February 13, 2026 | 04:26 pm
TEMPO.CO, Jakarta - Concrete examples of the dangers of artificial intelligence (AI) bias continue to emerge as adoption of the technology expands across society. Ardi Sutedja, Chair of the Indonesia Cyber Security Forum, said bias in AI emerges when the algorithms or training data used are not neutral. As a result, the outputs generated tend to favor or marginalize certain groups. "The risk is not only individual but also systemic," he said on Wednesday, February 4, 2026.
If used in recruitment, Ardi added, biased algorithms could trigger discrimination against certain applicants. Unfair decisions may also arise if the technology extends into the judicial system. Over the long term, AI bias could reinforce social inequality and hinder national progress.
An article titled AI Bias: 16 Real AI Bias Examples and Mitigation Guide, published on January 8, 2026, on the AI information platform Crescendo, defined AI bias as systematic discrimination resulting from imbalances in data and algorithms. If trained on data reflecting societal prejudices—such as racism or sexism—the digital brain could learn and reproduce those same biases in its decisions or predictions.
Among documented cases of digital bias was an example from the health sector, summarized from research published in the journal Dermis. Several AI models used to diagnose skin cancer, according to the review published on April 22, 2025, were trained on datasets dominated by images of light-skinned patients. When tested on more diverse datasets, detection accuracy for darker skin dropped sharply. As a result, the AI more frequently misclassified malignant lesions as benign in dark-skinned individuals.
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