Responsible Data And AI In The Time Of Pandemic And Crisis
Enterprises, corporate businesses, governments, and workers are exploring new methods to remain operational amidst the COVID-19 pandemic. Nationwide lockdowns, stay-at-home orders, border closures, and other safeguarding measures to contain the virus have made the working environment more complex than ever. Businesses are relying on technology solutions based upon artificial intelligence (AI) and data to formulate work processes that can function efficiently in the new normal. At the same time, government authorities and law enforcement agencies are depending upon contact-tracing technologies to preserve public safety while fighting against the deadly virus.
Some authorities have used cameras with facial recognition functionality to identify and track people traveling from an affected area. Similarly, police in Spain have implemented technology to impose stay-at-home orders with smart use of drones for patrolling and broadcasting important information to the public. At Hong Kong airports, people traveling from different regions of the world are required to wear monitoring bracelets that track their quarantine days and alert the respective authorities whenever they leave their houses. Likewise, a surveillance company in the United States has built AI-enabled thermal cameras capable of detecting fevers. Meanwhile, at Thailand airports, border officers are already carrying out trials on a biometric screen system with the help of fever-detecting cameras.
Such data-driven approaches, when misused, can raise human rights concerns — sabotaging people’s trust in their government.
In a time of crisis, we should tread this technology with extreme caution — only using it in a limited capacity with proper oversight. Bruce Schneier, a renowned American cryptographer and computer security professional, remarked, “data is the pollution problem of the information age and protecting privacy is the environmental challenge.”
More often than not, companies constitute their data governance practices that lay the foundation for data management and quality control. Right now, many organizations are creating new data and technology principles that help them function in the changing business ecosystem while safeguarding confidential data of all stakeholders. Companies that do not have a concrete set of guidelines risk mishandling data and violating privacy.
Companies need to start defining transparent and clear data usage guidelines — helping build a trustworthy reputation among employees, business partners, customers, and other stakeholders. Moreover, the companies should make sure that these guidelines and policies are applicable to both in-house development services as well as external development services.
With AI and data being used in abundance, it is essential to adopt ethical principles with proper planning. When you frame policies without figuring out all outcomes of AI-based solutions, there will be a gap between your practice and policies. So, before implementing AI in your business system or client’s solution, you should evaluate existing policies and add relevant policies about the use and effect of AI and data.
