by Aisha Rawert
Rapid technological change in the magnitude and proportions of the current disruptions arising from Artificial Intelligence (AI), robotics, machine learning, and blockchain have the potential to immensely change society at the core. They may not only improve the laws of commerce, industry, or constitutional preponderance but also influence the legal profession by availing machine-mediated processes in the contracting and litigation procedures in the judicial arm of government and private practice[1]. Artificial intelligence and robotics will enable machines to perform roles traditionally assigned to humans who had legal personality and legal culpability wherever they acted errantly. However, computers and robots will engage a more significant influence in commerce and industry while they do not possess legal personality and, therefore, their errors may be hard to prosecute and tender legal redress. These concerns have created an urgency of theoretical and historical analyses seeking to find a suitable middle ground for the future of technology and society.
This article attempts to map the influence of technological disruption led by Artificial Intelligence, Blockchain, and Machine Learning on how regulations and laws can be sustainably applied in the field. The discussion explores a brief literature review that addresses advances, and theoretical lenses of public law practice and institutional preponderance on the subject then delves into topical concerns in the field. The specific influence of technology in the legal profession and the particular interests of disruptive technology are treated to extensive analysis. The last section discusses the political ramifications and the possible effects of the overall changes on international relations. This article underscores the altruism that the quest to improve exponentially, the precision of technologies in addressing problems in society through cost-effective means has shown a growing impetus in many segments of the economy and the process is gaining momentum across the globe.
The critical concern with disruptive technologies like AI and blockchain in administrative law is how to formulate and enforce new regulations, which will manage the rapidly changing typology of incessant disruptions of the present times and the future without adversely altering society in manners that are unsustainable. Technological disruption has seen completely established corporations fall and crumble like the famous case of Kodak and Nokia because they simply did not adjust to emerging models and modes of operations. Innovation may disrupt the delicate balance between regulators, consumers and the industry creating risks rather than safeguarding wellbeing[2]. The internet itself is a quintessential case of how immensely technological innovation can solicit far-reaching legal changes in the mode of business operations. Administrative laws have recently embraced the disruption theory effectively to carter for the pace of change witnessed in society.
A far greater danger lies in the formulation of rules or legislation without an accurate understanding of the pace and direction of change through disruptive innovations. Alternative enforcement mechanisms, rather than laws, might be the best option in dealing with the exigencies of change emanating from disruptive innovations. The poorly calibrated and premature rulemaking would jeopardize the natural pace of progress and the impetus for spontaneous innovation, which has addressed the problems of society more accurately and effectively. Public interest has always demonstrated that considerable restraint and fortitude among legislators and policy deliberations is a suitable thing when it comes to restraining programs of innovation and technological advancements.
The contemporary technological potential for disruption in the industry and in the fair or just preponderance of society is immense. Social media platforms have become places where a massive private date is often harvested, and many users are not fully aware of the possibility of compromises to privacy that take place. The recent Cambridge Analytica and Facebook fiasco was a small expose of what technology can do in political elections. Blockchain technology may facilitate immense processes for supply chain efficiency and payment systems on a global scale than ever witnessed before. Machine learning enables robotics and other mechanized systems to execute reinforcement learning, facilitating AI to correct their previous mistakes in the manner humans do. In this regard, beyond programming prototypes established in the law will find no basis to victimize the programmers because machines do their own learning to cope with the tasks assigned.
Traditionally, the functions of the legal systems only found culpability in machines when the programming violated established guidelines. Developers and programmers were thus keen to execute codes that upheld legal precedent. Whenever the process yielded identifiable negligence or foreseen harm, the developer was liable. In a New York case in which a robotic gantry-loading machine caused injury to a worker, the company was not held accountable[3]. The futuristic challenge is that machines can create their own adjustments through reinforcement learning. Nevertheless, reinforcement learning in computers can be optimized to a particular pedigree and the legal tags ascertained to the excellent learning pedigrees standards. Today’s regulations have to a limitation as to the extent machine implements will bear legal culpability in the multitude ways they have penetrated our lives and disrupted society in ways the masses will never understand and, therefore, popular politics cannot intercept.
