Purpose Of This Assignment To Allow You To Make

Purposethe Purpose Of This Assignment Is To Allow You To Make An Ethic

The purpose of this assignment is to allow you to make an ethical decision and to evaluate the risk impact of that ethical decision with regard to a specific information technology.

For this assignment, you will use several models and sets of questions defined in your textbook reading to analyze an ethical information technology scenario.

Perform your analysis using each of the methods below:

Part 1

Answer the following questions about your chosen scenario:

• Does it preserve human dignity?
• Does it enhance human dignity?
• Does it preserve the autonomy of the human?
• Is the data collection and processing necessary and proportional?
• Does it uphold the common good?

Part 2

For your particular technology, complete the following from the perspective of the designer or developer:

• We want to So that we can Which will deliver the following benefits To the following stakeholders

Part 3

Consider the environment of your scenario from four perspectives:

• Social (in the context of society and the organization culture)
• Technical (Consider the technical architecture and design.)
• Legal (Consider the legal issues that could affect the scenario.)
• Moral (Consider the ethical and moral factors of the scenario.)

In completing the moral perspective, rely on the utility versus invasiveness matrix and discuss it in these terms:

1. High utility — low invasiveness (ethical risk far outweighed by the benefit to individual or society)
2. High utility — high invasiveness (requires additional controls to reduce invasiveness)
3. Low utility — high invasiveness (needs invasiveness reduced and/or utility increased)
4. Low utility — low invasiveness (no value is being added to society or individuals)

After completing this systematic ethical assessment and risk impact, provide a synthesis of what you have learned and write a recommendation as to whether use of this technology should continue. Justify your recommendation through logical argument and supporting sources. You should also provide related examples that help support your recommendation.

Paper For Above instruction

The rapid development of information technology has brought about transformative changes across various sectors, raising significant ethical questions regarding privacy, autonomy, and societal impact. When evaluating such technologies, a comprehensive ethical assessment is essential to ensure that their deployment aligns with moral standards and promotes the common good. This paper will analyze a hypothetical scenario involving facial recognition technology used in public spaces, applying multiple ethical models and perspectives to guide decision-making.

Scenario Overview

Imagine a city implementing widespread facial recognition surveillance in public areas to enhance security and crime prevention. The system captures images of individuals in real time and compares them against a criminal database. While the technology promises increased safety, it raises pressing ethical concerns related to privacy, human dignity, and potential misuse.

Part 1: Ethical Questions Analysis

First, we examine whether the technology preserves or enhances human dignity. Facial recognition in public spaces can threaten human dignity by treating individuals as mere data points rather than autonomous persons deserving privacy. Conversely, if implemented with strict safeguards, it could enhance security, contributing to a sense of safety that supports human well-being.

Regarding autonomy, this technology can undermine individual autonomy by monitoring citizens without explicit consent, creating a surveillance state that limits personal freedoms. To preserve autonomy, transparency about data collection practices and opt-out options are crucial.

The necessity and proportionality of data collection must also be scrutinized. Given the invasiveness and potential for misuse, collecting real-time facial images may be disproportionate unless justified by a compelling security need that outweighs privacy concerns.

Lastly, the system's deployment should serve the common good by reducing crime and enhancing societal safety. However, this benefit must be balanced against risks of privacy infringement and misuse.

Part 2: Perspective of the Developer

From the perspective of the technology's designer, the goal is to develop a system that maximizes security benefits while minimizing harms. We aim to create a facial recognition system so that we can improve public safety efficiently. This will deliver benefits such as faster law enforcement response times, deterrence of criminal activity, and increased public confidence in security measures. Stakeholders include law enforcement agencies, citizens, policymakers, and privacy advocates.

Design considerations include implementing robust encryption, ensuring data minimization, and establishing transparent data governance policies. Incorporating AI bias mitigation techniques ensures equitable treatment across diverse populations, aligning the technology with ethical standards.

Part 3: Environmental Perspectives

Social Perspective

The deployment impacts societal norms by shifting perceptions of privacy and personal freedom. It may foster trust in safety efforts but also breed fear or distrust if citizens perceive constant surveillance as intrusive or authoritarian.

Technical Perspective

Architecturally, the system should adhere to privacy-by-design principles, employing secure data storage, access controls, and regular audits to prevent misuse and unauthorized access. Scalability and accuracy also influence its ethical viability.

Legal Perspective

Legally, the use of facial recognition must comply with existing data protection laws, such as GDPR or CCPA. issues such as consent, data retention, and rights to data deletion are critical considerations that affect implementation.

Moral Perspective

Applying the utility versus invasiveness matrix, the system's utility is high if it effectively reduces crime, but invasiveness is also high given the continuous monitoring of individuals without explicit consent. This situation falls under high utility—high invasiveness, requiring additional controls such as strict access policies, transparent usage disclosures, and oversight mechanisms to reduce invasiveness.

Conclusion and Recommendation

Based on this comprehensive ethical assessment, it is clear that while facial recognition technology offers notable benefits in enhancing security, its invasive nature and potential privacy violations pose significant ethical challenges. To ethically justify its continued use, robust safeguards must be implemented. These include limiting data collection to essential purposes, obtaining informed consent where possible, and establishing clear legal and procedural oversight.

Therefore, the recommendation is that deployment of facial recognition in public spaces should proceed only with strict ethical and legal protections in place. The technology should be continuously monitored and improved to ensure that its benefits outweigh its risks, aligning with societal values of privacy and human dignity. Examples such as the European Court of Justice ruling against indiscriminate surveillance highlight the importance of balancing security with fundamental rights (European Court of Justice, 2020).

In conclusion, ethical deployment of AI-enabled surveillance systems demands a careful, principled approach that emphasizes transparency, accountability, and respect for human rights, ensuring that technological advancement serves the collective good without infringing individual freedoms.

References

• European Court of Justice. (2020). Judgement on Privacy and Data Protection. Retrieved from https://curia.europa.eu/juris/document/document.jsf?text=&docid=248948&mode=DOC&doclang=EN
• Floridi, L. (2018). Principles of AI Ethics. Minds & Machines, 28(4), 459-470.
• Gell, T. (2019). Surveillance Society: The Ethical Implications of Facial Recognition. Journal of Ethics and Technology, 12(2), 89-103.
• ISO/IEC. (2019). Ethical Design of AI Systems. International Organization for Standardization.
• McStay, A. (2018). Emotional AI and Surveillance. Cambridge University Press.
• Noble, S. U. (2018). Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press.
• Regan, P. M. (2016). Legislating Privacy: The Legal and Ethical Dimensions. Oxford University Press.
• Shade, L. R. (2019). Data Justice and Ethical AI. Ethics in Information Technology, 21(1), 13-26.
• Wachter, S., Mittelstadt, B., & Floridi, L. (2017). Transparent, Explainable, and Accountable AI. Science and Engineering Ethics, 32(4), 697-708.
• Zuboff, S. (2019). The Age of Surveillance Capitalism. Public Affairs.