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Computer Science GCES AQA

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  1. Representing Algorithms Aqa
    4 主题
  2. Efficiency Of Algorithms Aqa
    1 主题
  3. Searching Algorithms Aqa
    3 主题
  4. Sorting Algorithms Aqa
    3 主题
  5. Data Types Aqa
    1 主题
  6. Programming Concepts Aqa
    5 主题
  7. Arithmetic Relational And Boolean Operations Aqa
    1 主题
  8. Data Structures Aqa
    3 主题
  9. String Manipulation Aqa
    1 主题
  10. Random Number Generation Aqa
    1 主题
  11. Structured Programming Aqa
    2 主题
  12. Robust And Secure Programming Aqa
    4 主题
  13. Number Bases Aqa
    2 主题
  14. Converting Between Number Bases Aqa
    3 主题
  15. Units Of Information Aqa
    9 主题
  16. Hardware And Software Aqa
    4 主题
  17. Boolean Logic Aqa
    3 主题
  18. Programming Languages And Translators Aqa
    2 主题
  19. Cpu Architecture Performance And Embedded Systems Aqa
    4 主题
  20. Memory Aqa
    2 主题
  21. Secondary Storage Aqa
    3 主题
  22. Fundamentals Of Computer Networks Aqa
    8 主题
  23. Fundamentals Of Cyber Security Aqa
    1 主题
  24. Methods Of Preventing Cyber Security Threats Aqa
    1 主题
  25. Relational Databases Aqa
    2 主题
  26. Ethical Legal And Environmental Impacts Aqa
    2 主题
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Exam code:8525

Privacy Issues in Computing

What is a privacy issue?

  • A privacy issue is an issue that comes from collecting, accessing or using personal information without consent or control

  • Who controls the data and how it is used raises crucial questions as technology becomes a bigger part of everyday life

The argument

Citizens

Government/Security services

“Governments and security services have too much access to private data”

“We cannot keep our citizens safe from terrorism and other attacks unless we have access to private data”

Examples of privacy issues in computing

Face recognition

  • The increase in cameras and advances in technology means facial recognition is possible, whilst this can mean an advantage in crime prevention/detection, people are concerned about privacy.

  • Privacy concerns include, what else is being watched? and who is watching?

GPS

  • GPS is built in to most smart phones and brings with it a number of features that many see as a benefit, ‘find my phone‘ for when it gets lost/stolen, location tagging in photos and for navigation software.

  • Some users are concerned with where this data is kept? ,who might have access to it? and is it being used for any other purposes?

Internet monitoring

  • Most schools and businesses use monitoring software to track their students’ and employees’ internet activity

  • Social media companies also employ similar tools to detect and remove illegal or harmful content like hate speech, misinformation, or violent threats

  • Arguments for, these measures promote responsible online behaviour and prevent cyberbullying

  • Arguments against, concerns about limitations to free speech, potential abuse by authorities who control the monitoring systems, and biased algorithms leading to censorship

  • A legal issue is a problem or dispute concerning the interpretation, application, or violation of laws

  • Examples of legal issues in computing are:

    • Copyright – The use of other people’s content without permission

    • Cybersecurity – Protecting against hacking, data breaches and all other cybercrimes

    • Data protection – Responsible collection, storing and use of personal information

  • These issues are covered in more detail here ‘Legislation in Computer Science’

What is an ethical issue?

  • An ethical issue is a situation that raises questions about what is right and wrong

  • As technology advances and laws are slow to keep up, ethical issues are more prevalent

  • Ethical issues call in a person’s own morals and values as there is often a lack of an easy answer and decisions can have consequences for yourself and others

Examples of ethical issues in computing

Digital divide

  • The increasing reliance on computers increases the digital divide, creating inequality between those who have access to technology and those who do not

  • This can hinder opportunities for education, employment, and economic advancement for disadvantaged groups

Algorithmic bias

  • Using algorithms in decision-making can unintentionally promote unfair biases, leading to discriminatory outcomes in areas such as:

    • Job seekers – Factors unrelated to qualifications such as postcode or social media activity

    • Loans – Denying lending to minority groups 

    • Criminal justice – Racial profiling, harsher sentences for certain groups

Intellectual property

  • The ease of digital copying and distribution raises ethical questions about protecting intellectual property rights and fair compensation for creators

  • Digital piracy can lead to significant revenue loss for creators. When consumers access pirated content instead of purchasing it legally, creators are deprived of the revenues they deserve

Automation

  • The automation of tasks through computers raises ethical concerns about job losses and the potential loss of livelihood for workers

Environmental Issues in Computing

What is an environmental issue?

