lab

• AI (Artificial Intelligence)

  The simulation of human intelligence processes by machines, particularly computer systems
• Domains of AI

  • Natural Language Processing (NLP)
  • Computer Vision
  • Machine Learning
  • Robotics and Automation
  • Autonomous Systems
• What AI is Great At

  • Good at detail-oriented jobs
  • Reduced time for data-heavy tasks
  • Saves labour and increases productivity
  • Delivers consistent results
  • Can improve customer satisfaction through personalization
  • AI-powered virtual agents are always available
• Challenges of Implementing AI

  • Expensive
  • Requires deep technical expertise
  • Limited supply of qualified workers to build AI tools
  • Reflects the biases of its training data, at scale
  • Lack of ability to generalize from one task to another
  • Eliminates human jobs, increasing unemployment rates
• Generative AI

  Deep-learning models that can take raw data and "learn" to generate statistically probable outputs when prompted
• Gen AI vs Traditional AI

  Traditional AI systems are primarily used to analyse data and make predictions, while generative AI goes a step further by creating new data similar to its training data
• Popular Gen AI models

  • ChatGPT
  • DALL-E2
  • GitHub Copilot
• GenAi assistance in tasks in education

  • Able to assist in lower order thinking such as Recall, Understand, Apply
  • May struggle to perform higher order thinking such as Analyze, Evaluate and Create
  • Evaluate and Create is still the task of the user/learner
• Ethical Considerations in AI

  • Fairness and Bias
  • Privacy and Data Protection
  • Accountability and Transparency
  • Job Displacement
  • Autonomous Weapons, life and death decisions
• Fairness and Bias

  AI algorithms can perpetuate existing biases present in training data, leading to unfair outcomes for certain groups
• Privacy and Data Protection

  • AI systems may access and process large amounts of personal data, raising concerns about privacy breaches
  • The data you use to ask prompts is used by AI to continually learn, do not upload personal information
  • Data used for training are not all open source
• Accountability and Transparency

  The opaque nature of some AI models makes it challenging to explain the decision-making process, leading to accountability issues
• Job Displacement

  Automation through AI can lead to job displacement, requiring measures for upskilling and workforce transition
• Autonomous Weapons, life and death decisions

  • The development of AI-powered autonomous weapons raises ethical concerns about the potential for misuse and lack of human oversight
  • Will autonomous cars need to decide who to sacrifice?