International Baccalaureate IB Digital society

Data as distinct from information, knowledge and wisdom

Types of data

- Identify trends, patterns, connections and relationships between different items
- Collect and organize measurable facts about people and communities

Create/collect/extract, store, process, analyse, access, preserve, reuse

Ways to collect and organize data

Charts, tables, reports, infographics, visualizations

Data security

Characteristics and uses of big data and data analytics

Unambiguous, finite, well-defined inputs and outputs, feasible

Instructions, variables, conditionals, loops

Natural language, flow chart, code, programming languages

- Sorting, searching, filtering, prioritizing, classifying, associating, counting
- Programming, software development and implementation
- Machine learning, neural networks and in the creation of other algorithms

Mainframe, server, personal computer, tablet, smart/mobile device, wearable computers and devices

Components of a computer

Types of computing networks

Client, server, modem, router, switch, hub, channels, network interface

- Standards and protocols – interoperability, domain names, addresses
- Security – identification, authentication, encryption, firewall, proxy server, VPN, security layers
- Capacity – bandwidth, data compression, net neutrality
- Infrastructure – internet backbone

Computing network providers and services

- Text, images, audio, animations, video, web pages
- Gaming and e‑sports
- Blogs, vlogs, podcasts, vodcasting and live streaming, hashtags, memes, wikis, streaming media
- User‑generated content
- Synthetic digital media, such as AI‑generated media and deepfakes

Rapid sharing, efficient storage, interactive, linear and non‑linear content, convergence of media forms and layers

Augmented reality (AR), virtual reality (VR), mixed reality (MR) and X reality (XR) technologies

Digital media dilemmas

- Strong, full, general, weak, narrow, domain‑specified
- The Turing test

- Types – supervised, unsupervised, reinforcement learning, deep learning
- Uses – pattern recognition, facial and speech recognition, image analysis, natural language processing

Learn and model complex and non‑linear relationships, generalize from initial inputs

- AI in science fiction and philosophy
- Cybernetics
- AI winters
- The singularity and the multiplicity

- Robots – industrial and productivity robots, service robots, social robots
- Autonomous technologies – Internet of things, autonomous vehicles, drones, virtual assistants

Characteristics of robots and autonomous technologies

- Sensory inputs for spatial, environmental and operational awareness
- Ability to logically reason with inputs, often using machine vision and/or machine learning
- Ability to interact and move in physical environments, sometimes remotely
- Demonstration of some degree of autonomy

Evolution of robots and autonomous technologies

- Early forms of robots and autonomous technology
- Robots in science fiction and philosophy
- Use in industry and manufacturing
- Expanding interactions with human users
- Machine consciousness, cognitive robotics and robot rights

Robots and autonomous technology dilemmas