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Coursework Issue

The coursework issue is about a class action lawsuit against Ring.

file: <studentID>_Surname

Example of applying Codes

The example is taken from the ACM code of ethics - case study 5

Malicious Input to Content Filters

The US. Children’s Internet Protection Act (CIPA) mandates that public schools and libraries employ mechanisms to block inappropriate material that is deemed harmful to minors.

Blocker Plus is an automated Internet content filter designed to help these institutions comply with CIPA’s requirements. To accomplish this task, Blocker Plus has a centrally controlled blacklist maintained by the software maker. In addition, Blocker Plus provides a user-friendly interface that makes it a popular product for home use by parents.

Due to the challenge of continually updating the blacklist, the makers of Blocker Plus began to explore machine learning techniques to automate the identification of inappropriate content. During the development of these changes, Blocker Plus combined input from both home and library users to aid in the classification of content. Pleased with their initial results, Blocker Plus deployed these techniques in their production system. Furthermore, Blocker Plus continued to collect input from users to refine their learned models.

During a recent review session, the development team reviewed several recent complaints about content being blocked inappropriately. An increasing amount of content regarding gay and lesbian marriage, vaccination, climate change, and other topics not covered by CIPA, had been added to the blacklist. Initial investigations into these incidents suggested that some activist groups had exploited Blocker Plus’s feedback mechanism to provide input that corrupted the classification model.

ANALYSIS SUMMARY:

Blocker Plus is a system designed to block content legally designated as harmful to children. While this filtering constitutes a form of censorship, children are considered a protected vulnerable class. To reduce the impact on adults, CIPA also mandates that these filters must be disabled on request. Given that Blocker Plus is complying with US. federal regulations to facilitate socially responsible uses of computers, the system is consistent with Principles 1.1 and 2.3. Given the complexity and risk involved in Blocker Plus’s use of machine learning techniques, Principle 2.5 calls for extraordinary care. Principle 2.9 suggests that Blocker Plus should have included better protections against the intentional misuse by the activist groups. Blocker Plus’s deployment of machine learning causes harm by suppressing information of legitimate public interest and safety, as well as by discriminating based on sexual orientation, raising concerns for both Principles 1.2 and 1.4. In addition, Blocker Plus provides an example of a system becoming integrated into the educational infrastructure of society. Principle 3.7 emphasises that the developers of such systems have an added responsibility to provide good stewardship and Blocker Plus must correct these issues.

Which principles apply to Blocker Plus?

  • 1.1 Contribute to society and human well-being
    • Socially responsible uses of computing
  • 2.3 Know and respect rules pertaining to professional work
    • This is broken as a federal law is being broken
  • 2.5 Evaluate computer systems and their impacts, including risks
    • Extraordinary care should be taken to identify and mitigate potential risks. Blocker Plus violates this principle by allowing its feedback algorithm to be manipulated by activists to corrupt the classification model.
  • 2.9 Design and implement robustly and usably secure systems
    • 2.9 requires that computing professionals should perform due diligence to ensure systems function as intended, and take appropriate action to secure resources against accidental and intentional misuse, modification or denial of service. That the activists were able to intentionally misuse Blocker Plus means that the system violates this principle
  • 1.2 Avoid harm
    • Avoid harm applies as the corruption of the machine learning model means that information of legitimate public interest (gay & lesbian marriage) and safety (vaccinations and climate change) is suppressed by the activists' intentional misuse of the system
  • 1.4 Be fair and do not discriminate
    • This applies in the respect that suppression of information of legitimate public interest enables discrimination on the basis of sex and sexual orientation
  • 3.7 Take special care of systems integrated into societal infrastructure
    • Applies as Blocker Plus is designed for educational purposes. In failing to prevent intentional misuse of the system, the leadership of Blocker Plus have failed in their responsibility to be good stewards of the system and enable fair access.

Codes for the coursework only apply for negative reasons, e.g. 1.1 may apply as Amazon wished to contribute to society and human well-being. However, this will not be marked.

There is one code in the Amazon Ring case that there is no evidence of; however, it is inferred by a lack of action.

The ACM CARE Framework

For determining whether a case is consistent with the code

Consider

What were the observable effects of Amazon's actions or decisions for Ring users

Who are the relevant actors and stakeholders? What were the anticipated and/or observable effects of the actions or decisions for those stakeholders? What additional details would provide a greater understanding of the situational context?

Analyse

What stakeholder rights (legal, natural or social) were impacted and to what extent, and ask what principles of the code are relevant here.

What stakeholder rights (legal, natural, or social) were impacted and to what extent? What technical facts are most relevant to the actors’ decision? What principles of the Code were most relevant? What personal, institutional, or legal values should be considered?

Review

What potential actions could have changed the outcomes

What responsibilities, authority, practices, or policies shaped the actors’ choices? What potential actions could have changed the outcomes?

Evaluate

What actions (or lack of actions) supported or violated the Code? Are the actions taken in this case justified, particularly when considering the rights of and impact on all stakeholders?

How might the decision in this case be used as a foundation for similar future cases? What actions (or lack of action) supported or violated the Code? Are the actions taken in this case justified, particularly when considering the rights of and impact on all stakeholders?