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Matthew Lim's AI Innovation Story: AI Search, The Invisible Risks
By Matthew Lim, AI expert and director of the Korean Association of AI Management (Former Head of Digital Strategy Research at Shinhan DS)
Over the past decade, artificial intelligence (AI) technology has rapidly transformed daily life.
In particular, AI has brought revolutionary changes to the field of information retrieval, fundamentally altering how we search for and consume information. As of 2025, AI search has evolved from being a mere assistive tool to becoming a primary means of obtaining information. However, like any significant advancement, the rise of AI-powered search comes with its own set of challenges and concerns.
◇ The New Wave of AI Search
Today's AI search offers an experience that transcends traditional keyword-based searches. Major search engines like Google, Bing, and Naver employ sophisticated AI algorithms and natural language processing to accurately understand user intent and provide contextually relevant results.
For instance, OpenAI's ChatGPT integrates real-time web search capabilities, delivering answers alongside related website links. Google offers its AI Overview feature to summarize information, while platforms like Perplexity aggregate and analyze data from the internet and databases to improve the accuracy of their responses.
Moreover, AI search services are increasingly embracing multimodal capabilities—processing diverse content types such as text, images, videos, and audio. These innovations enhance user interactions by offering versatile solutions, such as searching for recipes using food photos or identifying songs through humming.
However, these groundbreaking advancements come with significant challenges. The most pressing concern lies in information distortion and bias.
AI search engines rely on extensive datasets for training, but these datasets are often imperfect. They may reflect societal biases or distorted perspectives, leading to skewed search results. For instance, when addressing contentious topics, AI may present one-sided viewpoints instead of a balanced perspective.
Even more troubling is the potential for commercial bias in search outcomes. AI search providers may partner with specific companies or brands, intentionally manipulating search results and responses to serve commercial interests. Examples include promoting specific products during price comparisons or selectively omitting negative reviews of certain items.
Such practices threaten to undermine consumer rights and disrupt fair market competition, raising serious ethical and regulatory concerns.
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| ▲ Aravind Srinivas, co-CEO of Perplexity, delivers a presentation during a joint press conference on AI collaboration between SKT and Perplexity held at SKT Tower in Jung-gu, Seoul, on September 4, 2024. (Yonhap) |
◇ The Lack of Transparency and Ambiguity in Accountability
A significant issue with AI search lies in its "black box" nature, making it difficult for users to understand the basis of specific answers provided by AI. Moreover, when incorrect information is presented, it remains unclear who should be held accountable.
Such lack of transparency complicates the verification of information and increases the risk of false information being perceived as credible.
As modern society grows increasingly reliant on AI search, the appeal of its quick and convenient results may inadvertently erode critical thinking skills. Users risk accepting AI-provided answers at face value, without verification, potentially diminishing their ability to discern the validity of information. A parallel can be drawn to how the advent of automobiles improved mobility but led to a relative decline in human walking ability.
Addressing these challenges requires a multifaceted approach. First, AI search systems must enhance transparency. Users should be informed about the processes that generate search results, as well as any commercial affiliations that may influence outcomes.
Ensuring the diversity and fairness of data used for AI training is equally critical. This requires efforts to eliminate bias and include a variety of perspectives during data collection. Additionally, legal and institutional frameworks must clarify the ethical responsibilities and obligations of AI search providers.
◇ AI Literacy: A New Literacy for the Digital Age
Foremost, users must view AI search as a tool and learn to critically engage with it. This involves neither outright rejection nor blind faith in the technology but rather developing a balanced perspective on its use. Through education, users can cultivate habits of verifying AI search results and cross-referencing information across multiple sources.
AI search has become the new compass in the sea of information. However, this compass does not always point to the right direction. While enjoying the convenience it offers, users must also recognize its limitations and risks.
Technology is never neutral; its value depends on how it is used.
As AI search continues to evolve and integrates more deeply into daily life, retaining user autonomy is paramount. A balanced approach—utilizing the benefits of innovation while maintaining critical thinking—is essential. This represents not only a challenge but also a necessary skill for everyone navigating the AI era.
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