AI Terms Crib Sheet for Non-Data Scientists

Algorithm

A set of rules or instructions that a computer follows to solve a problem or complete a task. Think of it like a recipe.
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AI (Artificial Intelligence)

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Computer systems that can perform tasks that usually require human intelligence, like learning, problem-solving, and decision-making.

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AI Reliability

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The degree to which an AI system consistently performs accurately and as expected, is trustworthy, and minimizes errors or harmful outcomes.

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AI Reliability Framework

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A structured approach to ensure AI systems consistently perform as intended, are trustworthy, and minimize potential harms. This framework should  encompass five key components:

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• Grounding: Ensuring AI outputs are based on verifiable and accurate information, reducing the risk of hallucinations or fabricated content.
• Explainability: Making the AI's decision-making process transparent and understandable, allowing users to comprehend why specific outputs were generated.
• Consistency: Maintaining stable and predictable AI performance over time, regardless of changes in input data or usage patterns.
• Privacy/Security: Protecting sensitive data and ensuring the AI system adheres to privacy regulations, while also safeguarding against cyber threats and unauthorized access.
• Benchmarking/Currency: Regularly evaluating AI performance against established benchmarks and ensuring the model remains up-to-date with current data and best practices to maintain accuracy and effectiveness.
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Automation

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Using AI or other technologies to perform tasks automatically, with servers. Private out human intervention.

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Benchmarking AI

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Comparing the performance of different AI models to see which one works best for a specific task. Think of it like testing different cars to see which one is fastest or most fuel-efficient.

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Bias (in AI)

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When an AI system makes unfair or skewed decisions because of flaws in the data it was trained on.

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CCPA (California Consumer Privacy Act)

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A California state law that gives consumers more control over the personal information that businesses collect about them. Laws like the CCPA matter for AI because they tell companies how they can (and cannot) use people's data. This ensures AI models are built in a way that protects privacy and follows the rules.

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CDPA (Virginia Consumer Data Protection Act)

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The guidelines in the state of Virginia governing data privacy. These guidelines are often compared to frameworks like GDPR or CCPA. But there are differences. Consult your legal department for more information.

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Chatbots (Sometimes called virtual assistants)

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A computer program designed to simulate conversation with human users. Chatbots are often built for customers or internal tool users who are not data scientists.

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Cloud Computing (for AI)

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Using remote servers over the internet to store, manage, and process AI data and applications, rather than local servers or personal computers.

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COPA (Colorado Privacy Act)

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The guidelines in the state of Colorado governing data privacy. These guidelines are often compared to frameworks like GDPR or CCPA. But there are differences. Consult your legal department for more information.

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Consistent AI

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AI that provides predictable and stable performance over time, regardless of changes in data or usage. It's like a reliable car that always starts and runs smoothly.

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Continuous Improvement

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The process of always getting better. In AI, it means that the AI is always being tuned and improved.

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Continuous Learning

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The act of an AI to continue to learn and adapt to new information to improve speed, accuracy, and outcomes.

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Counterfactual Explanations

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Explanations that tell you what would have to change in the input data to get a different output from the AI. Essentially, "what if" scenarios.

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CPRA (California Privacy Rights Act)

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The guidelines in the state of California governing data privacy. These guidelines are often compared to frameworks like GDPR or CCPA. But there are differences. Consult your legal department for more information.

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CTDPA (Connecticut Data Privacy Act)

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The guidelines in the state of Connecticut governing data privacy. These guidelines are often compared to frameworks like GDPR or CCPA. But there are differences. Consult your legal department for more information.

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Data Analyst

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A professional who focuses on analyzing existing data to extract meaningful insights and trends. They primarily use statistical methods and visualization tools to understand past performance and identify patterns, often answering specific business questions. Data Analysts typically work with structured data and provide reports or dashboards to inform decision-making.

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Data Analytics

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The process of examining raw data to draw conclusions about that information.

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Data Encryption

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Converting data into a secret code to prevent unauthorized access. It's like locking your valuable information in a safe.

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Data Governance

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The overall management of the availability, usability, integrity, and security of data in an enterprise.

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Data Mining

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The process of discovering patterns and insights from large datasets.

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Data Privacy

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Protecting sensitive information from unauthorized access or misuse. This is crucial for building trust with customers and complying with regulations.

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Data Scientist

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A professional who goes beyond analyzing existing data to build predictive models and develop algorithms using machine learning and advanced statistical techniques. They explore complex datasets, including unstructured data, to uncover hidden patterns and create solutions for future predictions or automated decision-making. Data Scientists often design and implement new data processes and tools, and work on more open-ended, research-driven problems.

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Data Security

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Measures taken to protect data from cyber threats, breaches, and unauthorized access. It's like having a strong lock on your valuable information.

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Decision Understanding

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Actively teaching users how and why an AI makes its choices.

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Deep Learning

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A type of AI that uses neural networks with many layers to learn complex patterns from data.

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Delaware Personal Data Privacy Act (DPDPA)

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The guidelines in the state of Delaware governing data privacy. These guidelines are often compared to frameworks like GDPR or CCPA. But there are differences. Consult your legal department for more information.

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Domain-Specific Data

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Data that is very specific to a certain industry, or type of business, like personal finance or cancer treatment.

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DPDP (Digital Personal Data Protection Act)

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India’s law regarding the protection of digital personal data. These guidelines are often compared to frameworks like GDPR or CCPA. But there are differences. Consult your legal department for more information.

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Feedback Loops

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The process of gathering user input, and using that input to improve the AI.

