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Ethics Bistro

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We all tackle ethical dilemmas. Wrong decisions can break careers. Which are the key challenges faced? What are some likely solutions? Where can we find effective tools? Who can apply these and why? Dry, theoretical discussions don't help. Join us for lively, light conversations to learn, share and grow!

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Recent Posts

Applying Ethics and Ethical Learning in Projectized and Matrix Environments

Navigating the Ethical Landscape of Artificial Intelligence: A Balancing Act

Project Management for a Diverse, Equal, and Inclusive World: Strategies and Tips

Organizational Ethical Dilemma - How do you handle this?

PMI Talent Triangle®: how to classify PDUs related to ethics


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Applying Ethics and Ethical Learning in Projectized and Matrix Environments

Categories: Ethics Insight Team


In today’s fast-paced business world, projectized and matrix environments are becoming increasingly popular. These environments are characterized by their dynamic nature, which requires a high level of collaboration and communication among team members. However, working in such environments can also pose ethical challenges that need to be addressed. 

What are Ethics? 

Ethical learning is a lifelong process where its lessons are often based in, not rules,  principles and not taught by rote. Ethics are a set of moral principles that govern an individual’s behavior. They are the foundation of any society and essential for maintaining order and harmony. In a business context, ethics guide an organization’s behavior and decision-making processes. 

Ethical Considerations in Projectized and Matrix Environments 

Working in a projectized or matrix environment can pose several ethical challenges. Common ethical considerations in these environments include, but not limit to: 

Conflict of Interest 

In a projectized or matrix environment, team members may have multiple roles and responsibilities. This can create a conflict of interest, where an individual’s personal interests conflict with the interests of the organization. To avoid such conflicts, it is essential to establish clear guidelines and policies that define the roles and responsibilities of team members. 


In a projectized or matrix environment, team members may have access to sensitive information. It is essential to maintain confidentiality and ensure that such information is not disclosed to unauthorized individuals. This can be achieved by establishing clear policies and procedures for handling confidential information. 


In a projectized or matrix environment, team members may have different levels of authority and responsibility. It is essential to ensure that all team members are treated fairly and that decisions are made based on merit and not personal biases. 


In a projectized or matrix environment, team members may come from different backgrounds and cultures. It is essential to maintain a high level of professionalism and respect for diversity. This can be achieved by establishing clear guidelines and policies for communication and behavior. 


Working in a projectized or matrix environment can be challenging, but it can also be rewarding. By applying ethics and ethical considerations, organizations can ensure that their teams work together effectively and efficiently. It is essential to establish clear guidelines and policies that define the roles and responsibilities of team members, maintain confidentiality, ensure fairness, and promote professionalism. 

Reflecting on your own experience, what other considerations and lessons learnt do you notice, resonate, and/or identify with? 


Ethics in Project Management | PMI 

Code of Ethics & Professional Conduct | PMI 

Ethics Training and Resources | PMI 

Building an Ethical Company ( 

Posted by Ming Yeung on: December 01, 2023 12:00 AM | Permalink | Comments (0)

Navigating the Ethical Landscape of Artificial Intelligence: A Balancing Act

Categories: Values, Business Ethics, Ethics

How do you deal with the balancing act of ethics in an AI-powered world?

Artificial intelligence (AI) has rapidly evolved from a science fiction concept to ubiquitous in our daily lives, transforming industries and shaping the future. However, this transformative power comes with significant ethical considerations, raising concerns about potential biases, discrimination, and the erosion of human autonomy. In the ever-evolving realm of technology, artificial intelligence (AI) stands as both a beacon of innovation and a source of ethical quandaries. AI is increasingly used in businesses across the board, ethical concerns are likely to arise due to conflict between the AI recommendation and human values or what needs to be done right!

"With artificial intelligence, we are summoning the demon." – Elon Musk. Musk's ominous warning reflects a widespread concern about the potential dangers of unchecked AI development. While Musk's perspective may lean toward caution, it underscores the importance of ethical considerations in AI.

"There is a diversity crisis in AI... there is a tendency to build technology that benefits a select few." - Timnit Gebru. Gebru's emphasis on the lack of diversity in AI development brings attention to an ethical concern often overlooked. The potential biases embedded in AI systems can perpetuate social inequalities, making diversity a crucial aspect of ethical AI design.

One of the primary ethical concerns surrounding AI is the issue of bias. AI algorithms are trained on vast amounts of data, which may contain inherent biases that can be amplified through learning. These biases can lead to discriminatory outcomes, particularly in areas such as hiring, lending, etc. A 2018 study by Joy Buolamwini revealed that facial recognition systems from prominent companies exhibited higher error rates for darker-skinned and female faces, highlighting the bias present in AI algorithms. This study highlighted the importance of removing bias from the data before an AI model could work on it. This data also emphasizes the need for rigorous testing and diverse datasets to mitigate biased outcomes in AI applications. Mitigating bias in AI requires careful data curation, algorithmic auditing, and the development of fairness-aware machine learning techniques.

Another ethical concern is the potential for AI to erode human autonomy. As AI systems become more sophisticated, they may make recommendations that have significant impacts on people's lives without their input or consent. This raises concerns about transparency, accountability, and the preservation of individual autonomy. Ensuring human oversight and control over AI systems is crucial to preventing their misuse and preserving human agency.

To address ethical concerns, AI developers must prioritize transparency in their algorithms. Understanding how AI systems make decisions is essential for developers and end-users, fostering accountability in deploying AI technologies. Navigating the ethical landscape of AI requires a comprehensive approach involving policy, regulation, and industry collaboration. Governments must establish clear guidelines and regulations for AI development and deployment, ensuring that these systems are transparent, accountable, and aligned with ethical principles. Industry leaders must adopt responsible AI practices, prioritizing fairness, transparency, and human oversight. And researchers must continue to develop AI technologies that are ethically sound and beneficial to society.

As artificial intelligence continues to reshape our world, the ethical considerations surrounding its development are more critical than ever. Quotes from thought leaders serve as a poignant reminder of the potential risks, while objective data sheds light on real challenges faced by AI systems. Achieving a balance between innovation and ethics is not just a choice but a necessity in the responsible evolution of artificial intelligence. The path forward requires collaborative efforts, transparency, and a commitment to ensuring that AI benefits humanity as a whole.

What is our take on ethics and AI? How do we see treading the balancing act? Are there any specific pointers that we should be aware of?

I would like to know your view of this contemporary topic…


Buolamwini, J., & Gebru, T. (2018). Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification. Proceedings of Machine Learning Research, 81, 1–15

Posted by Dr. Deepa Bhide on: November 17, 2023 01:12 AM | Permalink | Comments (6)

Project Management for a Diverse, Equal, and Inclusive World: Strategies and Tips