Big Data, Analytics, and Technology’s Impact on Society Lyria Bennett Moses and Greg Adamson March 2017 The social implications of technology have been with us for as long as humans have created technology, which is to say as long as we’ve been human. In Paleolithic times, stone tools could be used to kill game or fellow humans. In Greek mythology, Icarus’ hubris was enabled by technology. In our time, headline revelations about National Security Agency spying, Anonymous’ hacking, and security breaches at Sony, at Target – you name it – no longer shock us. And now, appearing on the horizon, the Internet of Things (IoT) is arising with the “promise” of ubiquitous sensors, and big data analytics to improve our lives and, yet, along with it may come opaque algorithms and a growing sense that, perhaps, George Orwell will be proven prescient [1]. It’s been said that technology is neither good nor bad, but neither is it neutral. Technology does indeed have major, often unforeseen or poorly understood implications for society. Granted, this is the stuff of daily conversation – How secure is our data? How private are our conversations? How long before a trove of data defines our lives in the eyes of others using an opaque algorithm? We would argue that the dynamics of the market may blind some technologists to the implications of their work, while for others, creativity is the driver and reflection is an afterthought. Conversely, policymakers too often do not fully grasp the implications of technological developments, and how these interact with existing laws and policies. Where policymakers make mistakes, there can be a significant impact on the community. We come to the social implications of technology from two different backgrounds, but our interests intersect where automation and the use of algorithms can produce – or reduce – social value. Our challenge is to grasp the ethical and legal implications and impacts of such tools in a potentially sensitive context. For instance, governments and agencies are accumulating data on everyone: should algorithms be applied to tease out insights, particularly in the name of preventing crime and terrorism? To ensure that the use of these tools does not spin out of the control of a democratic society that applies them, we need to ask questions. “What do agencies want from such data?” “What biases are inherent in the algorithms that produce results?” Perhaps most importantly: “What legal frameworks should society impose for positive, just outcomes?” At first blush, algorithms just perform automated analysis at high speed, right? But it’s more complicated than that. Not to put too fine a point on it, but a recent op-ed in The New York Times – “Artificial Intelligence’s White Guy Problem” – points out that cultural biases seep into algorithms. To quote briefly from the article: “Like all technologies before it, artificial intelligence will reflect the values of its creators. So inclusivity matters … Otherwise, we risk constructing machine intelligence that mirrors a narrow and privileged vision of society, with its old, familiar biases and stereotypes … [and] we will see ingrained forms of bias built into the artificial intelligence of the future.”