Artificial Intelligence: Part 2

AI Safety

AI safety focuses on preventing AI systems from causing harm. This includes technical safety, such as reducing errors and preventing misuse, and social safety, such as avoiding discrimination or economic disruption. AI safety becomes more important as systems become more powerful, more widely used and more autonomous. It asks not only “Can we build it?” but “Can we make it reliable, controlled and beneficial?”

Algorithmic Bias

Algorithmic bias is unfairness or distortion caused by the way an algorithm is designed, trained or used. It may reflect biased data, flawed assumptions or inappropriate goals. For example, a loan-scoring system may disadvantage certain groups if historical data reflects unequal access to credit. Algorithmic bias is important because automated decisions can affect jobs, healthcare, policing, finance and education.

Anthropic

Anthropic is an AI research and technology company founded in 2021 by brother & sister Dario Amodei & Daniela Amodei, best known for developing the Claude family of AI assistants. Anthropic specialises in creating powerful AI systems with a strong emphasis on safety, reliability, transparency and responsible AI development.

Artificial Neural Network

An artificial neural network is a type of AI model loosely inspired by the brain. It is made up of layers of connected artificial “neurons” that process information. Neural networks are especially good at finding patterns in large amounts of data. They are used in image recognition, speech recognition, translation, recommendation systems and generative AI. Despite the name, they are not actual brains and do not think like humans.

ASI – Artificial Super Intelligence

Artificial Super Intelligence (ASI) is a hypothetical future form of AI that would surpass human intelligence in almost every field. Although it does not exist today, many experts believe it could become one of the most powerful technologies ever created, bringing both enormous opportunities and significant risks.