core technologies

Question 1

how many industry eras? describe the 4th.

Answer 1

5? debatable, but 4 for sure
4th- 2000s
= ongoing transformation of industries and society through the integration of advanced digital technologies
blurring lines, merge with human lives
a lot of innovation
risk: worse inequality
demand for skills that ppl do not have

components: big data, blockchain, it, ai and machine learning, cloud computing

Question 2

what is cloud computing?

Answer 2

= remote storage that allows access from any device, data synchronisation and backup and collaboration and access

Question 3

without cloud computing

Answer 3

• high upfront costs
• complex management
• scalability issues
• risks of obsolescence
• disaster recovery

Question 4

with cloud computing

Answer 4

• no hardware purchase
• pay-as-you-go
• reduced management complexity
• built-in disaster recovery
• rapid deployment

Question 5

types of cloud- pros and cons

Answer 5

public:
pro- third-party provider, available to anyone, scales quickly and convenient
con- lack of customisation, governance issues

private:
pro- resources dedicated to one business, more privacy for sensitive data
con- expensive

hybrid:
pro- greater flexibility
con- more complex

Question 6

implications of cloud computing

Answer 6

business operation:
- cost efficiency
- rapid deployment
- greater scalability and flexibility
- global reach

innovation and entrepreneurship:
- lower barriers to entry
- new business model
- increased competition

environmental:
- energy efficiency
- resource optimisation

challenges and risks:
- data privacy and protection
- cross-border data transfer
- security risks

Question 7

4 Vs of big data

Answer 7

Variety- various data
Volume- a lot of data
Velocity- speed of data generation and process
Veracity- uncertainty or quality of data

Question 8

types of data

Answer 8

structured- 20%- less storage, easy to manage
unstructured- 80%- more storage, diff to manage, img, video, etc- can be sometimes converted into structured

Question 9

data analytics for structured data

Answer 9

descriptive- what happened?
diagnostic- why it happened?
predictive- what will happen?
prescriptive- what should we do?

Question 10

data analysis for unstructured data

Answer 10

text analysis- summarise, sentiment analysis
audio analysis- speech analysis. musical info retrieval, voice identification, environmental management, health care, security

Question 11

implications data analytics

Answer 11

business:
- data-driven decision making
- new business models based on real-time data analytics

challenges and risks:
- data privacy and protection
- poor data quality
- bias and fairness in analytics
- ethical use of data

Question 12

AI and machine learning

Answer 12

structured data, pre-processing data needed

ai= teaching computers to think and make decisions like humans
machine learning (90s)= train computers to learn from examples- patterns learned from data

Question 13

rule-based systems

Answer 13

= type of AI that applies sets of logical rules to data or input to make decisions, perform actions or generate outputs
- rely on pre-defined rules- if-else- dictate the processing of inputs and determine the system’s behaviour

cons:
- dependency od domain knowledge
- not flexible enough
- lack of learning capabilities

Question 14

Deep learning revolution and AI

Answer 14

unstructured data, pre-processing data not needed

• 2010s- by how the human brain works- teach computers to learn from large amount of data using ‘neural networks’ that mimick the brain structures
• 2020s- GPT-3- milestone for Natural Language Processing and Generative AI

Question 15

traditional vs generative AI

Answer 15

traditional- recognise patterns or make decisions based on already existing data
generative- generate new data

Question 16

Implications of AI

Answer 16

economic:
- job displacement and workforce transformation
- new job creation and econ opportunity
- AI tech controlled by big tech companies, leading to potential econ inequality

social impact:
- changes in the human interactions
- impact on healthcare and wellbeing
- education and learning

environmental:
- massive computational resources are required to train AI

challenges and risks:
- bias and fairness
- individual property and copyright issues
- misinformation, fake news, videos, audios
- individual privacy

Question 17

IoT

Answer 17

=an expanding network of physical objects (things)
objects are embedded with sensors, software, and other tech to connect and exchange data with other devices over the internet

Question 18

technologies behind IoT

Answer 18

sensors: gather data from their environment
actuators: allow devices to interact with the environment y effecting a change- lightswitch, opening a valve

Question 19

the architecture of IOT

Answer 19

device- connectivity- cloud- analytics- end users

connectivity: Bluetooth, NFC, WIFI, LPWAN, cellular networks

cloud: storage, processing and accessibility of data generated by IOT devices, scalability, security, integration

machine learning and analytics: data driven insights, predictive maintenance, enhanced automation, real-time analysis, personalisation

Question 20

implications of IOT

Answer 20

econ:
- business efficiency and productivity
- new business models and revenue streams
- market competitiveness

social:
- quality of life
- accessibility

environmental:
- energy efficiency
- sustainable practices

challenges and risks:
- data privacy and protection
- security risks

Question 21

Blockchain

Answer 21

= digital database or ledger that is distributed among the nodes of a peer-to-peer network
ledger= kind of database where confirmed transactions are recorded

Question 22

types of ledger

Answer 22

centralised- only one actor has it
decentralised- more actors have it
- increase security
- reduced risks of corruption or failure
- transparency and trust

proof of work= mechanism to mitigate an issue- make the process of modifying longer and harder

Question 23

types of blockchain

Answer 23

public
- more decentralised
- anyone can participate
- more transparent
- more secure but slower

private
- participation is restricted to specific members
- less decentralised
- higher level of anonymity
- more efficient but higher risk of security issues

Question 24

implications blockchain

Answer 24

econ:
- innovation in data management
- business efficiency and productivity across industries
- market competitiveness

legal:
- smart contract
- property rights

environment:
- high energy consumption due to the mining process

challenges and risks:
- data privacy and protection
- security risks

Question 25

types of risks and concerns

Answer 25

cybersecurity, data privacy, ethics of AI

Question 26

cybersecurity

Answer 26

= the practice of protecting computers, servers, mobile devices, electronic systems, networks and data from malicious attacks

Question 27

importance of cybersecurity

Answer 27

-digitalisation is nearly in every aspect of our lives
- the need to protect sensitive info
- prevalence of cyberattacks and data breaches

Question 28

common cyberattacks

Answer 28

social engineering- impersonating- scams, phishing
password attack
malware
main-in-the-middle

Question 29

types of cybersecurity

Answer 29

network, application, data, cloud, device

Question 30

Data Privacy

Answer 30

-consent from users
- access control
- purpose limitation
- regulation compliance

important questions: consent, access control, purpose limitation

Question 31

types of digital footprint

Answer 31

active: social media, posts, photos, videos, comments

passive: social security nr, tax records, medical records, IP, browsing history

Question 32

Ethics of AI

Answer 32

issues: data protection, fairness, transparency, explainability, human autonomy

Question 33

issues of ethics of ai

Answer 33

com from data driven natire of AI, biased training and lack of diverse input, complexity and autonomy of AI

Question 34

what to do- ethics of ai

Answer 34

bias detection and mitigation
development of fairness-aware algorithm
enhancing transparency and explainability