Should a K-12 education system collect data from school laptops to assess student performance? Or a car manufacturer collect and share data on vehicle trips to inform smart city programs? Or should a maker of sensor-equipped industrial equipment use IoT data to make product improvements and sell insights?
Organizations could argue that collecting these types of data enables them to improve service and offer broader social benefits. Conversely, students or drivers or customers could argue that using this data violates their expectations about how data is collected and used.
“ Few consider ethics until there’s a problem. Only then do they stop to consider the potential risk”
Data ethics dilemmas like these are becoming more urgent as business leaders look to data and analytics programs to produce business value.
“As more organizations look to benefit from data, there will be an inevitable increase in data use and sharing missteps,” says Lydia Clougherty Jones, Senior Director Analyst, Gartner. “Organizations with an ethics culture will be better prepared to avoid missteps altogether or handle them effectively when they occur.”
Gartner defines “data ethics” as a system of values and moral principles related to the responsible collection, use and sharing of data. Data ethics violations range from overt and public to subtle and secret — like algorithms that suggest higher interest rates for minority mortgage applicants or lower lines of credit for women credit card applicants.
Whether overt or subtle, ethics missteps are bad for business. Affected stakeholders are left feeling that a promise — implicit or explicit — has been broken. Explanations based on after-the-fact analysis appear, when viewed through an ethics lens, disingenuous — even hypocritical. For organizations, the crisis is often a surprise, as few consider ethics until there’s a problem. Only then do they stop to consider the potential risk of unintended consequences.
There’s another way. For a more proactive stance, take these three actions.
Shift the organization’s data governance mindset
Many organizations approach data governance as a set of hard-and-fast rules, guided by data protection regulatory requirements like the European Union's General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). Unfortunately, a fixed approach to data governance is ill-suited to today’s rapidly changing digital environments. Data ethics also encompasses far more than privacy and security compliance.
Shift the governance mindset away from command-and-control or one-size-fits-all toward adaptive governance instead. With adaptive governance, organizations determine the right governance styles and mechanisms for a given context.
“ Organizations need an active and vocal data ethics leader at the helm with authority to drive ethical standards”
“Data-sharing strategy for intentional impact must exist within an adaptive ethical framework to balance risk with contextual opportunity,” says Clougherty Jones. “Building trust with emerging technologies is essential, along with aligning data and analytics strategy to organization goals.”
An adaptive approach invites leaders from different functions to collaborate on data ethics principles to guide decision making, while acknowledging that new circumstances may arise for which there is no precedent. Thoughtful leadership discussions about what it means for the organization to do the “right thing” helps provide a framework for ethical thinking and decision making.