When tragedy strikes, many of us turn to Google for quick updates. After the recent Air India Flight 171 crash, however, Google’s new AI Overview tool made a glaring error: it insisted the aircraft was an Airbus A330, when in fact it was a Boeing 787. This high-profile mistake highlights AI’s limits and the risks of relying on it in life-and-death situations.
The Human Toll and a Surge in Searches
More than 200 passengers and crew perished when Flight 171 went down shortly after takeoff from Ahmedabad. Naturally, search traffic for “Air India crash” soared—but instead of clarifying events, Google’s AI snippets spread fresh confusion. Some summaries blamed Airbus, others pointed to Boeing, and a few strangely mentioned both manufacturers in the same breath.
Why AI “Hallucinates“
These inaccuracies aren’t intentional; they stem from how large language models work. By weaving together fragments from hundreds of news articles—many of which compare Airbus and Boeing—the AI has no way to verify facts. It simply stitches every reference into one narrative, whether it belongs there or not.
Disclaimers vs. User Trust
Google does include a brief disclaimer—“AI answers may include mistakes”—but it’s tucked under the main text and easy to miss. In a popular Reddit thread, users noted that submitting the same query twice produced two completely different accounts of the crash. That inconsistency shows the non-deterministic nature of generative AI: ask once, get one story; ask again, get another.
Real-World Consequences
For the families of the victims and industry observers alike, mislabeling Flight 171 as an Airbus incident has real stakes. Airbus could face unwarranted blame, while Boeing—already under scrutiny after past software issues—might dodge criticism. Either way, the public ends up with a distorted understanding of what really happened.
Beyond Algorithms: The Need for Human Judgment
This episode underscores a basic truth: AI can churn out summaries, but it can’t weigh credibility the way a human fact-checker does. Until these systems learn to cross-reference and prioritize reliable sources, we risk letting misinformation take root.