Ethics Bistro

• Embedding ethics training into all levels of the organization
• Applying the PMI EDMF v8 when facing ambiguous or high‑impact decisions
• Strengthening internal controls and access governance
• Encouraging employees to speak up when they perceive unethical conduct.
• Creating a culture where integrity is rewarded, not assumed.

• Accountability and responsibility: When AI systems are used for decision-making, it is challenging to assign accountability if something goes wrong. AI agents are not members of the project team; they are a tool that should augment human capabilities. Project managers need to establish clear lines of responsibility for the outcomes of AI-driven projects.
• Bias and fairness: AI is still in its infancy, and finding large volumes of good-quality data that can be used to train AI models is difficult. AI models can inherit biases from the data they are trained on, leading to unfair or discriminatory outcomes in areas like task assignment or performance evaluation. These biases can reinforce existing societal prejudices related to factors like gender, race, or socioeconomic status, potentially leading to workplace discrimination and legal penalties.
• Transparency and explainability: The "black box" nature of some AI algorithms makes it difficult to understand how they reach a decision. This lack of transparency can erode trust and make it hard for project managers to oversee, troubleshoot, or validate AI-driven recommendations.
• Over-reliance on AI agents and lack of human oversight: At any point in the project, the control should remain with humans and avoid over-reliance on AI. Lack of knowledge and practice can lead to a decline in critical thinking and human judgment among team members.

• Contextual application: The principles and the code are designed to be applied within the context of project work. Ethical dilemmas are often encountered when balancing conflicting needs, and the framework provides guidance for decision-making.
• Performance domains: Ethical dilemmas can arise in any of the performance domains (e.g., Stakeholders, Delivery, Performance). The principles and the code provide the tools for navigating these situations and making responsible choices.
• Focus on value: Ethical considerations are a crucial part of focusing on long-term value, rather than just short-term outputs, ensuring that projects are conducted in a responsible and sustainable way. 

• The principles in the PMBOK 8th Edition align with and reinforce the values in the PMI Code of Ethics and Professional Conduct, which are honesty, responsibility, respect, and fairness.
• Project managers are expected to apply these principles in their daily work to make ethical choices that lead to positive results and maintain trust. 
• The PMI Code of Ethics and Professional Conduct remains the primary source for detailed ethical guidelines.
• ProjectManagement.com offers webinars that discuss the connection between PMBOK 7 principles and the Code of Ethics. 

It was a rainy Tuesday when the red flag popped up. The AI tool, designed to optimize resource allocation across our project portfolio, had flagged three critical projects for delay. The model’s recommendation? Shift half the team from Project Titan to Project Eclipse to balance out workloads.

At first glance, it seemed logical. The resource allocation maps, and velocity graphs supported the reallocation. But something did not sit right.

I had collaborated closely with Titan’s team leads for months. They were on the verge of a breakthrough with a critical client deliverable. Moving people now, even with Eclipse falling behind, could cause a domino effect across our most valuable account.

I called a huddle.

“Why did the model deprioritize Titan?” I asked the AI SME.

“It is based on risk scoring from delivery variance, budget utilization, and resource burn. Titan looked stable, so it pulled from there.”

“But it does not know the client conversation we had last week. Titan’s ‘stability’ is built on momentum we cannot afford to interrupt.”

That was it. The AI had the data but not the context.

We chose not to follow the recommendation. Instead, we manually adjusted scope and brought in temporary support for Eclipse. It was a tough call, but three months later, Titan delivered on time and exceeded client expectations. Eclipse caught up too—without derailing the portfolio.

That experience taught me something: AI is brilliant at pattern recognition, but it does not see what you know. It does not read nuance. And it does not carry responsibility.

So, when should project managers trust AI—and when should we intervene?

Trust AI when:

• You need unbiased, data-driven insights fast.
• The decision space is clearly defined and repeatable.
• You are analyzing trends across massive datasets where human bias or oversight might creep in.

But intervene when:

• The stakes involve human relationships, trust, or reputational risk.
• The model’s logic lacks access to critical context.
• The recommendation “feels wrong” and your intuition is backed by experience not fear.

AI is like a junior analyst with infinite memory and no emotional baggage. But it lacks judgment, and judgment is where leadership lives.

As project managers, we are not just responsible for outcomes; we are stewards of values. According to the PMI Code of Ethics, we are bound to act with responsibility, respect, fairness, and honesty. Blindly following AI no matter how accurate without human oversight may compromise all four.

Use AI like a compass not a map. Let it guide your thinking, but do not let it override your wisdom.

Because when things go south, the algorithm will not be in the room explaining the outcome you will.

So next time your AI flags a decision, pause. Ask: Does this align with what I know, what I have seen, and what matters most?

If the answer is no, trust yourself and intervene.

Reference:

PMI Code of Ethics

Webinar: Ethical Project Leadership in the digital age

Webinar: When to Trust AI and When to Intervene

The January 9, 2025, Bloomberg article titled "The New $30,000 Side Hustle: Making Jobs Referrals for Strangers" by Jo Constantz highlights a disturbing ethical issue and discusses the emerging trend of technology workers earning significant sums by referring job candidates they have never met. This underground marketplace for employment referrals has gained traction at major U.S. companies like Microsoft and Nvidia. Platforms like Refer Me and Refermarket allow job seekers to anonymously request referrals from verified employees, with some tech workers earning up to $30,000 in referral bonuses over 18 months. While this practice can improve hiring odds, it raises ethical concerns as it often violates company policies that require personal knowledge of candidates.

