Could AI Assist in Resolving the Dockworker's Strike?

Below is an excerpt from my new book, Classical Wisdom for Modern Leaders: Emotional Intelligence and AI, now available in ebook, paperback, and hardcover versions on Amazon. (Click here?if interested in learning more).

In Chapter 9 of my book, I explore ethical considerations related to AI and automation, using the famous Trolley Car dilemma as an illustrative tool. — The Trolley Car dilemma presents a moral quandary where one must choose between diverting a runaway trolley to kill one person or allowing it to continue on its path, potentially killing five. The ethical challenge lies in deciding whether it is morally justifiable to actively intervene and cause harm to one person in order to save a greater number of lives, or whether inaction, and letting the trolley continue on its path, is the more ethical choice despite the higher loss of life.

In a less dire but similar vein, in terms of logic, consider how AI might aid in resolving ethical challenges, such as those arising from the ongoing dockworkers strike, by employing an AI Ethics Board committee equipped with a Human-in-the-Loop “AI Twin” to navigate complex decisions. The combined human/AI system would leverage the strengths of humans and AI, using a “web of needs” analysis framework, to select the most optimal outcomes for “wicked problems” — i.e., problems that have no perfect solutions — only less bad options. Granted, this is an oversimplified hypothetical example; the devil is always in the details. Nonetheless, one can perhaps see the possibilities.

(Hypothetical Scenario)

An Ethics Board Utilizing Human in the Loop AI Twin for Ethical Decision-Making at a Multinational Corporation

The Ethics Board and Its Role

At a hypothetical large multinational corporation, the Ethics Board is a group comprised of diverse experts from various fields, including law, philosophy, business ethics, and technology, and representatives from affected stakeholders. Their task is to ensure that the company’s operations, especially those involving AI, align with ethical principles. However, as AI systems become more integrated into business processes, new ethical dilemmas arise that require more complex decision-making frameworks. To meet these challenges, the Ethics Board collaborates with an advanced AI platform called “Human in the Loop AI Twin” (HiL-AI Twin), which acts as an assistant to help navigate these intricate ethical landscapes.

Human in the Loop AI Twin is an AI system designed to assist human teams by analyzing large datasets, identifying ethical risks, and proposing potential solutions, all while keeping humans at the center of the decision-making process. The system integrates not only traditional business considerations but also wider social and human impacts, providing a holistic view of the implications of each decision. Importantly, it operates under the principle that AI should serve humanity, not the other way around. It constantly weighs societal good, human rights, and cultural differences in its evaluations.

Each week, the Ethics Board holds virtual and in-person collective sessions with HiL-AI Twin to explore and debate emerging ethical issues. During these meetings, the AI platform presents data-driven insights and ethical scenarios, while human board members contribute their intuition, experience, and moral perspectives. The collaborative dynamic between human and machine ensures that no decisions are made in isolation from human understanding or societal impacts.

A Complex Ethical Challenge: A Customized “Trolley Dilemma” for the Corporation

During a particular session, the Ethics Board is confronted with a complex ethical dilemma involving the company’s global supply chain. The challenge is akin to a corporate version of the Trolley Problem (as noted above, an ethical dilemma where one must choose between saving many lives at the expense of one or doing nothing and allowing more harm), but adjusted to the realities of a multinational corporation’s operations.

Scenario: The company has recently adopted a fully automated AI system to manage logistics in its global supply chain, which spans multiple continents and employs hundreds of thousands of workers. The system has proven to be highly efficient, reducing costs and improving delivery times, but now the corporation faces an ethical dilemma: In one of the key regions where the system operates, there is evidence that its increased efficiency has led to job losses and economic instability, particularly in regions with weaker labor protections. In contrast, maintaining the current trajectory of automation could benefit the company’s stakeholders, including shareholders, employees in other regions, and customers.

The company must decide whether to:

• Continue the automation strategy, knowing that it will increase unemployment in vulnerable regions but benefit the overall profitability and customer satisfaction globally, or
• Slow down or halt automation in these regions, which may maintain jobs locally but reduce efficiency and cause financial losses to shareholders and potentially increase product prices for consumers worldwide.

The Web of Needs and Considerations

HiL-AI Twin is tasked with assessing this problem using a “Web of Needs and Considerations” framework, which evaluates the issue from various ethical perspectives: economic, social, cultural, and human rights-oriented. The platform collects and analyzes data from the affected regions, including:

• Local employment statistics, tracking the impact on jobs and economic stability.
• Cultural attitudes toward work, focusing on how different societies view job security versus innovation.
• Global corporate impact, considering how a change in the company’s automation approach might affect global stakeholders, including customers and employees in other regions.
• Shareholder expectations, factoring in the company’s fiduciary duty to maintain profitability and deliver value.

