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SLR6
Ethical, Legal and Environmental Issues - Coggle Diagram
SLR6
Ethical, Legal and Environmental Issues
Environmental Issues
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Energy Consumption
Vast amounts of energy are consumed in the production, functioning, recycling of equipment and the storange of online data in data centres
70% of energy used in mining, manufacturing, transporting, packaging and recycling digital devices
30% of energy used in powering devices, running global communications networks and storing vast amounts of data
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Short Replacement Cycle
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Consequences
- adds to the problem of e-waste due to obsolete devices being thrown away
- more devices must be manufactured which comes with the environmental costs
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Positive
Impact
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Environmental monitoring ensures that regulations are being followed and prevents illegal activities such as poaching
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Personal
Data
Digital Footprint
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Benefits
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Convenience
Personal data (e.g. passwords), only need to be entered once
Drawbacks
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Security
Data breeches can happen - which leads to data falling into the wrong hands and being potentially misused
Discrimination
Analysis of shared data could result in some groups or individuals being discriminated against
Civil Liberties
Analysis of shared data by police forces could wrongly associate innocent people to criminal behaviour or categorise people politically
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Legislation
Data Protection Act 2018
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Lawfulness, Fairness and Transparency
Have a legitimate reason for using someone's data, must tell them what they'll use the data for and must obtain their consent
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Gives data subjects the right to
- be informed about the collection and use of their data
- access their data
- have their inaccurate data corrected
- object to how their data is processed
- withdraw consent at any time
- restrict the way in which their data is processed
- obtain and reuse their data for their own purposes
- complain to the Information Commissioner
Computer Misuse Act 1990
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Unauthorised access to computer material
E.g. logging into another person's computer without their permission
Unauthorised access with intent to commit further offences
E.g. stealing someone's credit card details and using them to commit another crime such as bank fraud
Unauthorised access with the intent to impair the running of a computer or to damage or destroy data
E.g. Planting a virus or installing malware on a computer
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Artificial
Intelligence
Machine
Learning
- a subset of AI
- algorithms that learn by looking for rules and patterns in real life data
- they get progressively better at carrying out tasks without having specified rules set out in their programs
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computer systems that are capable of performing tasks that require human intelligence (e.g. decision making)
Narrow AI
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Examples
- email spam filters
- biometric authentication measures
- self-driving cars
- content recommendations
Algorithmic
Bias
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May occur due to...
- the dataset used to train the AI is biased
- there's a design flaw in the AI causing it to exaggerate bias rather than ignore it
- the developers may have unintentionally installed their own prejudices and preconceptions into the AI
Responsibility
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Problems may be the fault of...
- creator of the algorithm - error made in developing the algorithm may cause the machine to malfunction
- supplier of the data used to train the algorithm - a small or biased set of sample data will result in errors
- user of the algorithm - if they choose to overrule the actions taken by the machine or fail to exercise judgement
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