Some examples of narrow AI are
AlphaGo,
self-driving cars,
robot systems used in the medical field, and diagnostic doctors. Narrow AI systems are sometimes dangerous if unreliable. And the behavior that it follows can become inconsistent. It could be difficult for the AI to grasp complex patterns and get to a solution that works reliably in various environments. This "brittleness" can cause it to fail in
unpredictable ways. Narrow AI failures can sometimes have significant consequences. It could for example cause disruptions in the electric grid, damage nuclear power plants, cause global economic problems, and misdirect autonomous vehicles. Simple AI programs have already worked their way into society, oftentimes unnoticed by the public.
Autocorrection for typing,
speech recognition for speech-to-text programs, and vast expansions in the
data science fields are examples. Narrow AI has also been the subject of some controversy, including resulting in unfair prison sentences, discrimination against women in the workplace for hiring, resulting in death via autonomous driving, among other cases. Despite being "narrow" AI,
recommender systems are efficient at predicting user reactions based on their posts, patterns, or trends. For instance,
TikTok's "For You" algorithm can determine a user's interests or preferences in less than an hour. Some other
social media AI systems are used to detect bots that may be involved in propaganda or other potentially malicious activities. == Weak AI versus strong AI ==