AI for Human Security


Just imagine for a moment that you have a fight with your landlord. Perhaps he is unreasonably raising your rent. Or perhaps he expects you to pay for certain defects in the property which you are not responsible for. Whatever the scenario may be, let’s imagine for a moment that you and your landlord have a dispute and it escalates to legal proceedings. You file a small claim for US$5000 and expect to meet with a lawyer or plead your case before a judge. This might be true for almost every county and country in the world, except Estonia. Over the course of 2019, the Estonian Ministry of Justice, in conjunction with Estonia’s Chief Data Officer, have developed and piloted artificial intelligence (AI) software to hear and decide on small claims disputes less than 7000 Euros. The program is still just starting out and could potentially be the very beginning of a global wave of AI in the judiciary, but before all that happens, we must consider our past with integrating technology and the judiciary and carefully weigh the pros and cons. Estonia’s Chief Data Officer, 28-year-old Ott Velsberg, wants to “eliminate the human element. “Although this sounds frighteningly similar to images evoked in Brave New World, 1984, and other dystopian science fiction stories, automation has already been increasingly integrated into the judiciary. For example, across the world, digital cameras and software have completely replaced any and all need for human interactions with the police or judge in relation to traffic offences, such as speeding or running red lights. Should you exceed the speed limit, a camera simply takes a photo of your license plate, which links to your name, address, and registration information to forward you a fine, whose amount is predetermined. While that might have been met with hostility upon introduction, they populate roads all across the world without much notice or remark.
But of course, this is still starkly different from Estonia’s proposal of an AI judge. AI differentiates itself from machine automation through a slightly perverse sense of self-thinking and self-growing––the very characteristics that we humans use to differentiate ourselves from machines. By definition, humans possess skills that machines cannot; in the case of the judiciary, it is the ability to critically analyse a situation and be sufficiently flexible to decide on fair judgements while adapting to a range of scenarios and consideration factors. A simple input/output, of speed for instance, is ok, but a thinking, analysing entity? That sounds extreme.

Research methodology
In accordance with the objectives of the present study, qualitative method of research is used where secondary data is studied. The reports of committees and commissions have been scanned to sifting the issues relating to the research problem. A thorough analysis of content from sites like JSTOR, SCC and Westlaw were done to generate a better perspective.

Artificial intelligence (AI), or the power of a PC to finish intelligent tasks ordinarily performed by individuals, has been a trending topic within the law of late, and permanently reason. it’s the power to fully rework however lawyers work. AI has already been used for years with e-discovery platforms, however will AI even be utilized in another key space of proceedings, legal research? Even any, will it ultimately replace attorneys conducting these tasks? To handle these queries, I interviewed varied thought leaders within the legal business to work out the state of the art on AI usage and its potential to be used in proceedings. 2 corporations in particular—ROSS Intelligence and Thomson Reuters—are each victimization Watson, a psychological feature technology, to reinforce legal analysis. owned by IBM, Watson became noted for beating former human Jeopardy! winners in 2011. Watson has been busy within the legal business. ROSS is functioning to create Watson associate degree “artificially intelligent attorney” that you simply will raise a matter, very much like you are doing with Google’s search engine; it then generates results supported legal sources like legislation and case law.

While reading online that ROSS is currently collaborating with the global law firm Dentons through Next Law, the law firm’s research and development subsidiary, I asked Andrew Arruda, ROSS cofounder and chief executive officer, whether they had branched out. He replied that they have begun commercializing, and one of their first partners is BakerHostetler. Thomson Reuters Legal entered into a partnership with Watson in October 2015. While that was less than a year ago, I figured it might be interesting to see what was happening on the ground. Unsurprisingly, Watson results are still in development, but there are other resources that are currently available. Mick Atton, chief architect, emphasized that AI has been used to enhance Thomson Reuters legal research products since the early 1990s. Mike Dahn, global head of Westlaw Product Management, stated that one of the company’s best-known legal research products, Westlaw, relies on two AI concepts in particular: NLP and machine learning. As an example, Dahn remarked that West Search, which is the search engine of the company’s updated legal research
product called WestlawNext, was designed to mimic the behaviours of expert researchers, including actions such as selecting, sharing, or printing a case. Further, according to Dahn, the system is composed of a collection of learning-to-rank algorithms that were trained on legal content, metadata, and user behaviour. In January 2016, the company also launched recommender systems to help customers finish research faster.

