Building Trust in the Robot Revolution

Proactive data responsibility is essential as warehouse robotics transform the industry. © Pugun & Photo Studio – stock.adobe.com

Addressing Concerns Around Data Safety and AI-Powered Systems

By Gemma Ross, is VP of Operations at OSARO

The warehouse floor is undergoing a remarkable transformation. With the help of artificial intelligence, robots are rapidly increasing their presence, streamlining various tasks from inventory movement to picking and packing orders. This automation offers significant efficiency gains and innovative solutions for labor challenges such as shortages and wage increases.

However, the exciting potential of warehouse robotics carries an equally important responsibility: data security. As robots become integral to operations, concerns about the data they collect and manage naturally arise. Proactive data responsibility by robotics vendors is crucial to build the necessary trust for widespread adoption, ensuring efficiency gains don’t come at the cost of security.

Defining the Risks: Data Privacy and Security Concerns in Warehouse Robotics

The rise of warehouse robotics raises questions similar to those surrounding Generative AI. What data is being collected, where is it stored, and how secure is it? Here’s why potential adopters should be mindful of these data privacy and security concerns and focus on companies that address these criteria:

• Data Collection: Pick-and-place robots rely heavily on camera systems and various sensors to navigate the warehouse and manipulate objects. This data collection can encompass product details, inventory layouts, package size, weight, and potentially even customer information visible on packages.
• Data Storage and Security: Understanding how this data is stored and secured is crucial. E-commerce and third-party logistics companies (3PL) executives should inquire about the vendor’s data security practices, encryption methods, and access controls. They should ensure the data is stored securely and only accessed by authorized personnel.
• Data Aggregation and Use: It’s important to understand how the collected data is used. Will it be used solely to optimize robot performance, or is there potential for aggregation with other data sources? Transparency about data use is key to building trust.

Ask the Right Questions

As a potential adopter of warehouse robotics, here are some key questions to ask your systems integrator or robotics supplier to ensure robust data security:

1. What specific data is collected by the system’s machine-learning software, and why is it necessary for operation?
2. How is the collected data secured at rest and in transit?
3. Who has access to the data? What access control measures are in place?
4. What is the data retention policy, and how is data permanently deleted?
5. Is there a possibility of data aggregation with other sources? If so, how will customer privacy be protected?

Best Practices for Data Security: Building a Resilient Foundation

Best practices frameworks like System and Organization Controls Type II compliance (SOC 2) provide a structured approach to responsible data management. Let’s explore some of the core components that contribute to this level of security and should be discussed with your systems integrator or robotics supplier:

• Access Controls: Think of these like a secure gatekeeper for your robotics systems. Strict controls determine who can access what information and actions, ensuring only authorized personnel have access to the data needed for their roles.
• Regular Updates and Patching: Keeping robot software up-to-date is like plugging up any potential holes in your defenses. Regular updates and security patches address known issues and protect against cyberattacks.
• Network Security: Picture this as a protective shield around your robotics systems. Firewalls, secure network configurations, and monitoring tools help block unauthorized access and detect any suspicious activity early on.
• Third-Party Risk Management: Your robot’s security isn’t just about your own practices. Choosing reliable suppliers with strong security measures and appropriate industry certifications is crucial for protecting the entire supply chain.
• Incident Response Planning: Having a plan in place is like having a fire extinguisher ready in case of an emergency. A well-defined plan ensures you can react quickly to a security issue, minimizing potential damage and restoring operations smoothly.

Building Trust: Transparency in Communication and Data Practices

In today’s data-driven world, trust is paramount when adopting new technologies like warehouse robotics. Both robotics suppliers and 3PLs  share a fundamental responsibility: safeguarding sensitive data throughout the fulfillment process. Transparency in data practices and unwavering accountability for security are key pillars in building this essential trust.

Given their visual nature, 3PLs and fulfillment operators understandably want clarity about the data pick-and-place robots collect and manage. Here’s where transparency plays a crucial role:

• Explicit Data Policies: Clear policies should outline data gathering, storage and encryption, retention and access controls.
• Customer Control: 3PLs and their customers should ideally have a degree of control over the data their robots generate. For instance, options to delete images after a set period can build trust.

In summary, proactive data responsibility is essential as warehouse robotics transform the industry. By understanding the risks, adhering to best practices and embracing transparency, 3PLs and robotics providers can build a secure and trustworthy foundation for the future of automated fulfillment.

About the Author

Gemma Ross is VP of operations at OSARO, a startup in San Francisco that designs and delivers AI-driven robotics solutions for e-commerce automation. Ross oversees solution delivery and the ongoing success of OSARO’s e-commerce and 3PL customers in the warehouse, logistics, and fulfillment sectors. Her experience includes roles at Kindred and DreamWorks Animation. Ross is a graduate of Dartmouth College with a degree in Computer Science. Contact Gemma Ross on LinkedIn.