They decide who passes and who fails in secondary school. They decide who gets arrested and who goes to prison. They decide what news you see first thing in the morning as well as what news you won’t see. And they drive the business models—and revenues—of the world’s largest and most powerful digital platforms.
In spite of all this, many of the world’s most powerful algorithms are accountable to no one—not even the companies that build and deploy them. Some have made vague pledges to “be ethical,” and for all we know, there may be strong policies or rules that the companies follow behind closed doors. But the overall lack of public explanation of how these systems are built and run indicates that companies do not have oversight over how their own systems work. In light of the enormous effects that they have on human rights, public health, public safety, democracy, and our understanding of reality, this is nothing short of reckless.
For the 2020 RDR Index, we looked for companies’ answers to some fundamental questions about algorithms: How do you build and train them? What do they do? What standards guide these processes?
We combed the public-facing documentation and, to no surprise, found very, very little. Yet companies are harvesting user data by the minute, to fuel algorithmic optimization, engagement, and personalization—all things that translate to enormous profits.
“…our findings suggest that much of the technology driving revenue for the world’s most powerful digital platforms is accountable to no one—not even the companies themselves.”
In the absence of this information, all we have is a set of clues. Companies offer small hints at how their systems work, both in their policies and in public statements. Other information has bubbled up through investigative journalism efforts and technical research. With our findings from a new set of indicators that evaluate company disclosures on algorithmic systems and targeted advertising, we seek to contribute to these efforts, by putting what we have learned into the broader context of what is publicly known about the algorithmic systems of digital platforms.