The deployment of AI depends immensely on the quality of data that can be obtained to facilitate the learning process. In fields where data does not contravene privacy laws as established in law, there will be a rapid advancement, and in sectors where most of the data is regarded as privacy, the process may have to wait until the laws are adjusted to facilitate progress. Nonetheless, many people are volunteering personal and private data through the various apps they voluntarily install in their gadgets. The progress in the voluntary production of personal data online makes it easy for AI to yield solutions to most of the problems faced in the contemporary economic and political arrangement, which is expected to change radically into the future.
The legal practice is one of the critically affected professions by the rapid advancements in the fields of AI, machine learning and robotics. This is because companies are developing databases with effectively classified cases and adopting machine learning techniques to yield machines that can do all the tasks lawyers do more accurately and efficiently. The entry-level lawyer tasks can be executed by the new AI machines adopted in the field because through algorithms, and machine learning, all the data based jobs performed by lawyers will be taken over by robots. Many companies have ventured into the business of facilitating legal data to the algorithmic technologies and big data to create the legal machine robotic equipment, which will radically change the legal profession forever[4]. Although deep legal expertise is needed to build the systems that effectively take up the roles of lawyers in critical litigation encounter, that expertise and facility are already available because most of the legal literature exists in elaborate detail in online databases.
It is predictable that the introduction of these technologies in the fields of legal practice will produce efficient dispute resolution, greater judicial transparency, and better access to justice for corporations, and the rapid pace of legal services delivery. Natural language processing (NLP) capabilities and machine learning will introduce critical functionalities, which lawyers have never exhibited previously because these computational techniques will integrate statistical functions and economic analytics in making legal decisions. The legal profession underwent crucial scrutiny during the 2008 meltdown, which has revealed critical economic flaws in the charging of legal fees for corporations and the need for automating the entire process of the law cannot be gainsaid in a world seeking greater efficiency and transparency in the law[5].
The very nature of AI technologies is that they are advancing rapidly to optimize machine functions to mimic almost prototypes of human performance. In very specialized professional tasks like in the banking sector, these AI artefacts will almost replace all social engagements and employment with mechanical processes. The need to allow time for AI and other futuristic technologies to shape the future with minimal restrictions and regulation is the fact that these technologies depend on data, which has not been acknowledged in the design of traditional societies, which prized privacy more than efficiency and progress. However, the sophistication created by the recent demographic trends and technology penetration in society points to the urgent need to value productivity and growth more than privacy. Nonetheless, the law has always lagged behind because it depends upon a process of deliberation fetching all its mantra from history and laying its base sentiment on the past rather than a futuristic prediction in a disrupted society.
Policy debate focusing on the disruptions created by AI in the fields of medicine, transportation, security, labour, criminal justice, safety and national security have advanced critically, and there is the impetus for recognizing sweeping changes in these critical fields[6]. Nonetheless, public debate and awareness have critically lagged behind in the face of these sweeping changes; this calls for worry because public scrutiny and discussion is a useful component of a robust public policy formulation and ratification process. The Paris-based intergovernmental organization, the Organization for Economic Cooperation and Development (OECD), as a leading think tank has modelled policy considerations and concerns regarding the safe and sustainable deployment of AI policies among the member states. Many other policy institutions and parliaments across the globe are grappling with efforts in a similar manner.
It is noteworthy that AI will unfold differently in different industries, and the most conspicuous incidences in the United States has underscored the influence in Autonomous Vehicles (AVs). The U.S. government considers varied policies regulating speed and environments for which the first-generation deployment of AVs will be executed. In aquatic and aerial systems, the policy deliberations harbour considerable restraint due to the existing complexities particularly within sophisticated city terrains with skyscrapers. Experts contend that as AI advances, it will address most of the challenges perceived to come with it because technology keeps getting better when it can access suitable data that will be used to execute learning functionalities inbuilt in the systems.
