truth alone triumphs,” assumes fresh meaning in a time when artificial intelligence (AI) is reshaping global narratives. Concerns about data integrity, AI-generated disinformation, and the erosion of truth are growing as countries compete to control the AI space. The question of whether “truth “in AI will ultimately triumph or if we are speeding toward a period of disinformation and social instability emerges when nations place a higher priority on AI supremacy than regulation.
All Bets Are Off in the AI Race
Even the European Union, which has set the standard for AI governance, is now racing to catch up to China and the United States, despite once being a strong supporter of AI safety and regulation. At the recent AI Paris Summit, there was a lot of talk about AI safety, transparency, and ethical AI, but little concrete action. The U.S., UK, and China notably refrained from signing the AI safety declaration, signaling that economic and strategic concerns outweigh ethical considerations. The urgency of the AI race has pushed global guardrails to the back burner, making innovation the primary currency of competition.
Meanwhile, China’s DeepSeek AI model has spooked Western nations, demonstrating that China is rapidly catching up to OpenAI and other leading AI developers. DeepSeek’s breakthrough highlights how the future of AI dominance hinges not just on powerful models but on access to the most comprehensive and accurate datasets. In this high-stakes race, the country or organization with the most truthful, expansive, and representative dataset will ultimately win.
The Dangers of ‘Quick and Dirty’ AI
With countries vying for AI supremacy, many are cutting corners, leading to “quick and dirty” AI. The result? Models that spread disinformation, reinforce biases, and exacerbate societal inequalities. One recent example of this is the viral AI video featuring fabricated appearances of Jewish celebrities condemning Kanye West’s antisemitic remarks.
The video, which appeared authentic to many viewers, falsely depicted figures like Scarlett Johansson and Adam Sandler. Johansson later spoke out, warning that AI poses a ‘far greater threat’ than many realize. The ability to generate hyper-realistic yet entirely fabricated content not only fuels misinformation but also has the potential to enrage populations, incite violence, and disrupt societies. If AI development continues unchecked without strong safeguards, we risk entering an era where fabricated realities will overshadow the truth.
The Need for a ‘TRUE’ Dataset in AI
Given these challenges, the importance of data integrity in AI cannot be overstated. For AI to be truly beneficial and reliable, it must be built upon what we call a ‘TRUE’ dataset:
- T – Transparency: AI datasets must be sourced ethically, with clear documentation on how data is collected and used.
- R – Representativeness: Data must be inclusive and diverse, ensuring that AI models do not inherit biases that skew results.
- U – Updated: AI must continuously learn from fresh, verified data to remain accurate and relevant.
- E – Ethical: AI development must align with ethical guidelines that respect privacy, consent, and fairness.
The Future: Will Truth in AI Prevail?
History has shown that misinformation spreads faster than truth. As the famous adage goes, “A lie can travel halfway around the world before the truth can get its shoes on.” The same applies to AI. Flawed AI models will likely dominate the landscape in the short term, fueling confusion and distrust before robust, truth-driven AI solutions emerge.
However, those who invest in ‘TRUE’ datasets—ones that are transparent, representative, updated, and ethical—will ultimately lead the next AI revolution. The AI battle is not merely about who builds the most powerful model but about who builds the most truthful one. In the end, just as Satyameva Jayate reminds us, only truth will stand the test of time.
The question remains: will AI developers and nations heed this lesson, or will they let short-term gains overshadow long-term credibility? Only time will tell, but one thing is certain – truth in AI is no longer just an ethical ideal; it is a necessity for the future of society itself.
About the Author
Roopa Prabhakar, holds a Master’s degree in Electrical and Computer Engineering and a bachelors in Electronics and Communication Engineering. She has over 20 years of experience in data & analytics and currently serves as a Global Business Insights Leader at Randstad Digital. She specializes in modernizing & migrating legacy technology towards AI-enabled systems, bridging traditional IT roles with AI-powered functions. As an independent researcher, Roopa focuses on gender bias in AI, informed by works from UN Women and the World Economic Forum.
