IB Computer Science Topic A4.4.1 Ethical Implications of Machine Learning in Real-world Scenarios Revision Notes (SL/HL)

IB Computer Science Topic A4.4.1 Ethical Implications of Machine Learning in Real-world Scenarios Revision Notes (SL/HL) | RevisionDojo

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Machine Learning in Real-World Scenarios

Machine learning (ML) is transforming industries, from healthcare to finance, by enabling data-driven decision-making.
However, its deployment raises significant ethical implications that must be carefully considered.

Note

An ethical implication is a potential positive or negative consequence that a decision or action may have.
These consequences can affect various aspects of life, including well-being, justice, fairness, rights, and freedom.

Key Issues

Accountability

Who is responsible when ML systems make mistakes?

Developers, users, and even the algorithms themselves may share responsibility.
Though in many cases, the problem that transpires is there is no clear accountability, which is required when life is at risk.

Example

In autonomous vehicles, determining liability in accidents is a complex ethical and legal challenge.

Consent and Privacy

Given the basis of ML relies on data, it often involves collecting and analyzing personal data
Therefore, it is vital in obtaining informed consent to protect privacy and autonomy

Note

Privacy is a fundamental right recognized by international human rights declarations.

Algorithmic Fairness

ML algorithms can perpetuate biases, leading to discriminatory outcomes.
This problem carries onto possible biases in training data which can lead to unfair and inequitable outcomes.

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Paywall

(on a website) an arrangement whereby access is restricted to users who have paid to subscribe to the site.

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Duis aute irure dolor in reprehenderit

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Note

Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam quis nostrud exercitation.

Excepteur sint occaecat cupidatat non proident

Nemo enim ipsam voluptatem quia voluptas sit aspernatur aut odit aut fugit, sed quia consequuntur magni dolores eos qui ratione voluptatem sequi nesciunt. Neque porro quisquam est, qui dolorem ipsum quia dolor sit amet, consectetur, adipisci velit.

Tip

Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.

Lorem ipsum dolor sit amet, consectetur adipiscing elit.
Sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris.
Duis aute irure dolor in reprehenderit in voluptate velit esse cillum.

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Machine Learning in Real-World Scenarios

Machine learning (ML) is transforming industries, from healthcare to finance, by enabling data-driven decision-making.
However, its deployment raises significant ethical implications that must be carefully considered.

Note

An ethical implication is a potential positive or negative consequence that a decision or action may have.
These consequences can affect various aspects of life, including well-being, justice, fairness, rights, and freedom.

Key Issues

Accountability

Who is responsible when ML systems make mistakes?

Developers, users, and even the algorithms themselves may share responsibility.
Though in many cases, the problem that transpires is there is no clear accountability, which is required when life is at risk.

Example

In autonomous vehicles, determining liability in accidents is a complex ethical and legal challenge.

Consent and Privacy

Given the basis of ML relies on data, it often involves collecting and analyzing personal data
Therefore, it is vital in obtaining informed consent to protect privacy and autonomy

Note

Privacy is a fundamental right recognized by international human rights declarations.

Algorithmic Fairness

ML algorithms can perpetuate biases, leading to discriminatory outcomes.
This problem carries onto possible biases in training data which can lead to unfair and inequitable outcomes.

Definition

Paywall

(on a website) an arrangement whereby access is restricted to users who have paid to subscribe to the site.

anim nostrud sit dolore minim proident quis fugiat velit et eiusmod nulla quis nulla mollit dolor sunt culpa aliqua

Duis aute irure dolor in reprehenderit

Note

Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam quis nostrud exercitation.

Excepteur sint occaecat cupidatat non proident

Tip

Lorem ipsum dolor sit amet, consectetur adipiscing elit.
Sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris.
Duis aute irure dolor in reprehenderit in voluptate velit esse cillum.

A1 Computer fundamentals4 subtopics

A2 Networks4 subtopics

A3 Databases4 subtopics

A4 Machine learning4 subtopics

B1 Computational thinking1 subtopic

B2 Programming5 subtopics

B3 Object-oriented programming2 subtopics

B4 Abstract data types (HL only)1 subtopic

IB Computer Science Topic A4.4.1: Ethical Implications of Machine Learning in Real-world Scenarios Notes

A1 Computer fundamentals4 subtopics

A2 Networks4 subtopics

A3 Databases4 subtopics

A4 Machine learning4 subtopics

B1 Computational thinking1 subtopic

B2 Programming5 subtopics

B3 Object-oriented programming2 subtopics

B4 Abstract data types (HL only)1 subtopic

Machine Learning in Real-World Scenarios

Key Issues

Accountability

Consent and Privacy

Algorithmic Fairness

anim nostrud sit dolore minim proident quis fugiat velit et eiusmod nulla quis nulla mollit dolor sunt culpa aliqua

Duis aute irure dolor in reprehenderit

Excepteur sint occaecat cupidatat non proident

Unlock the rest of this chapter with a free account

Machine Learning in Real-World Scenarios

Key Issues

Accountability

Consent and Privacy

Algorithmic Fairness

anim nostrud sit dolore minim proident quis fugiat velit et eiusmod nulla quis nulla mollit dolor sunt culpa aliqua

Duis aute irure dolor in reprehenderit

Excepteur sint occaecat cupidatat non proident

Unlock the rest of this chapter with a free account