Ethical Use of Artificial Intelligence
Expert-defined terms from the Professional Certificate in Data Ethics for Business Intelligence course at London School of Business and Administration. Free to read, free to share, paired with a globally recognised certification pathway.
Algorithm #
An algorithm is a set of rules or instructions designed to solve a specific prob… #
In the context of artificial intelligence, algorithms are used to process data and make decisions without human intervention. They are essential for machine learning and other AI applications.
Artificial Intelligence (AI) #
Artificial intelligence refers to the simulation of human intelligence in machin… #
AI technologies include machine learning, natural language processing, computer vision, and robotics. AI systems can perform tasks such as learning, problem-solving, and decision-making.
Bias #
Bias in artificial intelligence refers to the systematic errors or inaccuracies… #
Bias can lead to unfair or discriminatory outcomes, particularly in areas like hiring, lending, and criminal justice. Addressing bias is a critical aspect of ethical AI use.
Chatbot #
A chatbot is a computer program designed to simulate conversation with human use… #
Chatbots use natural language processing and machine learning to understand and respond to user queries. They are commonly used in customer service, marketing, and other applications.
Data Ethics #
Data ethics refers to the moral principles and values that govern the collection… #
Ethical data practices ensure that data is handled responsibly, transparently, and in ways that respect individuals' privacy and rights. Data ethics is crucial for building trust in data-driven technologies like AI.
Data Privacy #
Data privacy is the right of individuals to control how their personal informati… #
Protecting data privacy involves implementing measures to safeguard sensitive data from unauthorized access, disclosure, or misuse. Data privacy laws, such as the GDPR, regulate the handling of personal data.
Deep Learning #
Deep learning is a subset of machine learning that uses artificial neural networ… #
Deep learning algorithms can automatically discover patterns and features in large datasets, making them well-suited for tasks like image and speech recognition. Deep learning is a key technology in AI research.
Digital Ethics #
Digital ethics refers to the ethical principles and guidelines that govern the u… #
Digital ethics encompasses issues such as privacy, security, transparency, accountability, and fairness in the design and deployment of digital systems.
Ethical Use of Artificial Intelligence #
The ethical use of artificial intelligence involves ensuring that AI systems are… #
This includes addressing issues like bias, transparency, accountability, and privacy to minimize harm and maximize the benefits of AI technologies.
Explainable AI #
Explainable AI refers to the ability of AI systems to provide clear explanations… #
Explainable AI is crucial for understanding how AI algorithms work, identifying biases or errors, and building trust with users. Explainability is a key requirement for ethical AI use.
Fairness #
Fairness in artificial intelligence refers to the impartiality and lack of discr… #
Ensuring fairness involves identifying and mitigating biases, treating all individuals equitably, and promoting diversity and inclusion in AI development and deployment.
General Data Protection Regulation (GDPR) #
The General Data Protection Regulation (GDPR) is a comprehensive data privacy la… #
The GDPR aims to protect individuals' privacy rights and requires organizations to implement robust data protection measures.
Machine Learning #
Machine learning is a branch of artificial intelligence that enables systems to… #
Machine learning algorithms use statistical techniques to analyze data, identify patterns, and make predictions or decisions. Machine learning is essential for AI applications.
Natural Language Processing (NLP) #
Natural language processing is a subfield of artificial intelligence that focuse… #
NLP technologies allow machines to process and analyze text and speech data, enabling applications like chatbots, language translation, and sentiment analysis.
Personalization #
Personalization in artificial intelligence refers to tailoring products, service… #
Personalization algorithms use data on user interactions, demographics, and past behavior to deliver customized recommendations, content, or offers. Personalization enhances user engagement and satisfaction.
Reinforcement Learning #
Reinforcement learning is a machine learning approach where an agent learns to m… #
Reinforcement learning algorithms aim to maximize long-term rewards by learning optimal strategies through trial and error. Reinforcement learning is used in AI applications like gaming and robotics.
Supervised Learning #
Supervised learning is a machine learning paradigm where algorithms learn from l… #
Supervised learning algorithms are trained on input-output pairs to learn the mapping between input data and target outputs. Supervised learning is used in tasks like image recognition, speech recognition, and predictive analytics.
Transparency #
Transparency in artificial intelligence refers to the openness, clarity, and acc… #
Transparent AI systems provide visibility into how decisions are made, what data is used, and why specific outcomes occur. Transparency is essential for building trust and understanding in AI technologies.
Unsupervised Learning #
Unsupervised learning is a machine learning approach where algorithms learn from… #
Unsupervised learning algorithms do not require labeled training data and can automatically identify clusters or associations in data. Unsupervised learning is used in tasks like anomaly detection and data clustering.
Validation #
Validation in artificial intelligence refers to the process of assessing and con… #
Validation techniques like cross-validation, holdout validation, and A/B testing are used to evaluate AI algorithms, detect errors, and ensure that models generalize well to new data. Validation is critical for building robust and trustworthy AI solutions.