While humans have a legal personality and are liable for prosecution whenever they break the law, machines may violate the law but how would they be punished or deterred from involving in criminal activity is a significant challenge. Autonomous machines or artificial intelligence entities have a critically different personality from natural humans, and it will be necessary for the industry to develop new legislation based on the sciences and technologies of their function to remedy instances of disputes emanating from their flaws and incompetence or errors. It is only through this orchestrated and scientific approach that effective laws can be produced to resolve the disputes arising from their deployment in society and interactions with humans. Moreover, safety measures and mitigation rules can be coined to guide their implementation and interactions with humans in a manner that produces greater safety and progress trade-offs. Human-AI collaboration may present optimal gains than autonomous AI that will have limited personal indulgence over an extended array of tasks and deployments. Design concept and considerations have to tackle the existential concerns of AI overtaking human capacity across diverse functions, which could spell doom to the companies deploying the technologies in their operations and logistical functions.
In principle, legal personality can be assigned to whatever entities that emerge through their interactions and dealings to satisfy conditions that warrant such designations. The corporation remerged in the aftermath of the industrial revolution and attained legal personhood through its unique and elaborate dispositions. Artificial Intelligence entities will soon suffice such designation because they occupy a very special position in the futuristic economy as the central pillars in commerce and industry[7]. The complexity with AI is that its varieties of forms and functions may be hard to identify in legal prescriptions effectively and its varied features may pose far greater complexity in the application of legal personality. For instance, AI facilities of the nanotechnology domain may be hard to define in the fields of biotechnology, where the use of AI is moving rapidly. Nonetheless, the task of classification is a relatively easy one because all the variants of AI functions and mechanisms in their deployment can be spelt effectively.
Strong artificial intelligence, which is characterized as a philosophical personality is what qualifies to have a legal personality because such an entity can form opinions and execute their influence autonomously. Weak artificial intelligence is generally at the mercy of human manipulation and can do little beyond human input and control. The process of coding laws and regulations for the AI facilities developed from diverse laboratories will have to take into account classification models that enable orchestrated and robust legal formulation for the sector. As the industry advances and more significant risks are posed to humans and property by the AI gadgets, it will be necessary to expand the legal scope to cater for all the implements initiated in the industry that affect the society in whatever unique ways that they occur.
There is immense uncertainty in the functions of AI guided systems, particularly because they can learn new concepts based on their unique programming options and interactions within the domains of operations. The complexity is further exacerbated by the fact that most of their functions are meant to be automated and intercepting such automation may require a time lag[8]. Human interactions with such automated systems may pose a considerable danger, particularly within manufacturing plants where risks are heightened by the immensity of force and power involved. Asserting legal precedent and rules within such delicate and diversely complex situations can be a daunting task and will take a great deal of technical and legal convergence to facilitate[9]. The challenges of mediating in such gaps are future challenges the legal profession has to confront progressively so that a future of human-AI interaction is secured.
It is widely predicted that the world is moving towards decentralized systems and this tendency is created by the fact that blockchain and supercomputing will enable rapid data processing on a massive scale making it possible for the markets to assume high decentralization. The progress will create immense effects on the political and international relations frontiers. Among the European Union (EU) member states, privacy laws have been strictly protected in the traditional sense, and this is a threat to the deployment of useful AI and machine learning which entirely depends on data. The General Data Protection Regulations (GDPR) in EU legislation will have to adjust to the new typology in which national or international competitiveness will be influenced by the pace at which laws enable innovation and progress using new digital technologies. The UE has demonstrated a rigid approach to privacy laws, which will hurt its advancement in the face of international competition taking shape and mainly depending on the use of private data to shape machine-learning programs. The associated AI technologies and analytics can be used through social media platforms to guide public opinions, and perceptions about political agendas governing political elections, and this area has gained considerable attention. Regulations need to be exerted in such fields, and the affiliated companies should exercise more significant cautionary measures to safeguard democratic principles.
Since many nations are merely competing in commerce and industrial advancement through technology, advanced nations may use their scintific industrial and technological capabilities to defeat less developed nations. Therefore, AI technology, in global logistics may provide useful business intelligence and trade advantages to the advanced nations. In the fields of military operations, advanced AI may already present serious tactical advantages in the conduct of warfare than any other technologies of the past. Face recognition technologies applied to AI have made the Chinese government a leader in state surveillance operations, and many other countries are following the lead. These advances may critically alter the nature of international relations and the balance of power among nations leading to massive changes in commerce, industry, and governance[10].
