Case study: Crafting Code Responsibly: A Developer’s Odyssey with ChatGPT

Before starting this experience, please go through all of the “Foundations” readings and experiences.

Please read Crafting Code Responsibly: A Developer’s Odyssey with ChatGPT.

Questions for discussion

Choose one of the ethical discussion areas below:

1. Responsible Development: How can developers balance the benefits of using ChatGPT for coding assistance with the ethical responsibility to ensure accurate and reliable outputs?
2. Biased Training Data: What steps can developers take to mitigate the impact of biased training data on the responses generated by ChatGPT? How important is it to prioritize diverse and unbiased datasets in AI model training?
3. Mitigating Inappropriate Output: Discuss the strategies outlined in the article for mitigating the risk of inappropriate or offensive content generated by ChatGPT. How can developers ensure a positive and inclusive coding environment?
4. Securing User Data: What are some best practices for developers to prioritize data security when integrating ChatGPT into their applications? How can developers uphold transparency and obtain user consent in individual usage contexts?
5. Manipulative Use: Explore the ethical implications of using ChatGPT for manipulative purposes, such as spreading misinformation or engaging in social engineering. What role do developers play in promoting responsible AI usage within their coding communities?
6. Context and Intent: How does ChatGPT’s sensitivity to input phrasing impact its responses, and what strategies can developers employ to ensure accurate and relevant outputs? How can developers leverage contextual cues to enhance the model’s understanding?
7. Ethical Considerations in Code Generation: Discuss the importance of accuracy, transparency, responsible implementation, and security in code generation with ChatGPT. What ethical dilemmas might developers encounter when using AI models for code generation, and how can they navigate them effectively?
8. Continuous Monitoring and Evaluation: Why is it essential for developers to establish mechanisms for continuous monitoring and evaluation of ChatGPT’s responses, particularly in real-world applications? How can developers address biased outputs and ensure a fair and unbiased user experience over time?
9. User Trust and Bias Mitigation: How can developers build and maintain user trust in the quality of the code generated by ChatGPT? What strategies can developers implement to mitigate potential biases in code suggestions and ensure inclusivity?
10. Promoting Responsible AI Usage: What role do developers play in promoting responsible AI usage within their coding communities? How can developers contribute to creating a positive and trustworthy development environment while harnessing the capabilities of ChatGPT?

Ask ChatGPT (or other GenAI) to answer the questions in your chosen discussion area. Imagine that you were in situation where you on a position where you have to address the area you chose. Would you address it as suggested by ChatGPT? If possible, justify your answer by reference to either the ACM Code of Ethics or the Software Engineering Code of Ethics and Professional Practice.

Case Discussion

Sara, a talented software engineer with eight years of experience in the company, recently applied for a promotion to a senior software developer position. Sara has consistently demonstrated exceptional technical skills, leadership qualities, and a strong commitment to the company’s goals. She has contributed significantly to various projects, showing a deep understanding of software development principles and innovative problem-solving abilities.

However, despite her qualifications and years of service, Sara was passed up for the promotion in favor of Charlie, a relatively new employee with only two years of experience. Charlie, a tall white male, is known for his proficiency in using artificial intelligence (AI) for software development tasks. Charlie is now Sara’s manager, but she finds it difficult and unproductive to work with him due to his low competency, limited technical knowledge, and lack of experience in successfully developing software systems. She feels that she is continually educating Charlie on basic technical issues and tools (such as using GitHub) and what to do on the project.

While Charlie’s skills in AI are commendable, many in the company were surprised by the decision to promote him over Sara, given her extensive experience and proven track record Sara feels disheartened and demotivated by the outcome, questioning the fairness and transparency of the promotion process. She wonders if her gender or years of service played a role in the decision and whether she has been unfairly overlooked despite her qualifications and contributions to the company.

The decision has sparked concerns among employees about potential biases in the promotion process. Some speculate that unconscious biases, such as gender or racial bias, may have influenced the decision-making process. Others argue that Charlie’s proficiency in AI, a rapidly growing field in software engineering, may have been prioritized over Sara’s broader skill set and experience.

Take the companies position and argue why it was ethical to favor Charlie’s proficiency in AI over Sara’s broader skill set and experience. Now take the contrary position and argue why it was unethical to disregard Sara’s experience and proven track record in favor of Charlie’s proficiency in AI. If you were making the promotion decision, what would you decide and why?