These new tools analyse usage patterns during the session and make recommendations mid-session or within Westlaw folders. At the end of the day, Dahn reflected, “our enhancements in recent years represent a significant leap forward, but we’re far from done.” Khalid Al-Kofahi, vice president of research, also noted that WestSearch, which was launched in 2010, represents a “significant leap in scale and complexity in applications of natural language processing, machine learning, and information retrieval.” That said, Al-Kofahi is very focused on the future. “Our ultimate objective is to develop smart machines that truly understand the legal domain, the task, and the user—machines that enable more robust and natural interactions with the user, not just to respond to user input but also to proactively support the user in the research task. Such a general-purpose machine is probably years away.” Al-Kofahi added, “our partnership with IBM Watson will accelerate our solution development. So, stay tuned.”

Khalid Al-Kofahi, vice chairman of research, conjointly noted that WestSearch, which was launched in 2010, represents a “significant leap in scale and complexness in applications of language process, machine learning, and data retrieval.” That same, Al-Kofahi is very centred on the long run. “Our final objective is to develop good machines that truly perceive the legal domain, the task, and therefore the user—machines that change a lot of sturdy and natural interactions with the user, not simply to retort to user input however conjointly to proactively support the user within the analysis task. Such a general-purpose machine is perhaps years away.” Al-Kofahi adscititious, “our partnership with IBM Watson can accelerate our resolution development.”
Several tools out there use AI to benefit the litigator’s analysis wants. For large law companies needing to leave on AN innovation limb, teaming up with ROSS Intelligence may enhance legal research by creating the method faster and generating a lot JSTOR

of targeted results. Attorneys United Nations agency concentrate on intellectual property legal proceeding may think about using Lex Machina to strengthen legal proceeding case strategy. Those seeking a lot of ancient, however forward-thinking programs may use Thomson Reuters or Bloomberg Law to augment typical legal analysis. And these square measures simply these tools. More are on the horizon, thus it’s solely possible to urge better. Attorneys involved concerning being replaced by AI needn’t fret as a result of based on these thought leaders, AI is being developed to not replace attorneys however to help them.

For the Estonian and Chinese governments, the benefits are clear. AI judges are faster, they can process multiple cases at the one time, and they can find relevant legal documents almost instantly. Not only is this beneficial for the judges to focus on more important rulings, it is also helpful for the citizens who do not want to be caught up in the lengthy, expensive, and stressful litigation process. AI judges also have the potential to be fairer than human judges. A joint study between Australia’s Swinburne University Law School and Queensland University of Technology found that courts in the status quo were influenced by arbitrary factors like race or socio-economic status. Moreover, because the judiciary as a collective body is composed of hundreds, if not thousands, of different judges, lawyers, and legal professionals, judgements were inconsistent across different courts. To illustrate, the study found that one court in Victoria, Australia’s second most populous state, was three times more likely to imprison offenders than other courts in the state. One centralised, consistent judge would be the logical solution, a physically impossible feat until now, with the development of AI. Moreover, in the particular case of AI lawyers as is in the United Kingdom, legal representation and just recourse has become much more accessible. The biggest criticisms of the legal system are that it is too expensive to hire a lawyer and many are not aware of their options in gaining legal advice. A digital system allows individuals to access legal services for free and in their own time. This means that for the low and middle class, they can navigate any legal disputes for free and get the justice they deserve without having to sacrifice a work day or substantial portions of their salary.
Park, J. (2020). YOUR HONOR, AI. Harvard International Review, 41(2), 46-48. doi:10.2307/26917302