Examining the ethical issue using PMI’s Code of Ethics and Professional Conduct as Ethical Decision-Making Framework, I, as an astute member of the Ethics Insight Team, draw these lessons learned and propose remedies for considerations.

Comments and Lessons Learned:

1. Responsibility: Employees must recognize their responsibility to uphold company policies and ensure that referrals are based on genuine knowledge of the candidate's qualifications. This practice not only maintains the integrity of the hiring process but also ensures that the referred candidates are truly fit for the roles.
2. Respect: Respect for the hiring process and the candidates is crucial. Referring strangers without proper vetting can lead to mismatches and wasted resources for both the company and the candidates. Respecting the process ensures that all parties involved are treated fairly and professionally.
3. Fairness: The practice of selling referrals can create an unfair advantage for those who can afford to pay for them, undermining the principle of equal opportunity. Companies should strive to create a level playing field where all candidates are evaluated based on their merits and qualifications.
4. Honesty: Honesty is paramount in the referral process. Employees should provide truthful and accurate information about the candidates they refer. Misrepresenting a candidate's qualifications can damage the company's reputation and lead to poor hiring decisions.

Remedy: To address these ethical concerns, companies should reinforce their referral policies and provide clear guidelines on acceptable practices. Regular training on the corporate/internal on similar Code of Ethics and Professional Conduct Policy and or Procedures can help employees understand the importance of responsibility, respect, fairness, and honesty in the hiring process. Additionally, implementing stricter monitoring and enforcement mechanisms can deter unethical referral practices and ensure a more transparent and equitable hiring process.

How would you, as an ethical project practitioner, act when a stranger offers monetary incentives and seeks your referrals? Does the situation happen to you? Are there any other lessons learnt and remedies to which you can relate? The PMI Ethics Insight Team likes to bring this timely topic for a healthy deliberation.

References:

Constantz, J. (2025, January 9). How to Get a Job Referral from a Stranger. Bloomberg.com. https://www.bloomberg.com/news/articles/2025-01-09/how-employee-referrals-for-tech-jobs-became-a-side-hustle

Project Management Institute. (n.d.). Code of Ethics and Professional Conduct. pmi.org. https://www.pmi.org/-/media/pmi/documents/public/pdf/ethics/code-values-card.pdf

Project Management Institute. (2011). PMI Ethical Decision-Making Framework (EDMF). pmi.org. https://www.pmi.org/-/media/pmi/documents/public/pdf/ethics/ethical-decision-making-framework.pdf

“Fairness is not an attitude. It's a professional skill that must be developed and exercised – Brit Hume”

In the dynamic world of project management, maintaining fairness and avoiding favoritism and prejudice are crucial for fostering a productive and harmonious work environment. These ethical challenges can significantly impact team morale, project outcomes, and the overall success of an organization. Let’s delve into how fairness, favoritism, and prejudice play out in project management and explore strategies to address these issues effectively.

1. The Importance of Fairness

• Impartial Decision-Making: Fairness in project management involves making decisions impartially and objectively. This means evaluating team members based on their skills, performance, and contributions rather than personal biases or relationships.
• Equal Opportunities: Providing equal opportunities for all team members to participate, contribute, and grow is essential. This includes fair distribution of tasks, recognition, and rewards.

2. The Detrimental Effects of Favoritism

• Resentment and Demotivation: Favoritism can lead to resentment among team members who feel overlooked or undervalued. This can result in decreased motivation and productivity.
• Unbalanced Workload: When certain individuals are favored, it can lead to an unbalanced workload, where some team members are overburdened while others have less to do. This imbalance can affect the overall efficiency of the project.

3. Addressing Prejudice in the Workplace

• Awareness and Training: Raising awareness about unconscious biases and providing training on diversity and inclusion can help mitigate prejudice. This ensures that all team members are treated with respect and fairness.
• Inclusive Culture: Promoting an inclusive culture where diverse perspectives are valued and encouraged can help reduce prejudice. This involves actively listening to and considering the viewpoints of all team members.

4. Strategies for Promoting Fairness

• Transparent Processes: Implementing transparent processes for decision-making, task allocation, and performance evaluation can help ensure fairness. Clear criteria and open communication are key to maintaining transparency.
• Regular Feedback: Providing regular and constructive feedback helps team members understand their strengths and areas for improvement. This fosters a culture of continuous learning and development.

5. Creating a Positive Work Environment

• Recognition and Appreciation: Recognizing and appreciating the efforts and achievements of all team members fosters a positive work environment. This helps build trust and encourages everyone to contribute their best.
• Conflict Resolution: Addressing conflicts promptly and fairly is crucial. Ensuring that all parties are heard and that resolutions are based on facts rather than biases helps maintain a harmonious team dynamic.

Conclusion

Fairness, favoritism, and prejudice are critical issues in project management that can significantly impact team dynamics and project success. By promoting fairness, addressing favoritism, and mitigating prejudice, project managers can create a more inclusive, productive, and positive work environment. This not only enhances team morale but also drives better project outcomes.

Question:

What are your experiences with fairness, favoritism, and prejudice in project management? How have you addressed these challenges in your projects? Share your thoughts and insights!