OCN NI AI Week 2

• AI
• Higher Education (non-degree)

OCN NI AI Level 3 Week Two

Tutor: Michael Allison

Email: [e-mail] 

Recap! 

Last week we looked at:

1. The history of Artificial Intelligence 
2. The positives of Artificial Intelligence
3. The negatives of Artificial Intelligence 

Positives/Negatives of AI

Homework Task

Learners should consider current and potential implications for society and individuals.

PowerPoint Task: The Development of AI and Its Implications

Your task is to create a comprehensive PowerPoint presentation on the development of Artificial

Intelligence (AI) and its current and potential implications for society and individuals.

Objective:

Explain the evolution of AI technology, its current impact, and potential future effects on various

aspects of society and individual lives.

Assessment Criteria 2.2:

Be aware of different characteristics and applications of AI:

 Explain the different characteristics and

applications of AI including:

a) machine learning

b) natural language processing

c) computer vision

d) cognitive computing

Machine Learning

Enables computers to learn from data without explicit programming

Applications:

1. Recommendation systems for e-commerce and streaming platforms
2. Fraud detection in financial transactions
3. Predictive maintenance in manufacturing
4. Drug discovery and medical diagnosis

Natural Language Processing NPU

Focuses on interaction between computers and human language

Applications:

1. Chatbots for customer service
2. Email filtering and spam detection
3. Language translation services
4. Voice assistants like Siri and Alexa

Computer Vision

Teaches machines to interpret and understand visual information

Applications:

1. Facial recognition for security systems
2. Autonomous vehicles
3. Medical image analysis for disease detection
4. Quality control in manufacturing

Cognitive Computing

Aims to simulate human thought processes

Applications:

1. Expert systems for complex problem-solving
2. Decision support in healthcare diagnostics
   
3. Personalised learning platforms in education
   
4. Advanced data analytics for business intelligence

What We Have Completed So Far:

L01: Understand The  Development and Implications of AI For Society and Individuals 

L02:  Be Aware of Different Characteristics and Applications of AI 

Current and Potential Ethical Implications of The Use of AI

Current implications:

1. Job displacement and economic inequality due to AI automation
2. AI bias and discrimination in decision-making processes, particularly in hiring, lending, and law enforcement
3. Environmental impact from energy consumption of AI infrastructure

Current and Potential Ethical Implications of The Use of AI

Potential future implications:

1. Widening wealth gap as AI capabilities advance
2. Increased social isolation due to AI-human interactions
3. AI-driven climate solutions competing with AI's growing energy demands

Societal and Environmental Wellbeing

Current Implications:

Employee Wellbeing: AI automation can streamline tasks but may lead to employee isolation, reduced wellbeing, and a sense of alienation in the workplace.

Environmental Impact: The energy demands of AI systems, particularly large-scale models like generative AI, contribute to significant environmental concerns

Societal and Environmental Wellbeing

Potential Challenges: 

Economic Disparities: AI could widen wealth gaps by disproportionately benefiting those with access to advanced technologies while displacing low-skill workers.

Environmental Solutions: On the positive side, AI-driven innovations might contribute to climate solutions, such as optimizing energy use and improving resource management.

Transparency 

Current Challenges:

Black Box Nature: Many AI systems operate as "black boxes," making it difficult to interpret their decision-making processes. This lack of transparency undermines trust and accountability.

Generative AI Issues: Generative AI models can produce false or biased information due to limited visibility into their training data and inherent complexities.

Transparency 

Potential Challenges:

Black Box Nature: Many AI systems operate as "black boxes," making it difficult to interpret their decision-making processes. This lack of transparency undermines trust and accountability.

Generative AI Issues: Generative AI models can produce false or biased information due to limited visibility into their training data and inherent complexities.

Individual Task:

Accountability:

Research Two Current Challenges

Research Two Potential Challenges

Class/Homework Task:

Task: 

Write a Report on AI Characteristics and Applications

Your task is to write a comprehensive report explaining the different characteristics and applications of Artificial Intelligence (AI), focusing on Machine Learning, Natural Language Processing, Computer Vision, and Cognitive Computing.

What Went Well Today?