Joanna Crews
John Kendall, border and national security program director at Unisys‘ global public sector business, has stressed the need for security safeguards when employing artificial intelligence and machine learning for border protection.
In an article published Friday on Nextgov, Kendall espoused the benefits of microsegmentation, multifactor authentication, resilience and human analysis for the protection of intelligence programs and networks that support border and customs agents.
“Intelligence analysis produced by AI tools will be a great step forward for border security agencies and for our safety,” Kendall wrote.
He explained that machine learning systems would compile data from federal, state and local agencies and law enforcement organizations, along with social media accounts, travel histories, bank records and criminal histories.
“However, the public will support the use of the tools only if they are assured their personal data and privacy are protected,” Kendall added. He cautioned that data access and storage must comply with local and international laws, and feature robust security protocols built into the network’s foundation.