  • An environmental issue is an issue caused by manufacturing and use of computers that has a negative impact on the environment

  • As technology becomes a bigger part of everyday life, the number of devices being manufactured increases

Examples of environmental issues in computing

Natural resources

  • A great amount of natural resources (metals/plastic) are used during the manufacturing and distribution of components

Energy consumption

  • An increase in demand for 24/7 access to resources such as web servers and data centres means an increase in the energy needed to maintain them

Throw-away society

  • As consumption of technology increases and competition in the market expands, the rapid disposal of devices becomes a problem

  • Pollution caused by the production, distribution and disposal of technology gets higher

  • The volume of waste in landfill causes environmental contamination

Impacts & Risks of Digital Technology on Society

  • Exam questions will be taken from the following areas:

    • Cyber security

    • Mobile technologies: mobile phones, tablets, laptops etc.

    • Wireless networking

    • Cloud storage

    • Hacking: gaining unauthorised access to a network/service/device etc.

    • Wearable technologies: smart watches, fitness trackers etc.

    • Computer based implants: pacemakers, cochlear implants etc.

    • Autonomous vehicles: self-driving cars

  • It is important when structuring a response to consider key stakeholders (not all are applicable to every question):

    • Customers

    • Staff

    • Shareholders

    • Community

  • and consider the impacts on key stakeholders such as:

    • profits

    • productivity

    • job loss

    • reduced overheads

    • reduced personal service

    • 24/7 access

Example – Wearable technologies

Stakeholder

Impact

Customers

Positives

  • Improved health and fitness – tracking steps, heart rate, sleep patterns can lead to valuable data into a users’ heath and can motivate them to be active

  • Improved productivity – Quick access to notifications, messages & emails

  • Personalised – data gathered can be used for personalised experiences, fitness suggestions/routines and recommendations

  • Medical monitoring – tracking medical conditions such as diabetes, alerting users when insulin in low/high

Negatives

  • Privacy (see above)

  • Cyber security (see above)

  • Overload – too much data leading to misinterpretations/anxiety

  • Social divide – high cost limits who can purchase them

  • Addiction – constant monitoring/checking leading to unhealthy dependence, distorted sense of self-worth

Shareholders

Positives

  • Increased profits due to rapidly growing market

  • Creating new job opportunities

  • Technological innovation – investment in research and development leading to new breakthroughs and advances in wearable technology

Negatives

  • Intense competition – rivals may make maintaining profit difficult leading to job losses/collapse

  • Data privacy (see above)

  • Government regulations

Community

Positives

  • Health & wellness improvement

  • Emergency alert systems – location tracking for children, monitoring elderly or those living alone

  • Social connections – fitness trackers can foster sense of community through shared goals, motivation to be healthy

Negatives

  • Digital divide

  • Reliance – over reliance on data could lead to people not seeking professional medical advice

  • Data privacy

  • Mental health – obsessive tracking/unrealistic goals can lead to anxiety and body image issues

Examiner Tips and Tricks

Planning is crucial for securing the top marks, a structured discussion must take place, weighing up both sides of the argument

  • Start by bullet pointing 1 positive and 1 negative for each of the issues mentioned in the question

  • For each bullet point, expand it to explain why it is a positive or negative

  • They must apply to the context/scenario in the question

  • Add a conclusion – without it you can’t access the top marks!

Tip! do not feel like you have to use all available space, its quality over quantity, try not to waffle! 

Worked Example

Harrison is a medical researcher trying to find a cure for a disease. He has a team of hundreds of people carrying out medical testing.

Recent developments in Artificial Intelligence (AI) mean that a computer program could do the work of dozens of researchers in a much shorter time. Harrison decides to increase his use of Artificial Intelligence.

Discuss the issues surrounding this decision. Consider the following in your answer:

  • ethical issues

  • legal issues

[6]

How to answer this question

  • Consider each issue first, can you think of any immediate positive and negatives?

  • Try not to start writing the first thing that comes into your head, planning will help achieve higher marks and manage your time spent on the question

  • Remember, there is not a prescriptive list of factors you need to mention, they are looking at how you can use what you have learnt about the issues and apply in a variety of contexts

Indicative Content

  • Ethical

    • Replacing people with machines

    • Loss of jobs

    • Community will suffer

    • Working will be completed faster

    • May find a cure faster

    • More reliable calculations

    • Save more lives

  • Legal

    • More secure than people seeing personal data

    • May be at risk if not backed up

    • May be at risk of threats e.g. hackers

    • Who is responsible if there is an error

Possible response

Ethical

  • Replacing people – Using more AI will mean people losing jobs. Losing jobs will lead to higher unemployment.

  • Cure faster – Using more AI could lead to a cure being found faster, which mean many lives could be saved.

Legal

  • Secure – Using more AI could improve the security of the patient data being used. Using AI means people do not see the data, improving patient privacy.

  • Hacks – Using more AI could increase the chance of hackers targeting the network, increasing the chance of data breaches and putting patient data at more risk.

In conclusion, I think Harrison is right to increase his use of AI as the ultimate goal of his work is to help find a cure for a disease which could save lives.

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