ITN to explore how AI can be a force for good at the AI & Big Data Expo this November

ITN Business is set to launch “AI & Big Data: A Force for Good,” a news-style program exploring the transformative capabilities of AI at the AI & Big Data Expo in London on November 30, 2023. Anchored by news presenter Duncan Golestani, the program will delve into the ethical and responsible development of AI, its potential to enhance various sectors including healthcare, defense, and security, and the importance of creating a positive impact.

The program will feature contributions from thought leaders, including the Alan Turing Institute, and showcase organizations exemplifying best practices in AI development and utilization. It aims to highlight how AI can simplify everyday tasks, facilitate large-scale change, and contribute to a better and safer world. Key themes to be covered include ethical and responsible development, building an augmented workforce, driving digital transformation through AI, health and wellbeing, and the convergence of technologies.

After its launch at the AI & Big Data Expo, the program will be available on the ITN Business content hub and supported by a digital campaign led by ITN Business, with additional promotion on economist.com. “AI & Big Data: A Force for Good” combines expert interviews, news items, and sponsored editorial profiles to provide comprehensive coverage of AI’s potential for positive impact.

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Aihub Team

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AI and Data Privacy: Balancing AI advancements with privacy concerns and techniques for privacy-preserving AI.

AI and Virtual Assistants: AI-driven virtual assistants, chatbots, and voice assistants for personalized user interactions.

AI and Business Process Automation: AI-powered automation of repetitive tasks and decision-making in business processes.

AI and Social Media: AI algorithms for content recommendation, sentiment analysis, and social network analysis.

AI for Environmental Monitoring: AI applications in monitoring and protecting the environment, including wildlife tracking and climate modeling.

AI in Cybersecurity: AI systems for threat detection, anomaly detection, and intelligent security analysis.

AI in Gaming: The use of AI techniques in game development, character behavior, and procedural content generation.

AI in Autonomous Vehicles: AI technologies powering self-driving cars and intelligent transportation systems.

AI Ethics: Ethical considerations and guidelines for the responsible development and use of AI systems.

AI in Education: AI-based systems for personalized learning, adaptive assessments, and intelligent tutoring.

AI in Finance: The use of AI algorithms for fraud detection, risk assessment, trading, and portfolio management in the financial sector.

AI in Healthcare: Applications of AI in medical diagnosis, drug discovery, patient monitoring, and personalized medicine.

Robotics: The integration of AI and robotics, enabling machines to perform physical tasks autonomously.

Explainable AI: Techniques and methods for making AI systems more transparent and interpretable

Reinforcement Learning: AI agents that learn through trial and error by interacting with an environment

Computer Vision: AI systems capable of interpreting and understanding visual data.

Natural Language Processing: AI techniques for understanding and processing human language.