Like with any technological innovation, the potential for hacking proposes a substantial risk. This is particularly important when concerned with legal matters. Although the systems presently do not involve high stakes cases such as criminal trials, the courts have the potential to save or ruin lives, build or cripple companies, and set incredibly significant social precedents whose effects flow on for centuries. Already, the world has seen the impact of hacking into other branches of government through cases like electoral interference, and more technological integration into the judiciary is an invitation for vulnerability. Moreover, because AI relies on having a vast database of past cases to then predict judgements for future cases, AI judges would recreate the past mistakes and implicit prejudices of past cases overseen by humans into perpetuity. AI does not have the capacity to adapt flexibly with the social mores of the time or re-calibrate for errors of the past. And when the courts are often used as social barometers with an ear towards the changes in social norms, it is imperative that the judges are not informed solely by the past.

Notwithstanding the mundane aspects of AI governance, terribly real challenges lie ahead. We reside through an amount of transition between 2 epochs: Associate in Nursing industrial era characterized by certain works labour, and a new digital era characterised by widespread institutional unravelling. during this new century, the u. s. remains a formidable power, but its days of unipolar form of government have come back to an end. The laborious reality is that technology is disrupting the politics and regulative landscape, driving the requirement for brand new protocols and new regulative regimes. Without a doubt, the foremost advanced governance challenges encompassing AI these days involve defence and security. From killer swarms of drones (Future of Life Institute 2017) to the computer-assisted sweetening of the military decision-making method (Branch 2018), AI technologies can force multiply the capability of nation-states to project power. whereas the temptation to use the non-proliferation lens for the other reasonably AI technology (for example, ban all killer 4 Park, J. (2020). YOUR HONOR, AI. Harvard International Review, 41(2), 46-48. doi:10.2307/26917302 robots!), the dual-use challenge remains a similar. A killer golem isn’t a selected reasonably technology. It is, instead, the results of the recombination of AI “ingredients,” several of that also are used to, for instance, observe cancers or increase driver safety. Over and on top of the present COVID-19 crisis, data-driven technologies are provocative a massive geo-technological restructuring (Khanna 2014). In this new setting, AI and machine learning are set to reshape the principles of the game. As Google’s Sundar Pichai (2020) wrote early this year in Associate in Nursing op-ed for the money Times, the time for correctly regulation AI technologies is currently. As within the post-war era, what we’d like may be a new reasonably quadrilateral system to administrate an extremely technological civilization. Sadly, abundant of the prevailing governance design lacks the capability to address the wants of a data-driven economy. Nonetheless, most governments are already beginning to explore new rules, even as approaches vary. Given the size of the changes ahead, we will need to take into account the suitable regimes for regulating AI. as luck would have it, this doesn’t mean starting from scratch. whilst regulative compliance problems around AI proliferate, many existing regulative systems and frameworks will stay valuable. Indeed, whilst the final varieties of several AI technologies dissent, the underlying ingredients are shared. And even as consumer protection laws hold makers, suppliers and retailers responsible, so the plethora of AI-driven product and services can be equally regulated. notwithstanding, looking on the far side the mundane regulation of AI, several huge challenges stay. determination these challenges can mean rethinking a waning multilateral order.

The arc of the judiciary towards AI integration has been associate degree exceptionally slow one, and it in all probability are going to be terribly slow within the future. And with simply reason, since the court system is one in all the foremost impactful establishments within the world and one steeped in deep tradition and history. Any new step should be enamoured extreme caution and be created positive that it’s so a step within the right direction. On one hand AI guarantees potency, consistency, and accessibility. On the opposite hand, it risks vulnerability to external influence and propagation of past injustices. ought to justice be compromised for speed? What role will human interaction play within the justice system? Is associate degree unemotional, strictly consistent mediator even a decent thing? however will technology grow with the times? Going forward, legislators and innovators alike should grapple with these massive challenges.

Sejal Gupta
Research Intern
Institute of Law, Nirma University

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