In general, I think companies stink at thinking ethically, particularly when it comes to technology.
As long as I’ve covered technology, there always have been pieces urging companies to consider the ethics of using new technologies. But who really does? After all, the competition is certainly going to use it. We read these warnings, we may even agree with these warnings, but in the end, we’re rushing to compete and there’s no time for addressing these warnings.
I think it’s a lack of process, but also a lack of integrating any ethical discussion into project management. Ethics is often seen as the responsibility of legal or the corporate social responsibility team or the executive team — anybody else, any place but here, any time but right now. So the work pushes forward without undue thought as to whether it should.
When there’s no process in place, no time or place for evaluating the ethics of a technology, then you’re flipping the ethics coin each time you launch a project.
Personally, I think the failure to consider ethics is in and of itself unethical — regardless of whether the outcomes are for good or bad — because it shows a complete disregard for the consequences.
This lack of thought inevitably will lead to some unethical actions, particularly as technology enables us to integrate more and larger datasets.
By integrating ethics into data governance, you could help change that, and possibly save your organization a lawsuit, contends Forrester Research Senior Research Analyst Michele Goetz.
Goetz recently raised the issue of ethics in data governance, pointing to two technology projects that put data to work in an innovative, but ethically questionable way: A mashup that matched gun owner data with a map, and an interactive map that allowed you to find individuals across the U.S. and Canada.
"Why is this game changing for data governance and why should you care?” asks Goetz. “It begs us to ask, even if a regulation is not hanging over our head, what is the ethical use of data and what is the responsibility of businesses to use this data?”
As she points out, it’s not just about the data steward and who owns the data within the company. On a deeper level, the real data owner is the customer or partner or whoever that data describes.
Governance talks about data ownership, but in reality, what it often addresses is the custodian of the data, Goetz argues.
“The owners of data more often than not will sit outside your corporate walls. Data governance has to take into account not only the interests of the company, but also the interests of the data owners,” Goetz writes. “Companies have to consider policies that not only benefit the corporate welfare but also the interests of customer and partners or face reputational risk and potential loss of business.”
But are companies putting into place the needed time, questions and space to address that responsibility, even during data governance? I’m not so sure.
Recently, I read a piece by Manjeet Singh Sawhney that advocated an agile approach to data governance.
“The best way to implement Data Governance successfully is to take an agile approach and make it work for one subject area before moving to the next,” Sawhney writes. “This makes it an iterative approach and can be reapplied again and again with other subject areas which should be governed.”
That’s not an unusual recommendation, and from an internal view, it’s certainly going to be productive. But it’s a siloed, project-based approach, and that has consequences, I think.
For one thing, it’s unlikely to create the high-level thinking you need when evaluating ethics. It’s project-focused, and unless the participants are hyper-aware of the far-reaching, long-term consequences of what they do, it strikes me as an unlikely place for real ethical discussions.
For one thing, a project-level team that’s trying to “prove” data governance can work may not even have the right players at the table to enforce any ethical decisions.
One way to ensure that it does it to choose a data governance framework or methodology that includes an ethics component.
“Data governance programs are well established and proven to manage risk and data, and a good data governance framework will accommodate the ongoing need to evolve the program in an organization,” John O’Brien, CBIP, principal and CEO of Radiant Advisors, pointed out in a TDWI article on governance.
Even so, that may not be enough if individuals aren’t sure about the ethical philosophy of the company, not to mention the legal issues concerning customer data.
That’s why any data governance team should include someone who’s familiar with or (better still) responsible for corporate ethics. That person may be found in the corporate social responsibility program, legal division, human resources or even at the CXO level, but you need to involve someone who can speak to the ethics of your company.