by Angela Guess
Andrew Brust recently wrote in TechCrunch, “Data ethics is a subject our industry has largely ignored, avoided and failed to acknowledge as important. This neglect is almost certainly caused by fear — fear that examining the question would expose us as doing wrong; fear that ethics might stifle innovation; fear that the ethical questions are insoluble and intractable. Empathy is important; these fears should not be dismissed. But after some work with big data ethics analyst Kord Davis last year, I came to realize there’s also a good chance these fears are unfounded and overblown. Doing good needn’t contradict doing well. In most cases, data ethics are achievable, as long as standards and procedures can be thoughtfully explored, established and agreed upon.”
Brust goes on, “Perhaps more importantly, adherence to those standards and procedures can be made feasible with good technology. In other words, ethical data use can be productionalized and, in large part, automated, through the use of good tooling. Seen this way, data ethics is really a specialized area of data governance and stewardship.”
He continues, “We have to be careful not to oversimplify this, of course. Clearly, data ethics is not a problem that can be solved just by ‘throwing technology at it.’ As an industry, and as individual organizations, we need to discuss what should and shouldn’t be done with data. To what level is profiling of individual customers or constituents acceptable, versus doing everything at an aggregated level? What individual information is okay to store in plain text, in encrypted form or not at all?”
photo credit: Flickr/ regan76