I have been a data guy throughout my entire adult life. Today I am in the twilight years of a data career that spans more than 5 decades. It has been a tremendously rewarding career, and I can’t imagine any other field that would have kept me fascinated for 50 years. I’ve seen the evolution from punch cards to graph databases and from simple accounting to machine learning. We’ve come so far, yet it seems that we have missed something that is really important. 

When I observe the common uses of data today, I see a predominant focus on sales, marketing, and competitive positioning. We collect data about people without their knowledge, then use it aggressively to persuade them to buy the things that CRM algorithms say they are most susceptible to purchasing. Let’s remember that CRM is an acronym for Customer Relationship Management. Do we really think the most important customer relationships are those that let us reach deep into their pockets to generate more revenue?

The corporate world thinks of people first as “consumers” and not as humans and individuals. That perspective on people tells a troubling story. The majority of data applications today pursue increased market share and continuous upward growth of profits. When the value of data is measured only by the impact on the bottom line of financial statements, we have missed the point and we have lost our way.

In 2017, some of the great minds in the world of data—John Ladley, Kelle O’Neal, Danette McGilvray, Tom Redman, and James Price—introduced The Leader’s Data Manifesto. The manifesto states that “Data offers enormous untapped potential to create competitive advantage, new wealth, and jobs; improve healthcare; keep us all safer; and otherwise improve the human condition.” 

Let’s pay some attention to those last 4 words: improve the human condition. I’m certainly not saying don’t make a profit. We all want and need profitable companies. But I sincerely hope that your company and all companies have other goals—greater goals than profit making. Look beyond the economic goals of your company. Look for social, community, environmental, and ecological values and goals. We should invest in data initiatives to make a difference here too.

I don’t want to paint a picture that is all darkness. I’ve participated in projects that use data to bring healthcare to those most in need, to improve the experiences of and outcomes for children in foster care, to make meaningful advances in cancer research, to combat animal abuse and promote dog rescue, and to make effective use of limited resources available for the jobless and the homeless. Yes, I’ve had frequent opportunities to work in areas that apply data to improve the human (and canine) condition. But I must point out that most of this work is pro bono—volunteer work done to make a difference while working in other areas to make a living. Hasn’t the time come to actively invest in making a difference?

I’m also concerned about the risk side of data in today’s world. We collect more data now than ever before—personal data, behavioral data, location data, and more—often without knowledge and consent of the data subjects. We sell it, trade it, and otherwise monetize it without paying a cent to those whose data we covertly collect. We govern the data erratically, protect it badly, and operate without data ethics frameworks and principles. Data is the fuel that powers fraud, enables identity theft, and supports active and malicious manipulation of information and individuals. Without conscientious governance, protection, and ethics we give implicit consent to these activities.

The ways that we use data have many inherent risks. There are hidden dangers in algorithmic decision making. Data is imperfect and algorithms often have built-in biases—biases that all too frequently have traumatic impacts on individuals and families as in this example of facial recognition gone wrong. Cathy O’Neil describes the risks of algorithmic dependencies and decisions in depth in her book Weapons of Math Destruction. We have yet to master data governance and data ethics. And now we need to step up to algorithmic governance and data science ethics. The abundance of data and the immense power that we have to process data bring both opportunity and risk. It is a grave error to pursue the opportunities without also making a serious commitment to managing the risks.

Yes, data is informative and valuable—sometimes even invigorating and exciting. But we use it badly with too much attention to profits and too little attention to people. Data has a dark side of misuse and abuse. We are failing to step up to the real value opportunities of data—to improve the human condition—and we are failing to mitigate the risks inherent in modern data capabilities.

We—the data professionals—are the ones who can change this. Shine a light on the dark side. Become a leader in the push for data ethics. Be vocal about the risks of data. Be even more vocal about the missed opportunities to use data for community and social impacts. Go to the Data Leaders website and sign the manifesto. Data is pervasive in all of our lives. Let’s do all that we can to achieve the maximum social impact of data with minimum risk.

There are hopeful signs as social issues such as public health, equality, and human rights begin to find a place on corporate agendas. We see the signs in what is being called the Data for Good movement. It is a beginning, but only a small step that is not yet enough. Data for good should be the norm, not the exception. It should be a core value, not an afterthought. Look forward to more about this topic in the upcoming (November 2020) report Data for Good: Industry Initiatives to Improve Social and Economic Well-Being by my colleague Kevin Petrie.

This is my call out to everyone—data leaders, data professionals, business leaders, business professionals—to pursue two priorities: use data to drive social change, and do no harm with data. I’m sure that some readers will dismiss this as the mad ravings of a left coast liberal. I will acknowledge and accept everything except the “mad” description. Please view this as the sane ravings of a left coast liberal. We can and should use data to do well and to do good at the same time.