Name: Identifying and Mitigating Bias in AI Systems
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Identifying and Mitigating Bias in AI Systems

WORKSHOP: Ethics and Bias in AI: Practical Approaches

WORKSHOP OVERVIEW

This Workshop will Provide practical approaches to addressing ethics and bias in AI.

OBJECTIVE: Equip participants with tools and techniques to ensure ethical AI practices

OUTCOME: Participants will implement and evaluate ethical AI frameworks.

Target Audience: AI developers, ethicists, researchers, and policymakers.

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Identifying and Mitigating Bias in AI Systems

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SESSION OVERVIEW

EXPLORE MORE GODA SESSIONS

The Power Demand of AI: Challenges and Solutions

The Future of AI: Innovations and Trends

Open Data for Social Good: Transforming Communities

AI Ethics and Governance: Navigating Challenges

Smart Cities: Building the Urban Future with AI

AI for Climate Action: Tackling Environmental Challenges

Advanced Data Science Techniques: From Theory to Practice

AI and the Future of Work: Preparing for the AI-Driven Economy

AI in Finance: Transforming Financial Services

Open Source AI: Collaborating for Innovation

AI in Healthcare: Revolutionizing Patient Care

Data Privacy and Security in the Age of AI

AI in Education: Personalizing Learning Experiences

AI in Industry 4.0: Driving Manufacturing and Innovation

The Role of AI in Crisis Management

The Intersection of AI and IoT: Creating Intelligent Systems

Panel Discussion: Managing Energy Consumption in Data Centers and AI Model Training

Case Study Presentation: Optimizing Energy Use in AI Operations

Presentation - AI and the Environment: Balancing Innovation with Sustainability

Panel Discussion: The Environmental Impact of AI: Challenges and Mitigation Strategies

Case Study Presentation: AI and Environmental Sustainability

Case Study Presentation and Live Demo: Sustainable AI: Strategies for Reducing Power Consumption

Panel Discussion: Energy-Efficient AI Algorithms and Renewable Energy Integration

Case Study Presentation: "Sustainable AI Practices"

Introduction to Open Data and Workshop Objectives

Data Cleaning and Preprocessing Techniques

Building and Training Machine Learning Models

Model Evaluation and Validation

Introduction to AI Ethics

Techniques for Ensuring Transparency

Case Studies and Real-World Applications

Introduction to AI and Climate Action

AI in Climate Modeling and Prediction

Renewable Energy Optimization with AI

Sustainable Resource Management

Introduction to NLP and Workshop Objectives

Text Preprocessing and Tokenization

Sentiment Analysis and Topic Modeling

Building and Deploying NLP Models

Introduction to Data Visualization and Workshop Objectives

Principles of Effective Data Visualization

Tools and Techniques for AI-Powered Visualizations

Creating Interactive Dashboards

Introduction to AI in Healthcare and Workshop Objectives

AI Applications in Diagnostics and Treatment

Personalized Medicine and AI

Data Privacy and Security in Healthcare AI

Introduction to AI Chatbots and Workshop Objectives

Chatbot Frameworks and Platforms Overview

Natural Language Understanding and Dialogue Management

Building and Deploying Chatbots

Introduction to Deep Learning and Workshop Objectives

Fundamentals of Neural Networks

Convolutional Neural Networks (CNNs)

Recurrent Neural Networks (RNNs)

Introduction to AI in Finance and Workshop Objectives

Predictive Analytics for Financial Markets

AI Techniques for Fraud Detection

Algorithmic Trading with AI

Introduction to Autonomous Systems and Workshop Objectives

Fundamentals of Autonomous Systems

AI Algorithms for Robotics

Applications in Self-Driving Cars and Industrial Robots

Introduction to AI in Cybersecurity and Workshop Objectives

AI-Driven Threat Detection and Prevention

Anomaly Detection in Network Traffic

AI for Incident Response and Mitigation

Introduction to AI and IoT and Workshop Objectives

Overview of IoT Architecture and Components

AI Techniques for IoT Data Analysis

Developing Intelligent IoT Applications

Introduction to AI in Business and Workshop Objectives

AI Applications in Business Analytics

Decision Support Systems and Predictive Modeling

Implementing AI Solutions in Business Contexts

Introduction to AI Ethics and Workshop Objectives

Identifying and Mitigating Bias in AI Systems

Ethical AI Frameworks and Guidelines