Explaining what learned models predict: In which cases can we trust machine learning models and when is caution required?
In many cases, it is difficult to explain how machine learning models predict. Transparency becomes a big issue when it comes to applying models in several real-life areas. Here, we discuss how we can explain a model’s predictions and how people’s trust in the model depends on its explainability. We also try to understand where certain caution is required. AI-based products and services are increasingly prevalent for decision making in a wide range of domains. Machine learning models predict decisions based on patterns from data. When the complexity and amount of data grows, it becomes harder to explain those predictions. Without proper explainability of the result, these models may lose trust and credibility, especially when using it in some high-stakes decision-making. In such cases, it is also important to be cautious. Cyber attacks to access confidential data or the unpredictable nature of models may result in unexpected outcomes.
Can Computers Think?
The question that drives all artificial intelligence has been discussed, debated, and disputed for an eon. This article will discuss some famous experiments regarding computer intelligence. It will differentiate between human intelligence and artificial intelligence. It will also provide some explanation regarding what consciousness is and if it is attainable by machines. The intangible idea regarding whether a computer or a machine can think has always perplexed the greatest scientific minds\[4\]. Yet, we don’t have any clear answer. Deep learning neural networks have already exceeded human performance in terms of object recognition and pattern matching\[12\]. But intelligence is not all about pattern recognition. It is more about understanding and modeling the world around us, problem-solving, creating new understanding as we learn more about the world\[11\]. In this article, we’ll briefly explore the idea of whether computers have the ability to think and if they can think like a human.