Navigating the Ethical Landscape of AI

As artificial intelligence (AI) continues to transform supply chain operations, it’s crucial for managers to understand not only the potential benefits but also the ethical implications and risks associated with adopting these powerful tools.

As Arkestro founder and COO Edmund Zagorin said, “Whereas in the past, corporate technology deployments have typically been the responsibility of IT teams, understanding and addressing the impacts of AI tools used by supply chain professionals will increasingly fall on supply chain professionals themselves.”

What will you need to be on the lookout for and understand?

An AI Considerations Checklist

The risks range from data privacy to job displacement to ethical sourcing:

Data privacy and security. AI systems require vast amounts of data to function effectively. Ensure your data collection, storage and usage practices comply with regulations and respect individual privacy.

Bias and fairness. AI algorithms can perpetuate or even amplify existing biases if not carefully designed and monitored. Regular audits for fairness and bias are essential.

Transparency and explainability. Some AI systems operate as “black boxes,” making it difficult to understand their decision-making processes. Strive to adopt and develop AI systems that generate clearly explainable outputs. Also, ensure that systems are continuously assessed for effective performance.

Job displacement. While AI can increase efficiency, it may also lead to job losses. How will workers be impacted? Will training be needed to move them into new roles? What new skills are needed for working with AI? Plan for reskilling and redeployment of affected workers.

Overreliance on AI. Becoming too dependent on AI systems can create a single point of failure. Maintain human oversight and backup systems.

Ethical sourcing. Ensure that the AI tools and the data used to train them are sourced ethically, without exploitation of workers or communities.

An Ethical AI Roadmap

When implementing ethical AI practices, first develop an AI ethics framework. Create guidelines that align with your organization's values and industry standards. Additionally, conduct regular impact assessments: Evaluate the effects of AI implementation on stakeholders, including employees, customers and suppliers.

Other strategies include:

• Prioritize explainable AI. Choose AI systems that provide clear reasoning behind their output and solutions, allowing for better oversight and trust-building.
• Invest in education. Train your team on AI ethics and responsible use of these technologies.
• Collaborate with stakeholders. Engage with employees, customers and partners to address concerns and gather diverse perspectives on AI implementation.
• Maintain human oversight. While AI can augment decision-making, use it for just that — augmentation. Ensure that humans remain in control of critical choices.
• Regularly update and monitor. As AI technologies and ethical standards evolve, continually reassess and update your practices.

‘Technology Is Not Neutral’

By adopting these strategies, supply chain managers can harness the power of AI while mitigating risks and ensuring ethical practices. This approach not only protects your organization from potential pitfalls but also builds trust with stakeholders and contributes to a more responsible AI ecosystem in the supply management profession.

As tech ethicist Tristan Harris, co-founder of the nonprofit Center for Humane Technology, said, “Technology is not neutral. We’re inside what we make, and it’s inside us.” This sentiment underscores the importance of thoughtful, ethical implementation of AI in supply chain management, ensuring that these powerful tools serve not just business needs, but also broader societal values.

(Image credit: Getty Images/Cankansayin)