1. AI Bias in Hiring Software
Scenario:
A tech company develops an AI-powered hiring tool to screen resumes and automate candidate selection. Over time, reports emerge that the AI is biased against certain demographics, unintentionally favoring certain genders and racial groups due to biased training data.
Ethical Issues:
- Fairness & Non-Discrimination (ACM 2.4): The company failed to ensure that the AI system treated all applicants fairly.
- Avoiding Harm (ACM 2.2): The AI negatively impacts candidates who are unfairly rejected.
- Quality of Work (ACM 3.1): The algorithm was not sufficiently tested for bias before deployment.
Discussion Questions:
- Should the company halt the use of the AI system until bias is resolved?
- Who is responsible for ensuring AI models are unbiased?
- Should applicants be informed that an AI made the hiring decision?
2. Using Copyrighted Code in Open-Source Software
Scenario:
A developer working on an open-source project copies a large portion of code from a commercial software repository that they found online. They make small modifications but do not properly credit the original source. The project is later flagged for copyright infringement.
Ethical Issues:
- Respect for Intellectual Property (ACM 2.5): The developer failed to properly credit the original authors.
- Honesty & Trustworthiness (ACM 2.3): The project is misrepresented as original work.
- Professional Competence (ACM 3.2): The developer should have checked the licensing before use.
Discussion Questions:
- Should the open-source project be taken down due to the copyright issue?
- If code was used unintentionally, what should be the appropriate course of action?
- How can developers verify whether a code snippet is legally reusable?
3. Presenting Code as More Complete or Tested Than It Is
Scenario:
A software engineer is working on a critical component of a banking app. Their manager pressures them to complete the task quickly, so they skip some tests and write misleading documentation that suggests the software is fully tested. The software is later found to have severe security vulnerabilities.
Ethical Issues:
- Honesty & Transparency (ACM 2.3): The developer misrepresented the completeness of the code.
- Avoiding Harm (ACM 2.2): The software has security flaws that could put user data at risk.
- Quality of Work (ACM 3.1): The software did not meet professional standards before release.
Discussion Questions:
- What should the developer do if they are pressured to release untested code?
- Should the company take legal responsibility for the security flaws?
- How can software teams ensure realistic deadlines that allow for proper testing?
4. Releasing Software Too Early to Meet Market Demands
Scenario:
A startup is developing a new social media app. To beat competitors, management forces the engineering team to release the product early, despite known security and performance issues. Shortly after launch, users report data breaches and crashes.
Ethical Issues:
- Ensuring Public Good (ACM 4.1): The company prioritized profits over user safety.
- Quality Assurance (ACM 3.1): The software was knowingly released in a flawed state.
- Accountability (ACM 3.5): Who should take responsibility for the app’s failures?
Discussion Questions:
- Should business pressure justify launching an incomplete product?
- What ethical obligations do companies have toward their users?
- If a company knowingly releases flawed software, should they be held liable?
5. Reusing Proprietary Code from a Previous Job
Scenario:
A software engineer leaves a big tech company and starts their own business. To save time, they reuse proprietary algorithms they wrote at their former job, modifying them slightly. Later, their former employer discovers the code reuse and sues for intellectual property theft.
Ethical Issues:
- Intellectual Property & Ownership (ACM 2.5): The developer does not own the code from their previous job.
- Honesty & Trustworthiness (ACM 2.3): Using proprietary code violates confidentiality agreements.
- Legal Compliance (ACM 3.3): The developer should have reviewed employment contracts before reusing code.
Discussion Questions:
- Should developers be allowed to reuse code they wrote at a previous job?
- How can companies protect their intellectual property without stifling innovation?
- If an algorithm is modified significantly, is it still considered stolen?
6. AI-Generated Content and Plagiarism in Software Development
Scenario:
A software engineer uses AI-generated code from a tool like GitHub Copilot to develop a commercial application. However, the AI-produced code is later found to be very similar to copyrighted code from an open-source project. The company is sued for software plagiarism.
Ethical Issues:
- Respecting Intellectual Property (ACM 2.5): The AI may have used copyrighted code without consent.
- Accountability for AI-Generated Content (ACM 3.5): Who is responsible—the developer or the AI tool provider?
- Transparency & Professional Standards (ACM 2.3): Should developers disclose if AI-generated code is used?
Discussion Questions:
- Should developers be held responsible for AI-generated code plagiarism?
- How can AI coding tools be made more ethically and legally compliant?
- What policies should companies implement when using AI in software development?
Conclusion
These case studies reflect real-world ethical dilemmas faced by modern software engineers, AI developers, and computing professionals. The ACM Code of Ethics provides guidance on how to navigate these challenges responsibly and ethically.