Computer Science AS OCR
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1-1-structure-and-function-of-the-processor as5 主题
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1-2-types-of-processor as3 主题
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1-3-input-output-and-storage as2 主题
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2-1-systems-software as8 主题
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2-3-software-development as5 主题
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2-4-types-of-programming-language as4 主题
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3-1-compression-encryption-and-hashing as3 主题
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3-2-databases as3 主题
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3-3-networks as8 主题
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3-4-web-technologies as13 主题
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html as
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css as
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css-styling as
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javascript as
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variables-and-constants-in-javascript as
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outputs-in-javascript as
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selection-in-javascript- as
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for-loops-in-javascript- as
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while-loops-in-javascript- as
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strings-in-javascript- as
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operators-in-javascript- as
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nested-statements-in-javascript as
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functions-and-procedures-in-javascript as
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html as
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4-1-data-types as8 主题
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4-2-data-structures as4 主题
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4-3-boolean-algebra as1 主题
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5-1-computing-related-legislation as4 主题
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5-2-moral-and-ethical-issues as9 主题
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6-1-thinking-abstractly as3 主题
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6-2-thinking-ahead as1 主题
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6-3-thinking-procedurally as3 主题
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6-4-thinking-logically as2 主题
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6-5-thinking-concurrently as2 主题
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7-1-programming-techniques as9 主题
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8-1-standard-algorithms-and-big-o-notation as8 主题
analysing-personal-information- as
Exam code:H046
Personal Information Ethics
How is personal information analysed using computers?
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Computers play a critical role in analysing personal information, particularly in areas such as healthcare, where medical records are involved
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The process involves data gathering, storage, and analysis, where various technologies and techniques are implemented
Data mining
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This involves extracting patterns from large data sets
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In the healthcare context, it can help in predicting disease trends and identifying at-risk demographics
Machine learning
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Machine learning algorithms can predict patient outcomes, assess risks, and personalize patient treatment plans based on past data
Artificial intelligence
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AI is used to process large amounts of data and make predictions or recommendations
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E.g. AI can analyse medical images to detect diseases or anomalies
Impact of analysing personal information
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As computers become increasingly pivotal in managing and analysing personal information, such as medical records, there arise consequential moral, social, ethical, and cultural implications
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These implications call for careful consideration and the establishment of comprehensive frameworks and guidelines to safeguard individuals’ rights and privacy
Moral implications
Consent & autonomy
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From a moral standpoint, obtaining informed consent from individuals before gathering, storing, and analysing their personal information is crucial
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Consent respects the autonomy of individuals to control information about themselves
Equity
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There is a moral obligation to ensure that the benefits derived from analysing personal information, such as improved healthcare outcomes, are distributed equitably and do not disproportionately favour specific groups
Social implications
Privacy
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Personal information, particularly health data, is sensitive
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The use of computers to manage this data increases the risk of privacy breaches with significant social implications
Digital divide
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The digital divide refers to the disparity between individuals who have access to technology and those who do not
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The use of computers in managing health data may inadvertently exclude those who lack access to digital technology, leading to social inequity
Ethical implications
Data security
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Given the sensitive nature of personal information, there is an ethical obligation to protect this data from breaches, theft, or misuse
Transparency & accountability
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Organisations must be transparent about how personal information is used and be held accountable for any misuse of the data
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This necessitates robust auditing mechanisms
Cultural implications
Cultural sensitivity
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The use of personal information should respect cultural norms and practices
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E.g. some cultures have specific beliefs about health and privacy that must be respected when gathering and analysing their health data
Representation
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There is a risk that certain cultural groups may be underrepresented in data sets, leading to biased outcomes
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Efforts must be made to ensure fair representation of all cultural groups in the data-gathering process
Case Study
AI screening breast cancer images
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A Swedish study suggests that artificial intelligence (AI) can effectively read breast cancer screening images
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The research, led by Lund University, found that AI could detect cancer at a rate similar to two radiologists
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The study involved over 80,000 women, with AI-supported screening identifying cancer in 244 women, compared to 203 identified through standard screening
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Significantly, AI did not increase the rate of “false positives”
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Experts believe AI could help address radiologist shortages and improve efficiency in breast cancer screening
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However, more research is needed to understand its potential and cost-effectiveness fully
External link to BBC News article (opens in a new tab)
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