Part 3 – AI in Action
Artificial Intelligence is not a distant concept; it’s integrated into many aspects of our daily lives, often enhancing convenience and efficiency.
Where you use AI perhaps without realising it
• Streaming Services: Platforms like Netflix and Spotify analyse your viewing or listening habits to recommend content tailored to your preferences. By examining the genres, actors, or artists you favour, AI suggests new shows or songs you might enjoy.
• Voice Assistants: Devices such as Amazon’s Alexa, Apple’s Siri, or Google Assistant interpret and respond to voice commands. They can set reminders, answer queries, or control smart home devices, all through natural language processing.
• Email Spam Filters: Email services utilise AI to differentiate between legitimate messages and potential spam. By analysing email content and sender information, these filters keep unwanted messages out of your inbox.
AI behind the scenes
• Healthcare: AI aids in diagnosing diseases by analysing medical images, predicting patient outcomes, and personalising treatment plans. For instance, AI algorithms can detect anomalies in X-rays or MRIs, assisting doctors in early diagnosis.
• Finance: Banks and financial institutions use AI to monitor transactions for unusual activity, helping to prevent fraud. Additionally, AI analyses market trends to inform investment strategies and manage risks.
• Retail: Online retailers employ AI to recommend products based on your browsing history and purchase patterns. This personalisation enhances the shopping experience and can increase customer satisfaction.
The Limits of AI
While AI offers remarkable capabilities, it’s essential to recognise its boundaries:
• Lack of True Understanding: AI processes data and identifies patterns but doesn’t possess consciousness or genuine comprehension.
• Dependence on Data Quality: AI’s effectiveness relies on the quality and quantity of data it’s trained on. Inaccurate or biased data can lead to flawed outcomes.
• Ethical Considerations: AI can inadvertently perpetuate biases present in its training data, leading to unfair or discriminatory practices if not carefully managed.
Understanding these limitations is crucial for the responsible and effective application of AI.
