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62 lines
1.6 KiB
Markdown
62 lines
1.6 KiB
Markdown
---
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title: "ethics-in-cs"
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tags:
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- cosc202
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---
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# ethics-in-cs
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## 1 Case studies
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1. [[facial-recognition-in-US-riots-2021-01-06]]
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2. [[anti-govt-protest-china]]
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3. [[how-is-safe-enough-for-autonomous-vehicles]]
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### 1.1 Differences 1 vs 2
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Govt vs vigilante
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my judgements contain additionl context
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e.g., pro-democratic vs anti
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world contains vast differences
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how systems of laws work
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extent of civil liberties afforded to individuals
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### 1.2 Discussion
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When developing a technology you dont know what is could be used for
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## 2 Ethical handling of data
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- Data moves very quickly due to computerised systems
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- privacy act 2020
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- its unethical to ignore potential security problems
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- df
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## 3 Ethical handling of bias and errors, e.g., in AI
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- large datasets oftenb incdlude bias and errors
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- to AI trained on these datasets with also be biased
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- e.g., facial recognition trining overrepresenting white males
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- ML algorithgms are often opqaue
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- its not possible to understand how decisions are reached
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- makes asessing suitability of AI for a use case difficult
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- explainable AI
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- attacks e.g., 'trapdoors' within ML training data
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## 4 False or misleading claims
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- pressure to release can lead to false claims
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- are features fully tested
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- need to assess risks of bias
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- e.g., AWS uptime information
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- rumoured that service status colour is n management decision
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-
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## 5 Your responsibility
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- dont stay silent
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## 6 Professional reponsibilities
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- comp science per se lacks profressional standards
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- there are some prefessional bodies which encoede responsibilities
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- ACM coc
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- IEEE coc
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- neither are specific to NZ
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- Within NZ must consider treaty obligations
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