Full Answer Section

1. • • Erosion of Trust in AI and Organizations: When AI systems are perceived as biased or discriminatory, it erodes public trust in AI technology itself and in the organizations that deploy such systems. This can lead to reputational damage, legal challenges, and a broader societal skepticism towards technological advancements.
     • Loss of Talent for the Company: The corporation itself suffers by missing out on highly qualified candidates. Diversity in the workforce, including neurodiversity and varied abilities, is increasingly recognized as a driver of innovation, problem-solving, and improved organizational performance. By automatically filtering out these candidates, the company is inadvertently limiting its talent pool and competitive edge.
     • Legal and Regulatory Risks: Such discriminatory practices, even if unintentional, can lead to significant legal liabilities under anti-discrimination laws (e.g., the Americans with Disabilities Act in the U.S.). It also exposes the company to regulatory scrutiny and potential fines.

   • Who is impacted by it:

     • Directly Impacted: Candidates with disabilities who rely on assistive technology or alternative resume formats are directly and severely impacted. They face unfair rejection, reduced employment opportunities, and potentially prolonged unemployment, leading to financial hardship, decreased self-esteem, and feelings of injustice.
     • Indirectly Impacted:
       • Advocacy groups are impacted as they must expend resources to fight against such discriminatory practices.
       • The corporation is impacted through reputational damage, potential legal action, and a diminished talent pool.
       • Society at large is impacted as it moves further away from the ideal of an inclusive and equitable workforce, and public trust in AI is undermined.

2. Explain the role a data privacy, data access, data accuracy, or data security concern played in the selected scenario.

   In this scenario, the primary concern that played a role is data accuracy, specifically the inaccuracy or incompleteness of the training data or the processing parameters of the AI system regarding diverse resume formats.

   The AI system was likely trained on a dataset of resumes that predominantly (or exclusively) consisted of standard, conventional formats easily parsed by the algorithm. It probably wasn’t trained on, or robustly tested with, resumes that might come from individuals using assistive technologies (e.g., screen readers altering formatting, specialized software generating non-standard PDFs) or those who require alternative formats for submission.

   Therefore, the AI’s “understanding” of a “suitable” resume is inaccurate or incomplete because it doesn’t account for the full spectrum of valid and legitimate ways a qualified candidate might present their credentials due to a disability. The system’s “accuracy” is limited to a narrow definition of what constitutes a “correct” resume input, failing to accurately interpret or process inputs from disabled candidates. This data accuracy failure at the input processing or training level directly leads to the biased filtering outcome. It’s not that the data itself is incorrect (e.g., false educational claims), but rather the AI’s ability to accurately process and interpret diverse forms of data related to legitimate accommodations.

B. Apply an ethical framework to the issue described

1. Apply one of the following ethical frameworks to develop one potential response to the ethical issue identified in part A1: utilitarianism.

   Let’s apply Utilitarianism to develop a response. Utilitarianism is an ethical framework that holds that the best action is the one that maximizes overall utility, typically defined as the greatest good for the greatest number of people. It focuses on the consequences of actions.

   Potential Response (Utilitarianism):

   From a utilitarian perspective, the corporation’s continued reliance on the flawed AI hiring system is detrimental because it leads to widespread negative consequences (disutility) for a significant number of people, including candidates with disabilities, advocacy groups, and even the company itself (through reputational damage and lost talent). The aggregate harm (unemployment, discrimination, public distrust) outweighs any perceived efficiency gains from the AI system as it currently operates.

   A utilitarian response would focus on modifying the AI system and the hiring process to produce the greatest net benefit (utility) for all stakeholders. This would involve:

   • Immediate Suspension or Significant Modification of the Flawed AI Function: The company should suspend or significantly modify the automated filtering function for resumes that might come from candidates requiring accommodations. This would minimize immediate harm.
   • Comprehensive Retraining and Redesign of the AI: Invest in a rigorous process to redesign and retrain the AI system using a diverse and inclusive dataset that explicitly includes various resume formats and accommodations for disabilities. This ensures the AI can accurately parse and assess all qualified candidates.
   • Implementing Human Oversight and Appeals Process: Even with a redesigned AI, establish a robust human review process for all candidates flagged by the AI, especially those from underrepresented groups or those whose resumes might fall outside standard formats. This acts as a crucial check to prevent algorithmic bias.
   • Proactive Outreach and Partnerships: Actively engage with disability advocacy groups to understand their needs and solicit feedback on the new system. Partner with organizations that specialize in disability employment to ensure an inclusive talent pipeline.