AI’s Insight into the Dilemma

During the ethics board meeting, HiL-AI Twin presents a web of competing ethical priorities:

1. Economic Impact in Vulnerable Regions: The data shows that further automation will disproportionately affect regions with fewer social safety nets, where unemployment could exacerbate poverty and social unrest.
2. Shareholder and Global Customer Impact: The AI highlights that slowing down automation could lead to significant financial losses and a decrease in customer satisfaction, particularly in highly competitive markets where efficiency is a key factor.
3. Cultural Considerations: In some countries, local customs and societal norms emphasize the importance of job security and the negative consequences of unemployment on community well-being. The platform also notes that cultural differences influence perceptions of technological innovation, with some regions viewing automation with skepticism, while others embrace it as a driver of progress.
4. Human Rights Considerations: The AI flags that the company’s ethical charter includes a commitment to upholding human rights, including the right to work and social security. By continuing the automation process, the corporation might be perceived as infringing on the economic rights of workers in vulnerable areas.

Balancing the “Least Bad” Option

The Ethics Board, using the insights provided by HiL-AI Twin, realizes that there is no perfect solution to this dilemma — only less harmful options. Together with the AI platform, the board uses a human-in-the-loop approach to weigh each of these ethical considerations, creating a framework where human welfare is prioritized alongside business interests.

• Human Input: One board member advocates for halting the automation in vulnerable regions, citing the company’s ethical responsibility to prevent harm and protect workers. Another member suggests a phased approach, where automation could be gradually introduced alongside investment in retraining programs for displaced workers.
• AI Input:?HiL-AI Twin runs various simulations, predicting how each decision will impact the company over the next five years. In its analysis, a phased automation approach, combined with a substantial investment in workforce development in the affected regions, emerges as the solution that minimizes harm while maintaining long-term profitability.

Conclusion and Ethical Resolution

Ultimately, the Ethics Board, with the help of HiL-AI Twin, opts for a phased automation plan, with safeguards in place for workers who will lose their jobs. The corporation pledges to invest in education and retraining programs in the affected regions, in partnership with local governments and NGOs. This approach, while still not perfect, serves as the “least bad” solution in this intricate ethical web, balancing human welfare, business sustainability, and global responsibility.

The board also decides to conduct quarterly reviews with HiL-AI Twin, adjusting the company’s strategy based on new data and ensuring that ethical standards are continually maintained across its global operations.

Ethical Considerations

The outcome underscores the value of a human-centered ethical approach, with AI providing data-driven insights while human intuition, experience, and moral judgment guide the final decision. By integrating the “Human in the Loop AI Twin” platform, the Ethics Board could navigate a complex web of considerations, achieving an ethical balance that neither human nor AI alone could reach.

This scenario highlights the importance of maintaining human oversight in decisions involving AI, ensuring that even as automation advances, human well-being and societal impacts remain at the forefront of decision-making.

Reflections and Insights

This example illustrates how AI, when used collaboratively with human decision-makers, can provide a multiplier effect in solving ethical challenges. HiL-AI Twin’s ability to process vast amounts of data and generate ethical insights helps the Ethics Board make informed decisions that align with both ethical standards and business goals. By working together, the company can ensure that its AI systems operate responsibly, preserving the dignity and rights of workers, customers, and shareholders alike.

About the Author

David Ragland is a recognized expert at the intersection of organizational theory, leadership, and artificial intelligence. With a blend of academic rigor and industry experience, he draws on insights from classical philosophy to explore how timeless wisdom can inform modern leadership practices, particularly as AI transforms organizations worldwide. David is passionate about how classical virtues can guide ethical leadership and decision-making in the age of technology.

He earned his Doctorate in Business Administration with a focus on Organizational Behavior from IE University in Madrid, Spain, where his research delved into leadership dynamics and cultural traits in global virtual teams. He also holds a Master of Science in Information and Telecommunications Systems from Johns Hopkins University and a Bachelor of Science degree in Psychology from James Madison University. To stay ahead of technological advancements, David completed a certificate in Artificial Intelligence and Business Strategy from MIT, reinforcing his commitment to understanding AI’s strategic role in contemporary organizations.

As an author, adjunct professor, and former senior technology executive, David bridges the gap between theory and practice. His research, writing, and teaching blends classical texts with modern management principles and the latest technological innovations, offering a holistic view of leadership and organizational behavior.

David’s current research and writing explore how classical wisdom, can inform ethical leadership and effective decision-making in a rapidly evolving, AI-driven world. His mission is to equip modern leaders with the knowledge and tools needed to navigate the complexities of the future workplace while remaining grounded in the timeless principles of human leadership.

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