Category: Info
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Explainability (in AI)
Definition Explainability in artificial intelligence (AI) refers to the ability of an AI system or model to make its functioning and decision-making processes understandable to humans. In essence, an explainable AI system can provide clear reasons or justifications for its outputs, allowing people to comprehend how and why a particular decision or prediction was made.…
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Training Data (Artificial Intelligence)
Training data refers to the dataset used to teach an AI or machine learning model how to recognize patterns, make predictions, or take actions. It is the foundational information that the model learns from, enabling it to gradually improve its performance on a given task. In essence, these are example data points (which can be…
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Trust and Compliance: Robotic Advisors for Older Adults in Healthcare
The rapid evolution of healthcare robotics promises to assist an aging population with everyday health needs – from reminding older adults to take medications to providing companionship and advice. As these robotic advisors become more prevalent in elder care, a crucial question arises: will seniors trust these robots, and thus follow their guidance? Trust is…
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AI Ethics
AI Ethics refers to the field of study and set of practices concerned with the moral principles and societal implications governing the development and use of artificial intelligence (AI) technologies. In essence, AI ethics seeks to ensure that AI systems are designed and deployed in ways that are beneficial, fair, and accountable, while minimizing harm…
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AI Alignment
AI Alignment refers to the process of ensuring that artificial intelligence (AI) systems act in accordance with human values, goals, and ethical principles. In essence, an aligned AI is one that reliably does what we intend it to do and behaves in ways that are beneficial (or at least acceptable) to humans, rather than pursuing…
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AI Bias
Definition and Explanation of AI Bias AI Bias, also known as algorithmic bias or machine learning bias, refers to the systematic and unfair prejudices or distortions in the outputs of artificial intelligence systems. In essence, it means an AI system is producing results that are skewed or discriminatory against certain individuals or groups. These biased…
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Artificial Neural Network (ANN)
A neural network (often called an artificial neural network or ANN) is a computing model inspired by the human brain’s network of neurons. It consists of layers of interconnected nodes (“artificial neurons”) that process data and can learn to perform tasks by adjusting the connections (weights) between nodes. Neural networks “learn” from examples rather than…
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Algorithm
An algorithm is a precise, step-by-step procedure for solving a problem or accomplishing a specific task in a finite number of steps. In essence, an algorithm is like a recipe or set of rules: given some input (data or initial conditions), it describes a sequence of operations that leads to a desired output or solution.…
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Artificial Intelligence (AI)
Definition and Scope of AI Artificial Intelligence (AI) broadly refers to the capability of machines or computer programs to perform tasks that normally require human intelligence. In essence, AI involves the simulation of human cognitive processes by machines – enabling them to learn, reason, solve problems, perceive their environment, and make decisions in a way…