Disruptive technologies exhibit high rates of change and innovation in society, which need to be supported because the future is undeniably technological. Within legal professions, the deployment of machine learning and natural language processing (NLP) functions, most of the data-oriented tasks can effectively be solved with machines. Moreover, the law and regulatory systems need to create the room for research and innovation by allowing critical progress to advance unperturbed. The challenge of AI and other futuristic technologies is their diversity and complexity of mechanisms in which they are deployed. Forming a uniform body of law to cater for all such diverse circumstances is not practically possible. However, with the adoption of AI in the legal profession, far greater ease may be experienced in developing a consistent process of legislations and regulations for the sectors. Moreover, a future of advanced AI will yield far greater solutions to the contemporary worries and problems because the technology has the capacity for learning and correcting its own problems when the relevant quality and quantity of data is available.
Alarie, Benjamin, Anthony Niblett, and Albert H. Yoon. "How artificial intelligence will affect the practice of law." University of Toronto Law Journal 68, no. supplement 1 (2018): 106-124.
Bliznets, Ivan Anatol’yevich, Aleksandr Amiranovich Kartskhiya, and Mikhail Guramovich Smirnov. "Technology Transfer in Digital Era: Legal Environment." (Journal of History Culture and Art Research 7, no. 1 (2018): 354-363.)
Cath, Corinne. "Governing artificial intelligence: ethical, legal and technical opportunities and challenges." (2018): 20180080.
Dobrinoiu, Maxim. "The Influence of Artificial Intelligence on Criminal Liability." LESIJ-Lex ET Scientia International Journal 26, no. 1 (2019): 140-147.
Hildebrandt, Mireille. "Law as computation in the era of artificial legal intelligence: Speaking law to the power of statistics." University of Toronto Law Journal 68, no. supplement 1 (2018): 12-35.
Mills, Michael. "Artificial intelligence in law: The state of play 2016." (Thomson Reuters Legal Executive Institute. 2016.)
Naučius, Mindaugas. "Should fully autonomous artificial intelligence systems be granted legal capacity?." Teisės apžvalga 1 (17) (2018): 113-132.
Singh, Sh. "Attribution of legal personhood to artificially intelligent beings." Bharati Law Review (2017): 194-201.
Villaronga, Eduard Fosch, Peter Kieseberg, and Tiffany Li. "Humans forget, machines remember: Artificial intelligence and the right to be forgotten." Computer Law & Security Review 34, no. 2 (2018): 304-313.
[1]. Naučius, Mindaugas. "Should fully autonomous artificial intelligence systems be granted legal capacity?." (Teisės apžvalga 1 (17) (2018): 113-132.) [2]. Singh, Sh. "Attribution of legal personhood to artificially intelligent beings." (Bharati Law Review (2017): 194-201.) [3]. Jones v. W+ M Automation, Inc., 31 A.D.3d 1099, 818 N.Y.S.2d 396 (App. Div. 2006). [4]. Bliznets, Ivan Anatol’yevich, Aleksandr Amiranovich Kartskhiya, and Mikhail Guramovich Smirnov. "Technology Transfer in Digital Era: Legal Environment." (Journal of History Culture and Art Research 7, no. 1 (2018): 354-363.) [5]. Alarie, Benjamin, Anthony Niblett, and Albert H. Yoon. "How artificial intelligence will affect the practice of law." (University of Toronto Law Journal 68, no. supplement 1 (2018): 106-124.) [6]. Cath, Corinne. "Governing artificial intelligence: ethical, legal and technical opportunities and challenges." (2018): 20180080. [7]. Mills, Michael. "Artificial intelligence in law: The state of play 2016." (Thomson Reuters Legal Executive Institute. 2016.) [8]. Dobrinoiu, Maxim. "The Influence of Artificial Intelligence on Criminal Liability." LESIJ-Lex ET Scientia International Journal 26, no. 1 (2019): 140-147. [9]. Villaronga, Eduard Fosch, Peter Kieseberg, and Tiffany Li. "Humans forget, machines remember: Artificial intelligence and the right to be forgotten." (Computer Law & Security Review 34, no. 2 (2018): 304-313.) [10]. Hildebrandt, Mireille. "Law as computation in the era of artificial legal intelligence: Speaking law to the power of statistics." University of Toronto Law Journal 68, no. supplement 1 (2018): 12-35.
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