The debate about the replacement of lawyers by machines is already a cliché cropping up at most industry conferences and seminars, as many lawyers see themselves as threatened by this possibility considering the extraordinary capacities the technology is acquiring. If we focus on the advanced artificial intelligence and document automation tools currently being used in the industry we can say, without fear of contradiction, that jobs at law firms really are going to be destroyed. This phenomenon will even redefine the structure of the biggest firms, the early adopters of these technologies, for which these tools are already almost essential elements for providing service to clients, for example when dealing with due diligence for merger or acquisition processes. These firms will require fewer lawyers to do those jobs. But jobs related to document analysis are not the only ones that will be transformed by the new technology.

The success of machine learning algorithms has created a wave of excitement about the problems they could be used to solve. Already we have algorithms that match or outperform humans in nontrivial tasks such as image classification [18], the game of Go [37], and skin cancer classification [15]. This has spurred the use of machine learning algorithms in predictive policing [25], in loan lending [17], and to predict whether released people from jail will re-offend [9]. In these life-changing settings however, it has quickly become clear that machine learning algorithms can unwittingly perpetuate or create discriminatory decisions that are biased against certain individuals (for example, against a particular race, gender, sexual orientation, or other protected attributes). Specifically, such biases have already been demonstrated in natural language processing systems [5] (where algorithms associate men with technical occupations like'computer programmer' and women with domestic occupations like'homemaker'), and in online advertising [41] (where Google showed advertisements suggesting that a person had been arrested when that person had a name more often associated with black individuals).

"We live in a network world. Everything we do is an outcome of multiple elements. The pervasion of social media in our lives means hundreds and thousands of tweets and retweets by the minute. Gone are the times when information asymmetry was exploited," remarked Dr Alok Chaturvedi, professor of Management and Computer Science, Purdue University while initiating a talk at ORF Delhi on Big Data and Agent Based Simulation for Policy Analysis on 8 May, 2018. The discussion was moderated by Rakesh Sood, Distinguished Fellow, ORF and a former ambassador.

Subscribe to receive updates on Industry 4.0 The Fourth Industrial Revolution is upon us. The first three were based, respectively, on mechanization, mass production, and computing/automation; Industry 4.0 is all about the marriage of physical and digital technologies. Just as with the previous revolutions, Industry 4.0 is disrupting and redefining industries. This time, however, the revolution is progressing with unprecedented speed, driven by smart, connected technologies that are developing at an exponential rate.1 These technology innovations--including cloud computing and platform technologies, big data and analytics, mobile solutions, social and collaborative systems, Internet of Things (IoT) technology, and artificial intelligence (AI)--are fueling and accelerating a new era of digital business transformation. They're reshaping how organizations work, innovate, and create products--and enabling completely new kinds of products and services.2 They're spurring businesses to invent new business models and reimagine how they deliver value to their customers and markets. More broadly, industry boundaries are expanding and blurring, and relationships with business partners are being redefined. Yet too many organizations remain unprepared for the new revolution. A recent Deloitte Industry 4.0 study of C-level executives around the world indicates that, across all industries, only 14 percent of CXOs are "highly confident" that their organizations are ready to harness the changes associated with the new era.3

Last December, a U.S. National Security Strategy (NSS) declared artificial intelligence (AI) "critical to America's economic growth and security," but warned that China and other countries have attempted to "steal U.S. intellectual property" in the field of AI. To be fair, China has made great strides lately in strengthening its own enforcement of patent rights. Nonetheless, the NSS warned that stronger efforts were needed by U.S. companies to "curtail intellectual property (IP) theft by all sources" of our cutting-edge AI research. But as telecommunications giant AT&T and other firms can attest, only human intelligence can stop the theft of artificial intelligence. AT&T deploys a sophisticated suite of AI tools to manage the nearly 200 petabytes of data traffic that flows through its global telecommunications network every day (equivalent to 100 trillion pages of printed text).

This blogpost was co-authored by Mark Latonero, PhD, Data & Society Research Lead, Data & Human Rights and Melanie Penagos, Data & Society Research Analyst, Data & Human Rights. The first blogpost in a series on Artificial Intelligence and Human Rights, it summarizes a multidisciplinary workshop held at Data & Society on April 26 and 27, 2018. Multiple sectors of our global society are grappling to make sense of how AI may transform or alter the way we live, work, and relate to one another and our institutions. At the same time, "Artificial Intelligence" is a slippery and highly contextual concept -- the way a mathematician defines AI can diverge significantly from a marketing executive or a causal reader of science fiction. This tension makes discussions about norms that could shape or regulate AI systems a thoroughly contested and challenging space.

When we're asked, "What is artificial intelligence?" Perhaps it's a sassy-talking technology like Siri from Apple, or helpful humanoid counterparts like those depicted in The Jetsons. Some might even imagine sophisticated robots threatening to extinguish the human race. Nowadays, there are as many definitions of AI as there are companies trying to pitch AI solutions. So, how do law firms know how to incorporate artificial intelligence?

Artificial intelligence (AI) has the potential to be human rights' best advocate and its worst enemy. Either it can help us reach the UN's Sustainable Development Goals (SDGs) or, to quote internationally renowned AI scientist Yoshua Bengio, it can "increase discrepancies between the rich and the poor and be a threat to democracy." Fears of job loss and psychological manipulation are real and require a united front. To help us better understand and shape the social impacts of AI for the greater good, the inaugural conference AI on a Social Mission was held last month in Montreal. "AI is both a hope and a danger," warned Bengio, who was the keynote speaker at the conference.

Nuclear bombs can destroy us. Artificial intelligence (AI) and robots can enslave us (or, worse, take our jobs). Synthetic biology and gene-editing have humans playing God. Social media make us depressed: we've never been so connected yet never so alone. Those are just a few of the complaints levelled against technology.

Digital services have frequently been in collision -- if not out-and-out conflict -- with the rule of law. But what happens when technologies such as deep learning software and self-executing code are in the driving seat of legal decisions? How can we be sure next-gen'legal tech' systems are not unfairly biased against certain groups or individuals? And what skills will lawyers need to develop to be able to properly assess the quality of the justice flowing from data-driven decisions? While entrepreneurs have been eyeing traditional legal processes for some years now, with a cost-cutting gleam in their eye and the word'streamline' on their lips, this early phase of legal innovation pales in significance beside the transformative potential of AI technologies that are already pushing their algorithmic fingers into legal processes -- and perhaps shifting the line of the law itself in the process.