AI and ETHICS

Turing Test

A test designed to determine whether a machine can exhibit intelligent behavior equivalent to or indistinguishable from that of a human.

Creative Destruction

An economic concept that describes the process by which new innovations lead to the demise of older industries and jobs, especially in the context of AI policy.

The Singularity

A hypothetical future point in time when technological growth becomes uncontrollable and irreversible, resulting in unforeseeable changes to human civilization.

Exponential Growth

A growth pattern where the quantity increases at a rate proportional to its current value, crucial for understanding the potential rapid advancements leading to the singularity.

Symbolic AI

A type of artificial intelligence that uses high-level, human-readable symbols to represent problems and logic.

Subsymbolic AI

A form of AI that operates on a lower level of abstraction such as neural networks, processing information in a way that resembles human brain function.

Supervised Learning

A type of machine learning where the model is trained on labeled data, taking input-output pairs and learning to map inputs to correct outputs.

Neural Network

A computational model inspired by the human brain, consisting of layers of interconnected nodes (neurons) that process information.

Deep Learning

A subset of machine learning that uses large neural networks with many layers to analyze various forms of data.

Backpropagation

An algorithm used in training neural networks that adjusts weights based on the error rate obtained in the previous run, effectively minimizing the output error.

Convolutional Neural Network (CNN)

A specialized type of neural network primarily used for processing structured grid data such as images, inspired by human visual perception.

Unsupervised Learning

A type of machine learning that identifies patterns in data without pre-existing labels, allowing the model to learn the structure of the data.

K-means Algorithm

An unsupervised learning algorithm that partitions a dataset into K distinct clusters by minimizing the distance between data points and their corresponding cluster centroid.

Reinforcement Learning

A type of machine learning where an agent learns to make decisions by taking actions in an environment to maximize cumulative rewards.

Q-table

A table used in reinforcement learning that stores the expected utility of taking a given action in a given state to inform decision-making.

Explore-Exploit Tradeoff

The dilemma in reinforcement learning between exploring new actions to find potentially better rewards and exploiting known actions that yield high rewards.

Nativism-Empiricism Debate

A discussion regarding whether knowledge is innate or acquired through experience, relevant to understanding different approaches in AI development.

Marcus’s Critiques of AI

A series of criticisms made by Gary Marcus regarding the limitations of AI, focusing on supervised learning models and their inability to generalize effectively.

Artificial Intelligence (AI)

The simulation of human intelligence processes by machines, especially computer systems.

Machine Learning

A subset of AI that enables systems to learn and improve from experience without being explicitly programmed.

Natural Language Processing (NLP)

A field of AI that enables machines to understand, interpret, and respond to human language.

AI Ethics

The study of the moral implications and responsibilities of AI development and deployment.

Decision Trees

A model used in machine learning for making decisions based on a set of rules derived from data.

Overfitting

A modeling error in machine learning where a model learns noise in the training data instead of the underlying pattern.

Bias in AI

A systematic error that leads to unfair treatment of certain groups within AI systems.

Generative Adversarial Networks (GANs)

A class of AI algorithms where two networks, the generator and discriminator, compete to produce and evaluate data.

Feature Engineering

The process of using domain knowledge to select, modify, or create features that make machine learning algorithms work better.

Cross-Validation

A technique for assessing how the results of a statistical analysis will generalize to an independent data set.

Artificial Neural Network

A computational model inspired by the way human brains operate, designed to recognize patterns.

Recurrent Neural Networks (RNN)

A class of neural networks where connections between nodes can create cycles, allowing them to maintain a memory of previous inputs.

Transfer Learning

A machine learning technique where a model developed for one task is reused as the starting point for a model on a second task.

Hyperparameters

Parameters whose values are set before the learning process begins, influencing the training of machine learning models.

Gradient Descent

An optimization algorithm used to minimize the cost function in machine learning by iteratively moving towards the steepest descent.

AI Bias

The presence of systematic bias in AI systems, leading to unfair outcomes or decisions.

Data Augmentation

A technique used to artificially expand the size of a dataset by creating modified versions of existing data.

A/B Testing

A method of comparing two versions of a web page or product against each other to determine which one performs better.

Cloud Computing

The delivery of computing services over the internet, enabling faster innovation and flexible resources.

Ethical AI

The body of guidelines and principles that govern the responsible development and use of AI technology.

Algorithm

A set of rules or instructions for solving a problem or completing a task.

Data Science

An interdisciplinary field that uses scientific methods, processes, and algorithms to extract knowledge from structured and unstructured data.

Big Data

Large and complex datasets that traditional data processing applications can't handle efficiently.

Cloud Storage

An online service that allows you to store and manage data on remote servers accessed via the internet.

Internet of Things (IoT)

The network of physical devices connected to the internet, collecting and exchanging data.

Blockchain

A decentralized digital ledger that records transactions across many computers securely.

Augmented Reality (AR)

An interactive experience where real-world environments are enhanced by computer-generated information.

Virtual Reality (VR)

A simulated experience that can mimic or differ from the real world, often involving immersive technology.

Predictive Analytics

The use of statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data.

Chatbot

A software application that simulates human conversation through voice or text interactions.