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Florida Digital Bill of Rights (FDBR)

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The guidelines in the state of Florida governing data privacy. These guidelines are often compared to frameworks like GDPR or CCPA. But there are differences. Consult your legal department for more information.

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GDPR (General Data Protection Regulation)

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A European Union law that protects the personal data and privacy of individuals within the EU.

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Generative AI

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AI that can create new content, like text, images, or music, based on what it has learned from existing data.

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Grounded AI

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AI that bases its outputs on verifiable and accurate information, minimizing the risk of "hallucinations" (making up facts). It's like ensuring your AI is using reliable sources.

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Hallucinations (in AI)

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When an AI system generates false or fabricated information and presents it as if it were true.

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HIPAA (Health Insurance Portability and Accountability Act)

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A U.S. federal law that protects the privacy and security of individuals' health information.

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IACDPA (Iowa Consumer Data Protection Act)

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The guidelines in the state of Iowa governing data privacy. These guidelines are often compared to frameworks like GDPR or CCPA. But there are differences. Consult your legal department for more information.

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INCDPA (Indiana Consumer Data Protection Act)

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The guidelines in the state of Indiana governing data privacy. These guidelines are often compared to frameworks like GDPR or CCPA. But there are differences. Consult your legal department for more information.

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ISO 27001

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An international standard for information security management systems.

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Knowledge Graphs

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A way to represent information in a network, where things are connected to other things. This allows AI to understand relationships between data.

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Large Language Models (LLMs)

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A very large AI model designed to understand and generate human-like text.

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Machine Learning (ML)

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A type of AI that allows computers to learn from data without being explicitly programmed.

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Model Drift

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When an AI model's performance declines over time because the data it's processing has changed.

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Model System Messages

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Instructions that are given to an AI model to make it act in a certain way.

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Montana Consumer Data Privacy Act (MTCDPA)

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The guidelines in the state of Montana governing data privacy. These guidelines are often compared to frameworks like GDPR or CCPA. But there are differences. Consult your legal department for more information.

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Natural Language Models

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AI models that are designed to understand and generate human-like language.

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Neural Network

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A computer system modeled after the human brain, used for tasks like image recognition and natural language processing.

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New Jersey Data Privacy Act (NJDPA)

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The guidelines in the state of New Jersey governing data privacy. These guidelines are often compared to frameworks like GDPR or CCPA. But there are differences. Consult your legal department for more information.

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OCPA (Oregon Consumer Privacy Act)

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The guidelines in the state of Oregon governing data privacy. These guidelines are often compared to frameworks like GDPR or CCPA. But there are differences. Consult your legal department for more information.

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Optimization (in AI)

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The process of making an AI system as efficient and effective as possible.

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Output Quality Validation

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Checkpoints that are used to ensure the AI output is usable and correct.

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Partial Dependence Plots (PDPs)

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Visualizations that show how a change in a feature affects the AI output.

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PCI Compliance (Payment Card Industry Compliance)

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Industry standards that businesses must follow when handling credit card information.

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PIPEDA (Personal Information Protection and Electronic Documents Act)

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PIPEDA is the Canadian privacy law that is frequently compared to GDPR and CCPA. It governs the topic of data privacy, and how private-sector companies can collect, use and disclose personal information. Consult your legal team for information on this law when you are conducting business in Canada or with Canadians.

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Predictive AI

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AI systems that use data patterns and algorithms to forecast future outcomes or trends. It's like using past weather data to predict future weather patterns, but applied to business scenarios.

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Private AI Models

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AI models that are run on a company’s private servers, and not on public servers. Private AI models help protect data security and proprietary approaches to problem-solving.

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Prompt Engineering for Predictability

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The act of carefully crafting the input given to the AI, so that the AI gives a desired output.

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Public AI Models

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AI models that are run on public servers.

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Real-Time Processing (in AI)

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AI systems that can process data and provide results instantly or very quickly.

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Retrieval-Augmented Generation (RAG)

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A method for AI to get information from external databases in real time to increase accuracy.

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Scalability (of AI)

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The ability of an AI system to handle increasing amounts of data or users without losing performance.

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Secure AI Development Practices

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Methods used to make sure that the AI is developed in a secure manner.

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TDPSA (Texas Data Privacy and Security Act)

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The guidelines in the state of Texas governing data privacy. These guidelines are often compared to frameworks like GDPR or CCPA. But there are differences. Consult your legal department for more information.

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TIPA (Tennessee Information Protection Act)

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The guidelines in the state of Tennessee governing data privacy. These guidelines are often compared to frameworks like GDPR or CCPA. But there are differences. Consult your legal department for more information.

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Traceability

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The ability to follow the trail of data, and how it was used by the AI.

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Training Data

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The data used to teach an AI model how to perform a task.

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Transparency (in AI)

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Making the AI's decision-making process clear and understandable to users.

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Trust (in AI)

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The confidence that users have in the reliability, accuracy, and ethical behavior of an AI system.

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UCPA (Utah Consumer Privacy Act)

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The guidelines in the state of Utah governing data privacy. These guidelines are often compared to frameworks like GDPR or CCPA. But there are differences. Consult your legal department for more information.

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Unstructured Data

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Data that is not organized in a clear manner. Like text documents, or images.

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XAI (Explainable AI)

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AI systems that provide clear explanations of how they arrive at decisions. This helps users understand and trust the AI's outputs, rather than treating it like a "black box."

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Want more help?

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AI is increasingly a component of virtually every business function and enhances millions of workflows daily. We developed this in-plain-English AI terms crib sheet to help you understand the key terms you may encounter while working with AI solutions. We hope you find it useful.