   The utilitarian justification for this response is that by making these changes, the company would:

   • Increase the utility for candidates with disabilities by providing them with fair opportunities, leading to employment, financial stability, and increased well-being.
   • Increase the utility for the company by accessing a broader, more diverse talent pool, potentially leading to greater innovation, productivity, and a stronger public image, thus improving its long-term profitability and sustainability.
   • Increase the utility for society by promoting inclusivity, reducing discrimination, and demonstrating a responsible use of AI, which fosters greater trust in technology.

   The collective benefits of these actions (fair employment, enhanced reputation, better talent, societal equity) would significantly outweigh the costs of redesigning the system or implementing human oversight.

2. Explain how the response from part B1 would be similar or different when applying another ethical framework from those listed in part B1 to the same ethical issue.

   Let’s compare the utilitarian response with a response derived from Deontology.

   Deontology is an ethical framework that emphasizes duties or rules. Actions are judged based on whether they adhere to a set of moral rules or duties, regardless of the consequences. A key principle is that individuals should be treated as ends in themselves, not merely as means to an end.

   Potential Response (Deontology):

   From a deontological perspective, the core ethical issue is the corporation’s failure to uphold its duty to treat all candidates with dignity and respect, and its duty to provide equal opportunity. The current AI system inherently violates moral rules regarding fairness and non-discrimination.

   A deontological response would emphasize the moral obligations and duties of the corporation:

   • Duty to Non-Discrimination: The company has a moral duty to not discriminate against individuals based on their disabilities. The AI, by filtering out qualified candidates with disabilities, is violating this duty. Therefore, the immediate action is to cease any practice that results in such discrimination.
   • Duty to Fairness and Equal Treatment: Every individual, regardless of their physical abilities or the format of their resume, has a right to be judged on their qualifications and merits. The company has a duty to ensure its hiring process is fair and provides equal access to all.
   • Duty to Respect for Persons: Treating candidates as mere data points to be automatically discarded without proper consideration for their individual circumstances (such as needing accommodations for resume submission) treats them as means to an end (streamlined hiring) rather than as individuals deserving of respect.

   The deontological response would therefore be to:

   • Immediately rectify the discriminatory flaw in the AI system, regardless of the cost or convenience. This is a moral imperative, not a calculation of benefits.
   • Establish a clear, non-negotiable rule that all candidates must have a fair and accessible pathway to apply and be assessed, regardless of disability.
   • Implement mechanisms (like mandatory human review or alternative submission processes) that ensure compliance with this duty, guaranteeing that the process itself is ethical and treats all individuals with respect and fairness.

   Similarities and Differences between Utilitarianism and Deontology:

   • Similarities:

     • Both frameworks would likely arrive at the same practical outcome: that the AI system needs to be fixed to accommodate candidates with disabilities, and human oversight is crucial. Both would advocate for a fair and inclusive hiring process.
     • Both would agree that the current situation is ethically problematic.

   • Differences:

     • Justification/Reasoning:
       • Utilitarianism: The justification for fixing the AI and ensuring inclusivity is based on consequences – it leads to the greatest good (more employment, better talent, improved reputation, less societal harm). The company should do it because it produces the best overall outcome.
       • Deontology: The justification is based on duties and moral rules – the company must do it because it has a moral duty to treat all individuals fairly, respectfully, and without discrimination, regardless of the consequences or benefits. It’s about adhering to the right action, not just the best outcome.
     • Emphasis on Means vs. Ends:
       • Utilitarianism: Focuses on the “ends” – maximizing overall utility. The means (how the AI is fixed) are important primarily insofar as they contribute to the best outcome.
       • Deontology: Places strong emphasis on the “means” – ensuring the process of hiring is inherently just and adheres to moral rules, treating individuals as ends in themselves. The non-discriminatory nature of the action is paramount, independent of its broader consequences.
     • Flexibility:
       • Utilitarianism: Could potentially justify exceptions if a different action were to produce significantly greater overall utility (though unlikely in this specific case, as discrimination rarely leads to net positive utility).
       • Deontology: Less flexible. If there’s a duty not to discriminate, that duty applies universally, regardless of specific circumstances or perceived ‘benefits’ of discrimination.

C. Acknowledge sources, using in-text citations and references, for content that is quoted, paraphrased, or summarized.

(As I am an AI and cannot browse the live internet or access specific academic texts, I will provide examples of how you would cite if you were using typical academic sources. You would replace these placeholders with actual academic sources from your research.)

In-text citations (examples):

• “Algorithmic bias occurs when systemic and repeatable errors in a computer system create unfair outcomes, such as discrimination against specific groups” (Smith, 2022, p. 45).
• The negative societal impact of AI discrimination highlights concerns regarding fairness and equal opportunity (Jones & Brown, 2023).
• Utilitarianism posits that ethical actions are those that maximize overall good (Mill, 1863/2001).
• Deontological ethics emphasizes adherence to moral duties, irrespective of consequences (Kant, 1785/1993).